program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3304.5.2"}, {"coremlc-version", "3304.6.2"}})]
{
    func main<ios16>(tensor<fp32, [1, 77]> input_ids) {
            tensor<int32, []> var_5 = const()[name = tensor<string, []>("op_5"), val = tensor<int32, []>(-1)];
            tensor<bool, []> var_6 = const()[name = tensor<string, []>("op_6"), val = tensor<bool, []>(false)];
            tensor<string, []> cast_1_dtype_0 = const()[name = tensor<string, []>("cast_1_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> inputs_embeds_axis_0 = const()[name = tensor<string, []>("inputs_embeds_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> inputs_embeds_batch_dims_0 = const()[name = tensor<string, []>("inputs_embeds_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [49408, 1280]> text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor<fp16, [49408, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<int32, [1, 77]> cast_1 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = tensor<string, []>("cast_2")];
            tensor<fp16, [1, 77, 1280]> inputs_embeds_cast_fp16 = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = cast_1, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor<string, []>("inputs_embeds_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> position_embeddings_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [73920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126484608))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126558592))), name = tensor<string, []>("position_embeddings_to_fp16_palettized"), shape = tensor<uint32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 1280]> input_3_cast_fp16 = add(x = inputs_embeds_cast_fp16, y = position_embeddings_to_fp16_palettized)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<int32, [1]> hidden_states_1_axes_0 = const()[name = tensor<string, []>("hidden_states_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126558784)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126561408)))];
            tensor<fp16, []> var_15_to_fp16 = const()[name = tensor<string, []>("op_15_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 77, 1280]> hidden_states_1_cast_fp16 = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("hidden_states_1_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126564032))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(127792896))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(127793088)))];
            tensor<fp16, [1, 77, 1280]> linear_0_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<fp16, []> var_149_to_fp16 = const()[name = tensor<string, []>("op_149_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_5_cast_fp16 = mul(x = linear_0_cast_fp16, y = var_149_to_fp16)[name = tensor<string, []>("tensor_5_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(127795712))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129024576))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129024768)))];
            tensor<fp16, [1, 77, 1280]> linear_1_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
            tensor<int32, [4]> var_154 = const()[name = tensor<string, []>("op_154"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_155_cast_fp16 = reshape(shape = var_154, x = linear_1_cast_fp16)[name = tensor<string, []>("op_155_cast_fp16")];
            tensor<int32, [4]> var_156_perm_0 = const()[name = tensor<string, []>("op_156_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129027392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130256256))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130256448)))];
            tensor<fp16, [1, 77, 1280]> linear_2_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
            tensor<int32, [4]> var_161 = const()[name = tensor<string, []>("op_161"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_162_cast_fp16 = reshape(shape = var_161, x = linear_2_cast_fp16)[name = tensor<string, []>("op_162_cast_fp16")];
            tensor<int32, [4]> var_163_perm_0 = const()[name = tensor<string, []>("op_163_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_170 = const()[name = tensor<string, []>("op_170"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_171_cast_fp16 = reshape(shape = var_170, x = tensor_5_cast_fp16)[name = tensor<string, []>("op_171_cast_fp16")];
            tensor<int32, [4]> var_172_perm_0 = const()[name = tensor<string, []>("op_172_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_174 = const()[name = tensor<string, []>("op_174"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_172_cast_fp16 = transpose(perm = var_172_perm_0, x = var_171_cast_fp16)[name = tensor<string, []>("transpose_127")];
            tensor<fp16, [20, 77, 64]> query_states_1_cast_fp16 = reshape(shape = var_174, x = var_172_cast_fp16)[name = tensor<string, []>("query_states_1_cast_fp16")];
            tensor<int32, [3]> var_176 = const()[name = tensor<string, []>("op_176"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_156_cast_fp16 = transpose(perm = var_156_perm_0, x = var_155_cast_fp16)[name = tensor<string, []>("transpose_126")];
            tensor<fp16, [20, 77, 64]> key_states_3_cast_fp16 = reshape(shape = var_176, x = var_156_cast_fp16)[name = tensor<string, []>("key_states_3_cast_fp16")];
            tensor<int32, [3]> var_178 = const()[name = tensor<string, []>("op_178"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_163_cast_fp16 = transpose(perm = var_163_perm_0, x = var_162_cast_fp16)[name = tensor<string, []>("transpose_125")];
            tensor<fp16, [20, 77, 64]> value_states_3_cast_fp16 = reshape(shape = var_178, x = var_163_cast_fp16)[name = tensor<string, []>("value_states_3_cast_fp16")];
            tensor<bool, []> attn_weights_1_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_1_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_1_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_1_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_1_cast_fp16 = matmul(transpose_x = attn_weights_1_transpose_x_1, transpose_y = attn_weights_1_transpose_y_1, x = query_states_1_cast_fp16, y = key_states_3_cast_fp16)[name = tensor<string, []>("attn_weights_1_cast_fp16")];
            tensor<int32, [4]> var_183 = const()[name = tensor<string, []>("op_183"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_184_cast_fp16 = reshape(shape = var_183, x = attn_weights_1_cast_fp16)[name = tensor<string, []>("op_184_cast_fp16")];
            tensor<fp16, [1, 1, 77, 77]> op_58_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4447]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130259072))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130263616))), name = tensor<string, []>("op_58_to_fp16_palettized"), shape = tensor<uint32, [4]>([1, 1, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_3_cast_fp16 = add(x = var_184_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_3_cast_fp16")];
            tensor<int32, [3]> var_189 = const()[name = tensor<string, []>("op_189"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_5_cast_fp16 = reshape(shape = var_189, x = attn_weights_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_7_cast_fp16 = softmax(axis = var_5, x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<bool, []> attn_output_1_transpose_x_0 = const()[name = tensor<string, []>("attn_output_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_1_transpose_y_0 = const()[name = tensor<string, []>("attn_output_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_1_cast_fp16 = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast_fp16, y = value_states_3_cast_fp16)[name = tensor<string, []>("attn_output_1_cast_fp16")];
            tensor<int32, [4]> var_194 = const()[name = tensor<string, []>("op_194"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_3_cast_fp16 = reshape(shape = var_194, x = attn_output_1_cast_fp16)[name = tensor<string, []>("attn_output_3_cast_fp16")];
            tensor<int32, [4]> attn_output_5_perm_0 = const()[name = tensor<string, []>("attn_output_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_197 = const()[name = tensor<string, []>("op_197"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_5_cast_fp16 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast_fp16)[name = tensor<string, []>("transpose_124")];
            tensor<fp16, [1, 77, 1280]> input_9_cast_fp16 = reshape(shape = var_197, x = attn_output_5_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130263808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131492672))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131492864)))];
            tensor<fp16, [1, 77, 1280]> linear_3_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_9_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_11_cast_fp16 = add(x = input_3_cast_fp16, y = linear_3_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<int32, [1]> input_13_axes_0 = const()[name = tensor<string, []>("input_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131495488)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131498112)))];
            tensor<fp16, [1, 77, 1280]> input_13_cast_fp16 = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131500736))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136416000))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136416192)))];
            tensor<fp16, [1, 77, 5120]> linear_4_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_13_cast_fp16)[name = tensor<string, []>("linear_4_cast_fp16")];
            tensor<string, []> input_17_mode_0 = const()[name = tensor<string, []>("input_17_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_17_cast_fp16 = gelu(mode = input_17_mode_0, x = linear_4_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136426496))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141341760))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141341952)))];
            tensor<fp16, [1, 77, 1280]> linear_5_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized, x = input_17_cast_fp16)[name = tensor<string, []>("linear_5_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_19_cast_fp16 = add(x = input_11_cast_fp16, y = linear_5_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
            tensor<int32, [1]> hidden_states_7_axes_0 = const()[name = tensor<string, []>("hidden_states_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141344576)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141347200)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_7_cast_fp16 = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("hidden_states_7_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141349824))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142578688))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142578880)))];
            tensor<fp16, [1, 77, 1280]> linear_6_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_7_cast_fp16)[name = tensor<string, []>("linear_6_cast_fp16")];
            tensor<fp16, []> var_236_to_fp16 = const()[name = tensor<string, []>("op_236_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_11_cast_fp16 = mul(x = linear_6_cast_fp16, y = var_236_to_fp16)[name = tensor<string, []>("tensor_11_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142581504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143810368))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143810560)))];
            tensor<fp16, [1, 77, 1280]> linear_7_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_7_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
            tensor<int32, [4]> var_241 = const()[name = tensor<string, []>("op_241"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_242_cast_fp16 = reshape(shape = var_241, x = linear_7_cast_fp16)[name = tensor<string, []>("op_242_cast_fp16")];
            tensor<int32, [4]> var_243_perm_0 = const()[name = tensor<string, []>("op_243_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143813184))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145042048))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145042240)))];
            tensor<fp16, [1, 77, 1280]> linear_8_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_7_cast_fp16)[name = tensor<string, []>("linear_8_cast_fp16")];
            tensor<int32, [4]> var_248 = const()[name = tensor<string, []>("op_248"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_249_cast_fp16 = reshape(shape = var_248, x = linear_8_cast_fp16)[name = tensor<string, []>("op_249_cast_fp16")];
            tensor<int32, [4]> var_250_perm_0 = const()[name = tensor<string, []>("op_250_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_257 = const()[name = tensor<string, []>("op_257"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_258_cast_fp16 = reshape(shape = var_257, x = tensor_11_cast_fp16)[name = tensor<string, []>("op_258_cast_fp16")];
            tensor<int32, [4]> var_259_perm_0 = const()[name = tensor<string, []>("op_259_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_261 = const()[name = tensor<string, []>("op_261"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_259_cast_fp16 = transpose(perm = var_259_perm_0, x = var_258_cast_fp16)[name = tensor<string, []>("transpose_123")];
            tensor<fp16, [20, 77, 64]> query_states_3_cast_fp16 = reshape(shape = var_261, x = var_259_cast_fp16)[name = tensor<string, []>("query_states_3_cast_fp16")];
            tensor<int32, [3]> var_263 = const()[name = tensor<string, []>("op_263"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_243_cast_fp16 = transpose(perm = var_243_perm_0, x = var_242_cast_fp16)[name = tensor<string, []>("transpose_122")];
            tensor<fp16, [20, 77, 64]> key_states_7_cast_fp16 = reshape(shape = var_263, x = var_243_cast_fp16)[name = tensor<string, []>("key_states_7_cast_fp16")];
            tensor<int32, [3]> var_265 = const()[name = tensor<string, []>("op_265"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_250_cast_fp16 = transpose(perm = var_250_perm_0, x = var_249_cast_fp16)[name = tensor<string, []>("transpose_121")];
            tensor<fp16, [20, 77, 64]> value_states_7_cast_fp16 = reshape(shape = var_265, x = var_250_cast_fp16)[name = tensor<string, []>("value_states_7_cast_fp16")];
            tensor<bool, []> attn_weights_7_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_7_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_7_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_7_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_7_cast_fp16 = matmul(transpose_x = attn_weights_7_transpose_x_1, transpose_y = attn_weights_7_transpose_y_1, x = query_states_3_cast_fp16, y = key_states_7_cast_fp16)[name = tensor<string, []>("attn_weights_7_cast_fp16")];
            tensor<int32, [4]> var_270 = const()[name = tensor<string, []>("op_270"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_271_cast_fp16 = reshape(shape = var_270, x = attn_weights_7_cast_fp16)[name = tensor<string, []>("op_271_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_9_cast_fp16 = add(x = var_271_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_9_cast_fp16")];
            tensor<int32, [3]> var_276 = const()[name = tensor<string, []>("op_276"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_21_cast_fp16 = reshape(shape = var_276, x = attn_weights_9_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_23_cast_fp16 = softmax(axis = var_5, x = input_21_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")];
            tensor<bool, []> attn_output_7_transpose_x_0 = const()[name = tensor<string, []>("attn_output_7_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_7_transpose_y_0 = const()[name = tensor<string, []>("attn_output_7_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_7_cast_fp16 = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast_fp16, y = value_states_7_cast_fp16)[name = tensor<string, []>("attn_output_7_cast_fp16")];
            tensor<int32, [4]> var_281 = const()[name = tensor<string, []>("op_281"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_9_cast_fp16 = reshape(shape = var_281, x = attn_output_7_cast_fp16)[name = tensor<string, []>("attn_output_9_cast_fp16")];
            tensor<int32, [4]> attn_output_11_perm_0 = const()[name = tensor<string, []>("attn_output_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_284 = const()[name = tensor<string, []>("op_284"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_11_cast_fp16 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast_fp16)[name = tensor<string, []>("transpose_120")];
            tensor<fp16, [1, 77, 1280]> input_25_cast_fp16 = reshape(shape = var_284, x = attn_output_11_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145044864))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146273728))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146273920)))];
            tensor<fp16, [1, 77, 1280]> linear_9_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast_fp16)[name = tensor<string, []>("linear_9_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_27_cast_fp16 = add(x = input_19_cast_fp16, y = linear_9_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = tensor<string, []>("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146276544)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146279168)))];
            tensor<fp16, [1, 77, 1280]> input_29_cast_fp16 = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146281792))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151197056))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151197248)))];
            tensor<fp16, [1, 77, 5120]> linear_10_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast_fp16)[name = tensor<string, []>("linear_10_cast_fp16")];
            tensor<string, []> input_33_mode_0 = const()[name = tensor<string, []>("input_33_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = linear_10_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151207552))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(156122816))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(156123008)))];
            tensor<fp16, [1, 77, 1280]> linear_11_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized, x = input_33_cast_fp16)[name = tensor<string, []>("linear_11_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_35_cast_fp16 = add(x = input_27_cast_fp16, y = linear_11_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
            tensor<int32, [1]> hidden_states_13_axes_0 = const()[name = tensor<string, []>("hidden_states_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(156125632)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(156128256)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_13_cast_fp16 = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("hidden_states_13_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(156130880))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157359744))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157359936)))];
            tensor<fp16, [1, 77, 1280]> linear_12_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_13_cast_fp16)[name = tensor<string, []>("linear_12_cast_fp16")];
            tensor<fp16, []> var_323_to_fp16 = const()[name = tensor<string, []>("op_323_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_17_cast_fp16 = mul(x = linear_12_cast_fp16, y = var_323_to_fp16)[name = tensor<string, []>("tensor_17_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157362560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158591424))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158591616)))];
            tensor<fp16, [1, 77, 1280]> linear_13_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_13_cast_fp16)[name = tensor<string, []>("linear_13_cast_fp16")];
            tensor<int32, [4]> var_328 = const()[name = tensor<string, []>("op_328"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_329_cast_fp16 = reshape(shape = var_328, x = linear_13_cast_fp16)[name = tensor<string, []>("op_329_cast_fp16")];
            tensor<int32, [4]> var_330_perm_0 = const()[name = tensor<string, []>("op_330_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158594240))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159823104))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159823296)))];
            tensor<fp16, [1, 77, 1280]> linear_14_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_13_cast_fp16)[name = tensor<string, []>("linear_14_cast_fp16")];
            tensor<int32, [4]> var_335 = const()[name = tensor<string, []>("op_335"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_336_cast_fp16 = reshape(shape = var_335, x = linear_14_cast_fp16)[name = tensor<string, []>("op_336_cast_fp16")];
            tensor<int32, [4]> var_337_perm_0 = const()[name = tensor<string, []>("op_337_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_344 = const()[name = tensor<string, []>("op_344"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_345_cast_fp16 = reshape(shape = var_344, x = tensor_17_cast_fp16)[name = tensor<string, []>("op_345_cast_fp16")];
            tensor<int32, [4]> var_346_perm_0 = const()[name = tensor<string, []>("op_346_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_348 = const()[name = tensor<string, []>("op_348"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_346_cast_fp16 = transpose(perm = var_346_perm_0, x = var_345_cast_fp16)[name = tensor<string, []>("transpose_119")];
            tensor<fp16, [20, 77, 64]> query_states_5_cast_fp16 = reshape(shape = var_348, x = var_346_cast_fp16)[name = tensor<string, []>("query_states_5_cast_fp16")];
            tensor<int32, [3]> var_350 = const()[name = tensor<string, []>("op_350"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_330_cast_fp16 = transpose(perm = var_330_perm_0, x = var_329_cast_fp16)[name = tensor<string, []>("transpose_118")];
            tensor<fp16, [20, 77, 64]> key_states_11_cast_fp16 = reshape(shape = var_350, x = var_330_cast_fp16)[name = tensor<string, []>("key_states_11_cast_fp16")];
            tensor<int32, [3]> var_352 = const()[name = tensor<string, []>("op_352"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_337_cast_fp16 = transpose(perm = var_337_perm_0, x = var_336_cast_fp16)[name = tensor<string, []>("transpose_117")];
            tensor<fp16, [20, 77, 64]> value_states_11_cast_fp16 = reshape(shape = var_352, x = var_337_cast_fp16)[name = tensor<string, []>("value_states_11_cast_fp16")];
            tensor<bool, []> attn_weights_13_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_13_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_13_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_13_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_13_cast_fp16 = matmul(transpose_x = attn_weights_13_transpose_x_1, transpose_y = attn_weights_13_transpose_y_1, x = query_states_5_cast_fp16, y = key_states_11_cast_fp16)[name = tensor<string, []>("attn_weights_13_cast_fp16")];
            tensor<int32, [4]> var_357 = const()[name = tensor<string, []>("op_357"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_358_cast_fp16 = reshape(shape = var_357, x = attn_weights_13_cast_fp16)[name = tensor<string, []>("op_358_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_15_cast_fp16 = add(x = var_358_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_15_cast_fp16")];
            tensor<int32, [3]> var_363 = const()[name = tensor<string, []>("op_363"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_37_cast_fp16 = reshape(shape = var_363, x = attn_weights_15_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_39_cast_fp16 = softmax(axis = var_5, x = input_37_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
            tensor<bool, []> attn_output_13_transpose_x_0 = const()[name = tensor<string, []>("attn_output_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_13_transpose_y_0 = const()[name = tensor<string, []>("attn_output_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_13_cast_fp16 = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast_fp16, y = value_states_11_cast_fp16)[name = tensor<string, []>("attn_output_13_cast_fp16")];
            tensor<int32, [4]> var_368 = const()[name = tensor<string, []>("op_368"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_15_cast_fp16 = reshape(shape = var_368, x = attn_output_13_cast_fp16)[name = tensor<string, []>("attn_output_15_cast_fp16")];
            tensor<int32, [4]> attn_output_17_perm_0 = const()[name = tensor<string, []>("attn_output_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_371 = const()[name = tensor<string, []>("op_371"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_17_cast_fp16 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast_fp16)[name = tensor<string, []>("transpose_116")];
            tensor<fp16, [1, 77, 1280]> input_41_cast_fp16 = reshape(shape = var_371, x = attn_output_17_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159825920))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161054784))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161054976)))];
            tensor<fp16, [1, 77, 1280]> linear_15_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_41_cast_fp16)[name = tensor<string, []>("linear_15_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_43_cast_fp16 = add(x = input_35_cast_fp16, y = linear_15_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
            tensor<int32, [1]> input_45_axes_0 = const()[name = tensor<string, []>("input_45_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161057600)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161060224)))];
            tensor<fp16, [1, 77, 1280]> input_45_cast_fp16 = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161062848))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165978112))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165978304)))];
            tensor<fp16, [1, 77, 5120]> linear_16_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_45_cast_fp16)[name = tensor<string, []>("linear_16_cast_fp16")];
            tensor<string, []> input_49_mode_0 = const()[name = tensor<string, []>("input_49_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = linear_16_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165988608))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170903872))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170904064)))];
            tensor<fp16, [1, 77, 1280]> linear_17_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized, x = input_49_cast_fp16)[name = tensor<string, []>("linear_17_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_51_cast_fp16 = add(x = input_43_cast_fp16, y = linear_17_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<int32, [1]> hidden_states_19_axes_0 = const()[name = tensor<string, []>("hidden_states_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170906688)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170909312)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_19_cast_fp16 = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast_fp16)[name = tensor<string, []>("hidden_states_19_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170911936))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172140800))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172140992)))];
            tensor<fp16, [1, 77, 1280]> linear_18_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_19_cast_fp16)[name = tensor<string, []>("linear_18_cast_fp16")];
            tensor<fp16, []> var_410_to_fp16 = const()[name = tensor<string, []>("op_410_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_23_cast_fp16 = mul(x = linear_18_cast_fp16, y = var_410_to_fp16)[name = tensor<string, []>("tensor_23_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172143616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173372480))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173372672)))];
            tensor<fp16, [1, 77, 1280]> linear_19_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_19_cast_fp16)[name = tensor<string, []>("linear_19_cast_fp16")];
            tensor<int32, [4]> var_415 = const()[name = tensor<string, []>("op_415"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_416_cast_fp16 = reshape(shape = var_415, x = linear_19_cast_fp16)[name = tensor<string, []>("op_416_cast_fp16")];
            tensor<int32, [4]> var_417_perm_0 = const()[name = tensor<string, []>("op_417_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173375296))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174604160))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174604352)))];
            tensor<fp16, [1, 77, 1280]> linear_20_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_19_cast_fp16)[name = tensor<string, []>("linear_20_cast_fp16")];
            tensor<int32, [4]> var_422 = const()[name = tensor<string, []>("op_422"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_423_cast_fp16 = reshape(shape = var_422, x = linear_20_cast_fp16)[name = tensor<string, []>("op_423_cast_fp16")];
            tensor<int32, [4]> var_424_perm_0 = const()[name = tensor<string, []>("op_424_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_431 = const()[name = tensor<string, []>("op_431"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_432_cast_fp16 = reshape(shape = var_431, x = tensor_23_cast_fp16)[name = tensor<string, []>("op_432_cast_fp16")];
            tensor<int32, [4]> var_433_perm_0 = const()[name = tensor<string, []>("op_433_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_435 = const()[name = tensor<string, []>("op_435"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_433_cast_fp16 = transpose(perm = var_433_perm_0, x = var_432_cast_fp16)[name = tensor<string, []>("transpose_115")];
            tensor<fp16, [20, 77, 64]> query_states_7_cast_fp16 = reshape(shape = var_435, x = var_433_cast_fp16)[name = tensor<string, []>("query_states_7_cast_fp16")];
            tensor<int32, [3]> var_437 = const()[name = tensor<string, []>("op_437"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_417_cast_fp16 = transpose(perm = var_417_perm_0, x = var_416_cast_fp16)[name = tensor<string, []>("transpose_114")];
            tensor<fp16, [20, 77, 64]> key_states_15_cast_fp16 = reshape(shape = var_437, x = var_417_cast_fp16)[name = tensor<string, []>("key_states_15_cast_fp16")];
            tensor<int32, [3]> var_439 = const()[name = tensor<string, []>("op_439"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_424_cast_fp16 = transpose(perm = var_424_perm_0, x = var_423_cast_fp16)[name = tensor<string, []>("transpose_113")];
            tensor<fp16, [20, 77, 64]> value_states_15_cast_fp16 = reshape(shape = var_439, x = var_424_cast_fp16)[name = tensor<string, []>("value_states_15_cast_fp16")];
            tensor<bool, []> attn_weights_19_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_19_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_19_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_19_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_19_cast_fp16 = matmul(transpose_x = attn_weights_19_transpose_x_1, transpose_y = attn_weights_19_transpose_y_1, x = query_states_7_cast_fp16, y = key_states_15_cast_fp16)[name = tensor<string, []>("attn_weights_19_cast_fp16")];
            tensor<int32, [4]> var_444 = const()[name = tensor<string, []>("op_444"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_445_cast_fp16 = reshape(shape = var_444, x = attn_weights_19_cast_fp16)[name = tensor<string, []>("op_445_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_21_cast_fp16 = add(x = var_445_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_21_cast_fp16")];
            tensor<int32, [3]> var_450 = const()[name = tensor<string, []>("op_450"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_53_cast_fp16 = reshape(shape = var_450, x = attn_weights_21_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_55_cast_fp16 = softmax(axis = var_5, x = input_53_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")];
            tensor<bool, []> attn_output_19_transpose_x_0 = const()[name = tensor<string, []>("attn_output_19_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_19_transpose_y_0 = const()[name = tensor<string, []>("attn_output_19_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_19_cast_fp16 = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast_fp16, y = value_states_15_cast_fp16)[name = tensor<string, []>("attn_output_19_cast_fp16")];
            tensor<int32, [4]> var_455 = const()[name = tensor<string, []>("op_455"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_21_cast_fp16 = reshape(shape = var_455, x = attn_output_19_cast_fp16)[name = tensor<string, []>("attn_output_21_cast_fp16")];
            tensor<int32, [4]> attn_output_23_perm_0 = const()[name = tensor<string, []>("attn_output_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_458 = const()[name = tensor<string, []>("op_458"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_23_cast_fp16 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast_fp16)[name = tensor<string, []>("transpose_112")];
            tensor<fp16, [1, 77, 1280]> input_57_cast_fp16 = reshape(shape = var_458, x = attn_output_23_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174606976))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175835840))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175836032)))];
            tensor<fp16, [1, 77, 1280]> linear_21_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_57_cast_fp16)[name = tensor<string, []>("linear_21_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_59_cast_fp16 = add(x = input_51_cast_fp16, y = linear_21_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<int32, [1]> input_61_axes_0 = const()[name = tensor<string, []>("input_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175838656)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175841280)))];
            tensor<fp16, [1, 77, 1280]> input_61_cast_fp16 = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175843904))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180759168))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180759360)))];
            tensor<fp16, [1, 77, 5120]> linear_22_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_61_cast_fp16)[name = tensor<string, []>("linear_22_cast_fp16")];
            tensor<string, []> input_65_mode_0 = const()[name = tensor<string, []>("input_65_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_65_cast_fp16 = gelu(mode = input_65_mode_0, x = linear_22_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180769664))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185684928))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185685120)))];
            tensor<fp16, [1, 77, 1280]> linear_23_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized, x = input_65_cast_fp16)[name = tensor<string, []>("linear_23_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_67_cast_fp16 = add(x = input_59_cast_fp16, y = linear_23_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
            tensor<int32, [1]> hidden_states_25_axes_0 = const()[name = tensor<string, []>("hidden_states_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185687744)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185690368)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_25_cast_fp16 = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("hidden_states_25_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185692992))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186921856))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186922048)))];
            tensor<fp16, [1, 77, 1280]> linear_24_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_25_cast_fp16)[name = tensor<string, []>("linear_24_cast_fp16")];
            tensor<fp16, []> var_497_to_fp16 = const()[name = tensor<string, []>("op_497_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_29_cast_fp16 = mul(x = linear_24_cast_fp16, y = var_497_to_fp16)[name = tensor<string, []>("tensor_29_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186924672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188153536))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188153728)))];
            tensor<fp16, [1, 77, 1280]> linear_25_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_25_cast_fp16)[name = tensor<string, []>("linear_25_cast_fp16")];
            tensor<int32, [4]> var_502 = const()[name = tensor<string, []>("op_502"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_503_cast_fp16 = reshape(shape = var_502, x = linear_25_cast_fp16)[name = tensor<string, []>("op_503_cast_fp16")];
            tensor<int32, [4]> var_504_perm_0 = const()[name = tensor<string, []>("op_504_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188156352))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189385216))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189385408)))];
            tensor<fp16, [1, 77, 1280]> linear_26_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_25_cast_fp16)[name = tensor<string, []>("linear_26_cast_fp16")];
            tensor<int32, [4]> var_509 = const()[name = tensor<string, []>("op_509"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_510_cast_fp16 = reshape(shape = var_509, x = linear_26_cast_fp16)[name = tensor<string, []>("op_510_cast_fp16")];
            tensor<int32, [4]> var_511_perm_0 = const()[name = tensor<string, []>("op_511_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_518 = const()[name = tensor<string, []>("op_518"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_519_cast_fp16 = reshape(shape = var_518, x = tensor_29_cast_fp16)[name = tensor<string, []>("op_519_cast_fp16")];
            tensor<int32, [4]> var_520_perm_0 = const()[name = tensor<string, []>("op_520_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_522 = const()[name = tensor<string, []>("op_522"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_520_cast_fp16 = transpose(perm = var_520_perm_0, x = var_519_cast_fp16)[name = tensor<string, []>("transpose_111")];
            tensor<fp16, [20, 77, 64]> query_states_9_cast_fp16 = reshape(shape = var_522, x = var_520_cast_fp16)[name = tensor<string, []>("query_states_9_cast_fp16")];
            tensor<int32, [3]> var_524 = const()[name = tensor<string, []>("op_524"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_504_cast_fp16 = transpose(perm = var_504_perm_0, x = var_503_cast_fp16)[name = tensor<string, []>("transpose_110")];
            tensor<fp16, [20, 77, 64]> key_states_19_cast_fp16 = reshape(shape = var_524, x = var_504_cast_fp16)[name = tensor<string, []>("key_states_19_cast_fp16")];
            tensor<int32, [3]> var_526 = const()[name = tensor<string, []>("op_526"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_511_cast_fp16 = transpose(perm = var_511_perm_0, x = var_510_cast_fp16)[name = tensor<string, []>("transpose_109")];
            tensor<fp16, [20, 77, 64]> value_states_19_cast_fp16 = reshape(shape = var_526, x = var_511_cast_fp16)[name = tensor<string, []>("value_states_19_cast_fp16")];
            tensor<bool, []> attn_weights_25_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_25_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_25_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_25_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_25_cast_fp16 = matmul(transpose_x = attn_weights_25_transpose_x_1, transpose_y = attn_weights_25_transpose_y_1, x = query_states_9_cast_fp16, y = key_states_19_cast_fp16)[name = tensor<string, []>("attn_weights_25_cast_fp16")];
            tensor<int32, [4]> var_531 = const()[name = tensor<string, []>("op_531"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_532_cast_fp16 = reshape(shape = var_531, x = attn_weights_25_cast_fp16)[name = tensor<string, []>("op_532_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_27_cast_fp16 = add(x = var_532_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_27_cast_fp16")];
            tensor<int32, [3]> var_537 = const()[name = tensor<string, []>("op_537"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_69_cast_fp16 = reshape(shape = var_537, x = attn_weights_27_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_71_cast_fp16 = softmax(axis = var_5, x = input_69_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
            tensor<bool, []> attn_output_25_transpose_x_0 = const()[name = tensor<string, []>("attn_output_25_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_25_transpose_y_0 = const()[name = tensor<string, []>("attn_output_25_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_25_cast_fp16 = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast_fp16, y = value_states_19_cast_fp16)[name = tensor<string, []>("attn_output_25_cast_fp16")];
            tensor<int32, [4]> var_542 = const()[name = tensor<string, []>("op_542"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_27_cast_fp16 = reshape(shape = var_542, x = attn_output_25_cast_fp16)[name = tensor<string, []>("attn_output_27_cast_fp16")];
            tensor<int32, [4]> attn_output_29_perm_0 = const()[name = tensor<string, []>("attn_output_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_545 = const()[name = tensor<string, []>("op_545"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_29_cast_fp16 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast_fp16)[name = tensor<string, []>("transpose_108")];
            tensor<fp16, [1, 77, 1280]> input_73_cast_fp16 = reshape(shape = var_545, x = attn_output_29_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189388032))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190616896))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190617088)))];
            tensor<fp16, [1, 77, 1280]> linear_27_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_73_cast_fp16)[name = tensor<string, []>("linear_27_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_75_cast_fp16 = add(x = input_67_cast_fp16, y = linear_27_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")];
            tensor<int32, [1]> input_77_axes_0 = const()[name = tensor<string, []>("input_77_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190619712)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190622336)))];
            tensor<fp16, [1, 77, 1280]> input_77_cast_fp16 = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190624960))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195540224))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195540416)))];
            tensor<fp16, [1, 77, 5120]> linear_28_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_77_cast_fp16)[name = tensor<string, []>("linear_28_cast_fp16")];
            tensor<string, []> input_81_mode_0 = const()[name = tensor<string, []>("input_81_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_81_cast_fp16 = gelu(mode = input_81_mode_0, x = linear_28_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195550720))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200465984))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200466176)))];
            tensor<fp16, [1, 77, 1280]> linear_29_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized, x = input_81_cast_fp16)[name = tensor<string, []>("linear_29_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_83_cast_fp16 = add(x = input_75_cast_fp16, y = linear_29_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
            tensor<int32, [1]> hidden_states_31_axes_0 = const()[name = tensor<string, []>("hidden_states_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200468800)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200471424)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_31_cast_fp16 = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("hidden_states_31_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200474048))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201702912))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201703104)))];
            tensor<fp16, [1, 77, 1280]> linear_30_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_31_cast_fp16)[name = tensor<string, []>("linear_30_cast_fp16")];
            tensor<fp16, []> var_584_to_fp16 = const()[name = tensor<string, []>("op_584_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_35_cast_fp16 = mul(x = linear_30_cast_fp16, y = var_584_to_fp16)[name = tensor<string, []>("tensor_35_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201705728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202934592))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202934784)))];
            tensor<fp16, [1, 77, 1280]> linear_31_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_31_cast_fp16)[name = tensor<string, []>("linear_31_cast_fp16")];
            tensor<int32, [4]> var_589 = const()[name = tensor<string, []>("op_589"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_590_cast_fp16 = reshape(shape = var_589, x = linear_31_cast_fp16)[name = tensor<string, []>("op_590_cast_fp16")];
            tensor<int32, [4]> var_591_perm_0 = const()[name = tensor<string, []>("op_591_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202937408))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(204166272))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(204166464)))];
            tensor<fp16, [1, 77, 1280]> linear_32_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_31_cast_fp16)[name = tensor<string, []>("linear_32_cast_fp16")];
            tensor<int32, [4]> var_596 = const()[name = tensor<string, []>("op_596"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_597_cast_fp16 = reshape(shape = var_596, x = linear_32_cast_fp16)[name = tensor<string, []>("op_597_cast_fp16")];
            tensor<int32, [4]> var_598_perm_0 = const()[name = tensor<string, []>("op_598_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_605 = const()[name = tensor<string, []>("op_605"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_606_cast_fp16 = reshape(shape = var_605, x = tensor_35_cast_fp16)[name = tensor<string, []>("op_606_cast_fp16")];
            tensor<int32, [4]> var_607_perm_0 = const()[name = tensor<string, []>("op_607_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_609 = const()[name = tensor<string, []>("op_609"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_607_cast_fp16 = transpose(perm = var_607_perm_0, x = var_606_cast_fp16)[name = tensor<string, []>("transpose_107")];
            tensor<fp16, [20, 77, 64]> query_states_11_cast_fp16 = reshape(shape = var_609, x = var_607_cast_fp16)[name = tensor<string, []>("query_states_11_cast_fp16")];
            tensor<int32, [3]> var_611 = const()[name = tensor<string, []>("op_611"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_591_cast_fp16 = transpose(perm = var_591_perm_0, x = var_590_cast_fp16)[name = tensor<string, []>("transpose_106")];
            tensor<fp16, [20, 77, 64]> key_states_23_cast_fp16 = reshape(shape = var_611, x = var_591_cast_fp16)[name = tensor<string, []>("key_states_23_cast_fp16")];
            tensor<int32, [3]> var_613 = const()[name = tensor<string, []>("op_613"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_598_cast_fp16 = transpose(perm = var_598_perm_0, x = var_597_cast_fp16)[name = tensor<string, []>("transpose_105")];
            tensor<fp16, [20, 77, 64]> value_states_23_cast_fp16 = reshape(shape = var_613, x = var_598_cast_fp16)[name = tensor<string, []>("value_states_23_cast_fp16")];
            tensor<bool, []> attn_weights_31_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_31_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_31_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_31_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_31_cast_fp16 = matmul(transpose_x = attn_weights_31_transpose_x_1, transpose_y = attn_weights_31_transpose_y_1, x = query_states_11_cast_fp16, y = key_states_23_cast_fp16)[name = tensor<string, []>("attn_weights_31_cast_fp16")];
            tensor<int32, [4]> var_618 = const()[name = tensor<string, []>("op_618"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_619_cast_fp16 = reshape(shape = var_618, x = attn_weights_31_cast_fp16)[name = tensor<string, []>("op_619_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_33_cast_fp16 = add(x = var_619_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_33_cast_fp16")];
            tensor<int32, [3]> var_624 = const()[name = tensor<string, []>("op_624"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_85_cast_fp16 = reshape(shape = var_624, x = attn_weights_33_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_87_cast_fp16 = softmax(axis = var_5, x = input_85_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")];
            tensor<bool, []> attn_output_31_transpose_x_0 = const()[name = tensor<string, []>("attn_output_31_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_31_transpose_y_0 = const()[name = tensor<string, []>("attn_output_31_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_31_cast_fp16 = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast_fp16, y = value_states_23_cast_fp16)[name = tensor<string, []>("attn_output_31_cast_fp16")];
            tensor<int32, [4]> var_629 = const()[name = tensor<string, []>("op_629"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_33_cast_fp16 = reshape(shape = var_629, x = attn_output_31_cast_fp16)[name = tensor<string, []>("attn_output_33_cast_fp16")];
            tensor<int32, [4]> attn_output_35_perm_0 = const()[name = tensor<string, []>("attn_output_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_632 = const()[name = tensor<string, []>("op_632"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_35_cast_fp16 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast_fp16)[name = tensor<string, []>("transpose_104")];
            tensor<fp16, [1, 77, 1280]> input_89_cast_fp16 = reshape(shape = var_632, x = attn_output_35_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(204169088))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205397952))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205398144)))];
            tensor<fp16, [1, 77, 1280]> linear_33_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_89_cast_fp16)[name = tensor<string, []>("linear_33_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_91_cast_fp16 = add(x = input_83_cast_fp16, y = linear_33_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<int32, [1]> input_93_axes_0 = const()[name = tensor<string, []>("input_93_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205400768)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205403392)))];
            tensor<fp16, [1, 77, 1280]> input_93_cast_fp16 = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205406016))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210321280))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210321472)))];
            tensor<fp16, [1, 77, 5120]> linear_34_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_93_cast_fp16)[name = tensor<string, []>("linear_34_cast_fp16")];
            tensor<string, []> input_97_mode_0 = const()[name = tensor<string, []>("input_97_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_97_cast_fp16 = gelu(mode = input_97_mode_0, x = linear_34_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210331776))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215247040))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215247232)))];
            tensor<fp16, [1, 77, 1280]> linear_35_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized, x = input_97_cast_fp16)[name = tensor<string, []>("linear_35_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_99_cast_fp16 = add(x = input_91_cast_fp16, y = linear_35_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<int32, [1]> hidden_states_37_axes_0 = const()[name = tensor<string, []>("hidden_states_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215249856)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215252480)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_37_cast_fp16 = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("hidden_states_37_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215255104))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(216483968))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(216484160)))];
            tensor<fp16, [1, 77, 1280]> linear_36_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_37_cast_fp16)[name = tensor<string, []>("linear_36_cast_fp16")];
            tensor<fp16, []> var_671_to_fp16 = const()[name = tensor<string, []>("op_671_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_41_cast_fp16 = mul(x = linear_36_cast_fp16, y = var_671_to_fp16)[name = tensor<string, []>("tensor_41_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(216486784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(217715648))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(217715840)))];
            tensor<fp16, [1, 77, 1280]> linear_37_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_37_cast_fp16)[name = tensor<string, []>("linear_37_cast_fp16")];
            tensor<int32, [4]> var_676 = const()[name = tensor<string, []>("op_676"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_677_cast_fp16 = reshape(shape = var_676, x = linear_37_cast_fp16)[name = tensor<string, []>("op_677_cast_fp16")];
            tensor<int32, [4]> var_678_perm_0 = const()[name = tensor<string, []>("op_678_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(217718464))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218947328))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218947520)))];
            tensor<fp16, [1, 77, 1280]> linear_38_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_37_cast_fp16)[name = tensor<string, []>("linear_38_cast_fp16")];
            tensor<int32, [4]> var_683 = const()[name = tensor<string, []>("op_683"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_684_cast_fp16 = reshape(shape = var_683, x = linear_38_cast_fp16)[name = tensor<string, []>("op_684_cast_fp16")];
            tensor<int32, [4]> var_685_perm_0 = const()[name = tensor<string, []>("op_685_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_692 = const()[name = tensor<string, []>("op_692"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_693_cast_fp16 = reshape(shape = var_692, x = tensor_41_cast_fp16)[name = tensor<string, []>("op_693_cast_fp16")];
            tensor<int32, [4]> var_694_perm_0 = const()[name = tensor<string, []>("op_694_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_696 = const()[name = tensor<string, []>("op_696"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_694_cast_fp16 = transpose(perm = var_694_perm_0, x = var_693_cast_fp16)[name = tensor<string, []>("transpose_103")];
            tensor<fp16, [20, 77, 64]> query_states_13_cast_fp16 = reshape(shape = var_696, x = var_694_cast_fp16)[name = tensor<string, []>("query_states_13_cast_fp16")];
            tensor<int32, [3]> var_698 = const()[name = tensor<string, []>("op_698"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_678_cast_fp16 = transpose(perm = var_678_perm_0, x = var_677_cast_fp16)[name = tensor<string, []>("transpose_102")];
            tensor<fp16, [20, 77, 64]> key_states_27_cast_fp16 = reshape(shape = var_698, x = var_678_cast_fp16)[name = tensor<string, []>("key_states_27_cast_fp16")];
            tensor<int32, [3]> var_700 = const()[name = tensor<string, []>("op_700"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_685_cast_fp16 = transpose(perm = var_685_perm_0, x = var_684_cast_fp16)[name = tensor<string, []>("transpose_101")];
            tensor<fp16, [20, 77, 64]> value_states_27_cast_fp16 = reshape(shape = var_700, x = var_685_cast_fp16)[name = tensor<string, []>("value_states_27_cast_fp16")];
            tensor<bool, []> attn_weights_37_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_37_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_37_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_37_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_37_cast_fp16 = matmul(transpose_x = attn_weights_37_transpose_x_1, transpose_y = attn_weights_37_transpose_y_1, x = query_states_13_cast_fp16, y = key_states_27_cast_fp16)[name = tensor<string, []>("attn_weights_37_cast_fp16")];
            tensor<int32, [4]> var_705 = const()[name = tensor<string, []>("op_705"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_706_cast_fp16 = reshape(shape = var_705, x = attn_weights_37_cast_fp16)[name = tensor<string, []>("op_706_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_39_cast_fp16 = add(x = var_706_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_39_cast_fp16")];
            tensor<int32, [3]> var_711 = const()[name = tensor<string, []>("op_711"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_101_cast_fp16 = reshape(shape = var_711, x = attn_weights_39_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_103_cast_fp16 = softmax(axis = var_5, x = input_101_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
            tensor<bool, []> attn_output_37_transpose_x_0 = const()[name = tensor<string, []>("attn_output_37_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_37_transpose_y_0 = const()[name = tensor<string, []>("attn_output_37_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_37_cast_fp16 = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast_fp16, y = value_states_27_cast_fp16)[name = tensor<string, []>("attn_output_37_cast_fp16")];
            tensor<int32, [4]> var_716 = const()[name = tensor<string, []>("op_716"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_39_cast_fp16 = reshape(shape = var_716, x = attn_output_37_cast_fp16)[name = tensor<string, []>("attn_output_39_cast_fp16")];
            tensor<int32, [4]> attn_output_41_perm_0 = const()[name = tensor<string, []>("attn_output_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_719 = const()[name = tensor<string, []>("op_719"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_41_cast_fp16 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast_fp16)[name = tensor<string, []>("transpose_100")];
            tensor<fp16, [1, 77, 1280]> input_105_cast_fp16 = reshape(shape = var_719, x = attn_output_41_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218950144))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220179008))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220179200)))];
            tensor<fp16, [1, 77, 1280]> linear_39_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_105_cast_fp16)[name = tensor<string, []>("linear_39_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_107_cast_fp16 = add(x = input_99_cast_fp16, y = linear_39_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
            tensor<int32, [1]> input_109_axes_0 = const()[name = tensor<string, []>("input_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220181824)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220184448)))];
            tensor<fp16, [1, 77, 1280]> input_109_cast_fp16 = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220187072))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(225102336))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(225102528)))];
            tensor<fp16, [1, 77, 5120]> linear_40_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_109_cast_fp16)[name = tensor<string, []>("linear_40_cast_fp16")];
            tensor<string, []> input_113_mode_0 = const()[name = tensor<string, []>("input_113_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_113_cast_fp16 = gelu(mode = input_113_mode_0, x = linear_40_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(225112832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230028096))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230028288)))];
            tensor<fp16, [1, 77, 1280]> linear_41_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized, x = input_113_cast_fp16)[name = tensor<string, []>("linear_41_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_115_cast_fp16 = add(x = input_107_cast_fp16, y = linear_41_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
            tensor<int32, [1]> hidden_states_43_axes_0 = const()[name = tensor<string, []>("hidden_states_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230030912)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230033536)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_43_cast_fp16 = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast_fp16)[name = tensor<string, []>("hidden_states_43_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230036160))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231265024))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231265216)))];
            tensor<fp16, [1, 77, 1280]> linear_42_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_43_cast_fp16)[name = tensor<string, []>("linear_42_cast_fp16")];
            tensor<fp16, []> var_758_to_fp16 = const()[name = tensor<string, []>("op_758_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_47_cast_fp16 = mul(x = linear_42_cast_fp16, y = var_758_to_fp16)[name = tensor<string, []>("tensor_47_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231267840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(232496704))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(232496896)))];
            tensor<fp16, [1, 77, 1280]> linear_43_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_43_cast_fp16)[name = tensor<string, []>("linear_43_cast_fp16")];
            tensor<int32, [4]> var_763 = const()[name = tensor<string, []>("op_763"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_764_cast_fp16 = reshape(shape = var_763, x = linear_43_cast_fp16)[name = tensor<string, []>("op_764_cast_fp16")];
            tensor<int32, [4]> var_765_perm_0 = const()[name = tensor<string, []>("op_765_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(232499520))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233728384))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233728576)))];
            tensor<fp16, [1, 77, 1280]> linear_44_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_43_cast_fp16)[name = tensor<string, []>("linear_44_cast_fp16")];
            tensor<int32, [4]> var_770 = const()[name = tensor<string, []>("op_770"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_771_cast_fp16 = reshape(shape = var_770, x = linear_44_cast_fp16)[name = tensor<string, []>("op_771_cast_fp16")];
            tensor<int32, [4]> var_772_perm_0 = const()[name = tensor<string, []>("op_772_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_779 = const()[name = tensor<string, []>("op_779"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_780_cast_fp16 = reshape(shape = var_779, x = tensor_47_cast_fp16)[name = tensor<string, []>("op_780_cast_fp16")];
            tensor<int32, [4]> var_781_perm_0 = const()[name = tensor<string, []>("op_781_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_783 = const()[name = tensor<string, []>("op_783"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_781_cast_fp16 = transpose(perm = var_781_perm_0, x = var_780_cast_fp16)[name = tensor<string, []>("transpose_99")];
            tensor<fp16, [20, 77, 64]> query_states_15_cast_fp16 = reshape(shape = var_783, x = var_781_cast_fp16)[name = tensor<string, []>("query_states_15_cast_fp16")];
            tensor<int32, [3]> var_785 = const()[name = tensor<string, []>("op_785"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_765_cast_fp16 = transpose(perm = var_765_perm_0, x = var_764_cast_fp16)[name = tensor<string, []>("transpose_98")];
            tensor<fp16, [20, 77, 64]> key_states_31_cast_fp16 = reshape(shape = var_785, x = var_765_cast_fp16)[name = tensor<string, []>("key_states_31_cast_fp16")];
            tensor<int32, [3]> var_787 = const()[name = tensor<string, []>("op_787"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_772_cast_fp16 = transpose(perm = var_772_perm_0, x = var_771_cast_fp16)[name = tensor<string, []>("transpose_97")];
            tensor<fp16, [20, 77, 64]> value_states_31_cast_fp16 = reshape(shape = var_787, x = var_772_cast_fp16)[name = tensor<string, []>("value_states_31_cast_fp16")];
            tensor<bool, []> attn_weights_43_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_43_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_43_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_43_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_43_cast_fp16 = matmul(transpose_x = attn_weights_43_transpose_x_1, transpose_y = attn_weights_43_transpose_y_1, x = query_states_15_cast_fp16, y = key_states_31_cast_fp16)[name = tensor<string, []>("attn_weights_43_cast_fp16")];
            tensor<int32, [4]> var_792 = const()[name = tensor<string, []>("op_792"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_793_cast_fp16 = reshape(shape = var_792, x = attn_weights_43_cast_fp16)[name = tensor<string, []>("op_793_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_45_cast_fp16 = add(x = var_793_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_45_cast_fp16")];
            tensor<int32, [3]> var_798 = const()[name = tensor<string, []>("op_798"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_117_cast_fp16 = reshape(shape = var_798, x = attn_weights_45_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_119_cast_fp16 = softmax(axis = var_5, x = input_117_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")];
            tensor<bool, []> attn_output_43_transpose_x_0 = const()[name = tensor<string, []>("attn_output_43_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_43_transpose_y_0 = const()[name = tensor<string, []>("attn_output_43_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_43_cast_fp16 = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast_fp16, y = value_states_31_cast_fp16)[name = tensor<string, []>("attn_output_43_cast_fp16")];
            tensor<int32, [4]> var_803 = const()[name = tensor<string, []>("op_803"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_45_cast_fp16 = reshape(shape = var_803, x = attn_output_43_cast_fp16)[name = tensor<string, []>("attn_output_45_cast_fp16")];
            tensor<int32, [4]> attn_output_47_perm_0 = const()[name = tensor<string, []>("attn_output_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_806 = const()[name = tensor<string, []>("op_806"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_47_cast_fp16 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast_fp16)[name = tensor<string, []>("transpose_96")];
            tensor<fp16, [1, 77, 1280]> input_121_cast_fp16 = reshape(shape = var_806, x = attn_output_47_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(233731200))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234960064))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234960256)))];
            tensor<fp16, [1, 77, 1280]> linear_45_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_121_cast_fp16)[name = tensor<string, []>("linear_45_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_123_cast_fp16 = add(x = input_115_cast_fp16, y = linear_45_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
            tensor<int32, [1]> input_125_axes_0 = const()[name = tensor<string, []>("input_125_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234962880)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234965504)))];
            tensor<fp16, [1, 77, 1280]> input_125_cast_fp16 = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234968128))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239883392))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239883584)))];
            tensor<fp16, [1, 77, 5120]> linear_46_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_125_cast_fp16)[name = tensor<string, []>("linear_46_cast_fp16")];
            tensor<string, []> input_129_mode_0 = const()[name = tensor<string, []>("input_129_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_129_cast_fp16 = gelu(mode = input_129_mode_0, x = linear_46_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239893888))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244809152))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244809344)))];
            tensor<fp16, [1, 77, 1280]> linear_47_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized, x = input_129_cast_fp16)[name = tensor<string, []>("linear_47_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_131_cast_fp16 = add(x = input_123_cast_fp16, y = linear_47_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")];
            tensor<int32, [1]> hidden_states_49_axes_0 = const()[name = tensor<string, []>("hidden_states_49_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244811968)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244814592)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_49_cast_fp16 = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("hidden_states_49_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244817216))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(246046080))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(246046272)))];
            tensor<fp16, [1, 77, 1280]> linear_48_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_49_cast_fp16)[name = tensor<string, []>("linear_48_cast_fp16")];
            tensor<fp16, []> var_845_to_fp16 = const()[name = tensor<string, []>("op_845_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_53_cast_fp16 = mul(x = linear_48_cast_fp16, y = var_845_to_fp16)[name = tensor<string, []>("tensor_53_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(246048896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(247277760))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(247277952)))];
            tensor<fp16, [1, 77, 1280]> linear_49_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_49_cast_fp16)[name = tensor<string, []>("linear_49_cast_fp16")];
            tensor<int32, [4]> var_850 = const()[name = tensor<string, []>("op_850"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_851_cast_fp16 = reshape(shape = var_850, x = linear_49_cast_fp16)[name = tensor<string, []>("op_851_cast_fp16")];
            tensor<int32, [4]> var_852_perm_0 = const()[name = tensor<string, []>("op_852_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(247280576))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248509440))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248509632)))];
            tensor<fp16, [1, 77, 1280]> linear_50_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_49_cast_fp16)[name = tensor<string, []>("linear_50_cast_fp16")];
            tensor<int32, [4]> var_857 = const()[name = tensor<string, []>("op_857"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_858_cast_fp16 = reshape(shape = var_857, x = linear_50_cast_fp16)[name = tensor<string, []>("op_858_cast_fp16")];
            tensor<int32, [4]> var_859_perm_0 = const()[name = tensor<string, []>("op_859_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_866 = const()[name = tensor<string, []>("op_866"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_867_cast_fp16 = reshape(shape = var_866, x = tensor_53_cast_fp16)[name = tensor<string, []>("op_867_cast_fp16")];
            tensor<int32, [4]> var_868_perm_0 = const()[name = tensor<string, []>("op_868_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_870 = const()[name = tensor<string, []>("op_870"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_868_cast_fp16 = transpose(perm = var_868_perm_0, x = var_867_cast_fp16)[name = tensor<string, []>("transpose_95")];
            tensor<fp16, [20, 77, 64]> query_states_17_cast_fp16 = reshape(shape = var_870, x = var_868_cast_fp16)[name = tensor<string, []>("query_states_17_cast_fp16")];
            tensor<int32, [3]> var_872 = const()[name = tensor<string, []>("op_872"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_852_cast_fp16 = transpose(perm = var_852_perm_0, x = var_851_cast_fp16)[name = tensor<string, []>("transpose_94")];
            tensor<fp16, [20, 77, 64]> key_states_35_cast_fp16 = reshape(shape = var_872, x = var_852_cast_fp16)[name = tensor<string, []>("key_states_35_cast_fp16")];
            tensor<int32, [3]> var_874 = const()[name = tensor<string, []>("op_874"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_859_cast_fp16 = transpose(perm = var_859_perm_0, x = var_858_cast_fp16)[name = tensor<string, []>("transpose_93")];
            tensor<fp16, [20, 77, 64]> value_states_35_cast_fp16 = reshape(shape = var_874, x = var_859_cast_fp16)[name = tensor<string, []>("value_states_35_cast_fp16")];
            tensor<bool, []> attn_weights_49_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_49_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_49_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_49_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_49_cast_fp16 = matmul(transpose_x = attn_weights_49_transpose_x_1, transpose_y = attn_weights_49_transpose_y_1, x = query_states_17_cast_fp16, y = key_states_35_cast_fp16)[name = tensor<string, []>("attn_weights_49_cast_fp16")];
            tensor<int32, [4]> var_879 = const()[name = tensor<string, []>("op_879"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_880_cast_fp16 = reshape(shape = var_879, x = attn_weights_49_cast_fp16)[name = tensor<string, []>("op_880_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_51_cast_fp16 = add(x = var_880_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_51_cast_fp16")];
            tensor<int32, [3]> var_885 = const()[name = tensor<string, []>("op_885"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_133_cast_fp16 = reshape(shape = var_885, x = attn_weights_51_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_135_cast_fp16 = softmax(axis = var_5, x = input_133_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")];
            tensor<bool, []> attn_output_49_transpose_x_0 = const()[name = tensor<string, []>("attn_output_49_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_49_transpose_y_0 = const()[name = tensor<string, []>("attn_output_49_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_49_cast_fp16 = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast_fp16, y = value_states_35_cast_fp16)[name = tensor<string, []>("attn_output_49_cast_fp16")];
            tensor<int32, [4]> var_890 = const()[name = tensor<string, []>("op_890"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_51_cast_fp16 = reshape(shape = var_890, x = attn_output_49_cast_fp16)[name = tensor<string, []>("attn_output_51_cast_fp16")];
            tensor<int32, [4]> attn_output_53_perm_0 = const()[name = tensor<string, []>("attn_output_53_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_893 = const()[name = tensor<string, []>("op_893"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_53_cast_fp16 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast_fp16)[name = tensor<string, []>("transpose_92")];
            tensor<fp16, [1, 77, 1280]> input_137_cast_fp16 = reshape(shape = var_893, x = attn_output_53_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248512256))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249741120))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249741312)))];
            tensor<fp16, [1, 77, 1280]> linear_51_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_137_cast_fp16)[name = tensor<string, []>("linear_51_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_139_cast_fp16 = add(x = input_131_cast_fp16, y = linear_51_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
            tensor<int32, [1]> input_141_axes_0 = const()[name = tensor<string, []>("input_141_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249743936)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249746560)))];
            tensor<fp16, [1, 77, 1280]> input_141_cast_fp16 = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249749184))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254664448))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254664640)))];
            tensor<fp16, [1, 77, 5120]> linear_52_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast_fp16)[name = tensor<string, []>("linear_52_cast_fp16")];
            tensor<string, []> input_145_mode_0 = const()[name = tensor<string, []>("input_145_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_145_cast_fp16 = gelu(mode = input_145_mode_0, x = linear_52_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254674944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259590208))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259590400)))];
            tensor<fp16, [1, 77, 1280]> linear_53_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized, x = input_145_cast_fp16)[name = tensor<string, []>("linear_53_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_147_cast_fp16 = add(x = input_139_cast_fp16, y = linear_53_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
            tensor<int32, [1]> hidden_states_55_axes_0 = const()[name = tensor<string, []>("hidden_states_55_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259593024)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259595648)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_55_cast_fp16 = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("hidden_states_55_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259598272))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(260827136))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(260827328)))];
            tensor<fp16, [1, 77, 1280]> linear_54_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_55_cast_fp16)[name = tensor<string, []>("linear_54_cast_fp16")];
            tensor<fp16, []> var_932_to_fp16 = const()[name = tensor<string, []>("op_932_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_59_cast_fp16 = mul(x = linear_54_cast_fp16, y = var_932_to_fp16)[name = tensor<string, []>("tensor_59_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(260829952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(262058816))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(262059008)))];
            tensor<fp16, [1, 77, 1280]> linear_55_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_55_cast_fp16)[name = tensor<string, []>("linear_55_cast_fp16")];
            tensor<int32, [4]> var_937 = const()[name = tensor<string, []>("op_937"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_938_cast_fp16 = reshape(shape = var_937, x = linear_55_cast_fp16)[name = tensor<string, []>("op_938_cast_fp16")];
            tensor<int32, [4]> var_939_perm_0 = const()[name = tensor<string, []>("op_939_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(262061632))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(263290496))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(263290688)))];
            tensor<fp16, [1, 77, 1280]> linear_56_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_55_cast_fp16)[name = tensor<string, []>("linear_56_cast_fp16")];
            tensor<int32, [4]> var_944 = const()[name = tensor<string, []>("op_944"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_945_cast_fp16 = reshape(shape = var_944, x = linear_56_cast_fp16)[name = tensor<string, []>("op_945_cast_fp16")];
            tensor<int32, [4]> var_946_perm_0 = const()[name = tensor<string, []>("op_946_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_953 = const()[name = tensor<string, []>("op_953"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_954_cast_fp16 = reshape(shape = var_953, x = tensor_59_cast_fp16)[name = tensor<string, []>("op_954_cast_fp16")];
            tensor<int32, [4]> var_955_perm_0 = const()[name = tensor<string, []>("op_955_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_957 = const()[name = tensor<string, []>("op_957"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_955_cast_fp16 = transpose(perm = var_955_perm_0, x = var_954_cast_fp16)[name = tensor<string, []>("transpose_91")];
            tensor<fp16, [20, 77, 64]> query_states_19_cast_fp16 = reshape(shape = var_957, x = var_955_cast_fp16)[name = tensor<string, []>("query_states_19_cast_fp16")];
            tensor<int32, [3]> var_959 = const()[name = tensor<string, []>("op_959"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_939_cast_fp16 = transpose(perm = var_939_perm_0, x = var_938_cast_fp16)[name = tensor<string, []>("transpose_90")];
            tensor<fp16, [20, 77, 64]> key_states_39_cast_fp16 = reshape(shape = var_959, x = var_939_cast_fp16)[name = tensor<string, []>("key_states_39_cast_fp16")];
            tensor<int32, [3]> var_961 = const()[name = tensor<string, []>("op_961"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_946_cast_fp16 = transpose(perm = var_946_perm_0, x = var_945_cast_fp16)[name = tensor<string, []>("transpose_89")];
            tensor<fp16, [20, 77, 64]> value_states_39_cast_fp16 = reshape(shape = var_961, x = var_946_cast_fp16)[name = tensor<string, []>("value_states_39_cast_fp16")];
            tensor<bool, []> attn_weights_55_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_55_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_55_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_55_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_55_cast_fp16 = matmul(transpose_x = attn_weights_55_transpose_x_1, transpose_y = attn_weights_55_transpose_y_1, x = query_states_19_cast_fp16, y = key_states_39_cast_fp16)[name = tensor<string, []>("attn_weights_55_cast_fp16")];
            tensor<int32, [4]> var_966 = const()[name = tensor<string, []>("op_966"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_967_cast_fp16 = reshape(shape = var_966, x = attn_weights_55_cast_fp16)[name = tensor<string, []>("op_967_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_57_cast_fp16 = add(x = var_967_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_57_cast_fp16")];
            tensor<int32, [3]> var_972 = const()[name = tensor<string, []>("op_972"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_149_cast_fp16 = reshape(shape = var_972, x = attn_weights_57_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_151_cast_fp16 = softmax(axis = var_5, x = input_149_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
            tensor<bool, []> attn_output_55_transpose_x_0 = const()[name = tensor<string, []>("attn_output_55_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_55_transpose_y_0 = const()[name = tensor<string, []>("attn_output_55_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_55_cast_fp16 = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast_fp16, y = value_states_39_cast_fp16)[name = tensor<string, []>("attn_output_55_cast_fp16")];
            tensor<int32, [4]> var_977 = const()[name = tensor<string, []>("op_977"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_57_cast_fp16 = reshape(shape = var_977, x = attn_output_55_cast_fp16)[name = tensor<string, []>("attn_output_57_cast_fp16")];
            tensor<int32, [4]> attn_output_59_perm_0 = const()[name = tensor<string, []>("attn_output_59_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_980 = const()[name = tensor<string, []>("op_980"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_59_cast_fp16 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast_fp16)[name = tensor<string, []>("transpose_88")];
            tensor<fp16, [1, 77, 1280]> input_153_cast_fp16 = reshape(shape = var_980, x = attn_output_59_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(263293312))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264522176))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264522368)))];
            tensor<fp16, [1, 77, 1280]> linear_57_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_153_cast_fp16)[name = tensor<string, []>("linear_57_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_155_cast_fp16 = add(x = input_147_cast_fp16, y = linear_57_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<int32, [1]> input_157_axes_0 = const()[name = tensor<string, []>("input_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264524992)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264527616)))];
            tensor<fp16, [1, 77, 1280]> input_157_cast_fp16 = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264530240))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269445504))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269445696)))];
            tensor<fp16, [1, 77, 5120]> linear_58_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_157_cast_fp16)[name = tensor<string, []>("linear_58_cast_fp16")];
            tensor<string, []> input_161_mode_0 = const()[name = tensor<string, []>("input_161_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_161_cast_fp16 = gelu(mode = input_161_mode_0, x = linear_58_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269456000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274371264))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274371456)))];
            tensor<fp16, [1, 77, 1280]> linear_59_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized, x = input_161_cast_fp16)[name = tensor<string, []>("linear_59_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_163_cast_fp16 = add(x = input_155_cast_fp16, y = linear_59_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<int32, [1]> hidden_states_61_axes_0 = const()[name = tensor<string, []>("hidden_states_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274374080)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274376704)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_61_cast_fp16 = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast_fp16)[name = tensor<string, []>("hidden_states_61_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274379328))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(275608192))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(275608384)))];
            tensor<fp16, [1, 77, 1280]> linear_60_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_61_cast_fp16)[name = tensor<string, []>("linear_60_cast_fp16")];
            tensor<fp16, []> var_1019_to_fp16 = const()[name = tensor<string, []>("op_1019_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_65_cast_fp16 = mul(x = linear_60_cast_fp16, y = var_1019_to_fp16)[name = tensor<string, []>("tensor_65_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(275611008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(276839872))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(276840064)))];
            tensor<fp16, [1, 77, 1280]> linear_61_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_61_cast_fp16)[name = tensor<string, []>("linear_61_cast_fp16")];
            tensor<int32, [4]> var_1024 = const()[name = tensor<string, []>("op_1024"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1025_cast_fp16 = reshape(shape = var_1024, x = linear_61_cast_fp16)[name = tensor<string, []>("op_1025_cast_fp16")];
            tensor<int32, [4]> var_1026_perm_0 = const()[name = tensor<string, []>("op_1026_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(276842688))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(278071552))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(278071744)))];
            tensor<fp16, [1, 77, 1280]> linear_62_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_61_cast_fp16)[name = tensor<string, []>("linear_62_cast_fp16")];
            tensor<int32, [4]> var_1031 = const()[name = tensor<string, []>("op_1031"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1032_cast_fp16 = reshape(shape = var_1031, x = linear_62_cast_fp16)[name = tensor<string, []>("op_1032_cast_fp16")];
            tensor<int32, [4]> var_1033_perm_0 = const()[name = tensor<string, []>("op_1033_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1040 = const()[name = tensor<string, []>("op_1040"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1041_cast_fp16 = reshape(shape = var_1040, x = tensor_65_cast_fp16)[name = tensor<string, []>("op_1041_cast_fp16")];
            tensor<int32, [4]> var_1042_perm_0 = const()[name = tensor<string, []>("op_1042_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1044 = const()[name = tensor<string, []>("op_1044"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1042_cast_fp16 = transpose(perm = var_1042_perm_0, x = var_1041_cast_fp16)[name = tensor<string, []>("transpose_87")];
            tensor<fp16, [20, 77, 64]> query_states_21_cast_fp16 = reshape(shape = var_1044, x = var_1042_cast_fp16)[name = tensor<string, []>("query_states_21_cast_fp16")];
            tensor<int32, [3]> var_1046 = const()[name = tensor<string, []>("op_1046"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1026_cast_fp16 = transpose(perm = var_1026_perm_0, x = var_1025_cast_fp16)[name = tensor<string, []>("transpose_86")];
            tensor<fp16, [20, 77, 64]> key_states_43_cast_fp16 = reshape(shape = var_1046, x = var_1026_cast_fp16)[name = tensor<string, []>("key_states_43_cast_fp16")];
            tensor<int32, [3]> var_1048 = const()[name = tensor<string, []>("op_1048"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1033_cast_fp16 = transpose(perm = var_1033_perm_0, x = var_1032_cast_fp16)[name = tensor<string, []>("transpose_85")];
            tensor<fp16, [20, 77, 64]> value_states_43_cast_fp16 = reshape(shape = var_1048, x = var_1033_cast_fp16)[name = tensor<string, []>("value_states_43_cast_fp16")];
            tensor<bool, []> attn_weights_61_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_61_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_61_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_61_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_61_cast_fp16 = matmul(transpose_x = attn_weights_61_transpose_x_1, transpose_y = attn_weights_61_transpose_y_1, x = query_states_21_cast_fp16, y = key_states_43_cast_fp16)[name = tensor<string, []>("attn_weights_61_cast_fp16")];
            tensor<int32, [4]> var_1053 = const()[name = tensor<string, []>("op_1053"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1054_cast_fp16 = reshape(shape = var_1053, x = attn_weights_61_cast_fp16)[name = tensor<string, []>("op_1054_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_63_cast_fp16 = add(x = var_1054_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_63_cast_fp16")];
            tensor<int32, [3]> var_1059 = const()[name = tensor<string, []>("op_1059"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_165_cast_fp16 = reshape(shape = var_1059, x = attn_weights_63_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_167_cast_fp16 = softmax(axis = var_5, x = input_165_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")];
            tensor<bool, []> attn_output_61_transpose_x_0 = const()[name = tensor<string, []>("attn_output_61_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_61_transpose_y_0 = const()[name = tensor<string, []>("attn_output_61_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_61_cast_fp16 = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast_fp16, y = value_states_43_cast_fp16)[name = tensor<string, []>("attn_output_61_cast_fp16")];
            tensor<int32, [4]> var_1064 = const()[name = tensor<string, []>("op_1064"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_63_cast_fp16 = reshape(shape = var_1064, x = attn_output_61_cast_fp16)[name = tensor<string, []>("attn_output_63_cast_fp16")];
            tensor<int32, [4]> attn_output_65_perm_0 = const()[name = tensor<string, []>("attn_output_65_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1067 = const()[name = tensor<string, []>("op_1067"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_65_cast_fp16 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast_fp16)[name = tensor<string, []>("transpose_84")];
            tensor<fp16, [1, 77, 1280]> input_169_cast_fp16 = reshape(shape = var_1067, x = attn_output_65_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(278074368))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279303232))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279303424)))];
            tensor<fp16, [1, 77, 1280]> linear_63_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_169_cast_fp16)[name = tensor<string, []>("linear_63_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_171_cast_fp16 = add(x = input_163_cast_fp16, y = linear_63_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
            tensor<int32, [1]> input_173_axes_0 = const()[name = tensor<string, []>("input_173_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279306048)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279308672)))];
            tensor<fp16, [1, 77, 1280]> input_173_cast_fp16 = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279311296))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284226560))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284226752)))];
            tensor<fp16, [1, 77, 5120]> linear_64_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_173_cast_fp16)[name = tensor<string, []>("linear_64_cast_fp16")];
            tensor<string, []> input_177_mode_0 = const()[name = tensor<string, []>("input_177_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_177_cast_fp16 = gelu(mode = input_177_mode_0, x = linear_64_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284237056))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(289152320))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(289152512)))];
            tensor<fp16, [1, 77, 1280]> linear_65_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized, x = input_177_cast_fp16)[name = tensor<string, []>("linear_65_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_179_cast_fp16 = add(x = input_171_cast_fp16, y = linear_65_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")];
            tensor<int32, [1]> hidden_states_67_axes_0 = const()[name = tensor<string, []>("hidden_states_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(289155136)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(289157760)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_67_cast_fp16 = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast_fp16)[name = tensor<string, []>("hidden_states_67_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(289160384))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290389248))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290389440)))];
            tensor<fp16, [1, 77, 1280]> linear_66_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_67_cast_fp16)[name = tensor<string, []>("linear_66_cast_fp16")];
            tensor<fp16, []> var_1106_to_fp16 = const()[name = tensor<string, []>("op_1106_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_71_cast_fp16 = mul(x = linear_66_cast_fp16, y = var_1106_to_fp16)[name = tensor<string, []>("tensor_71_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290392064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(291620928))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(291621120)))];
            tensor<fp16, [1, 77, 1280]> linear_67_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_67_cast_fp16)[name = tensor<string, []>("linear_67_cast_fp16")];
            tensor<int32, [4]> var_1111 = const()[name = tensor<string, []>("op_1111"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1112_cast_fp16 = reshape(shape = var_1111, x = linear_67_cast_fp16)[name = tensor<string, []>("op_1112_cast_fp16")];
            tensor<int32, [4]> var_1113_perm_0 = const()[name = tensor<string, []>("op_1113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(291623744))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(292852608))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(292852800)))];
            tensor<fp16, [1, 77, 1280]> linear_68_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_67_cast_fp16)[name = tensor<string, []>("linear_68_cast_fp16")];
            tensor<int32, [4]> var_1118 = const()[name = tensor<string, []>("op_1118"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1119_cast_fp16 = reshape(shape = var_1118, x = linear_68_cast_fp16)[name = tensor<string, []>("op_1119_cast_fp16")];
            tensor<int32, [4]> var_1120_perm_0 = const()[name = tensor<string, []>("op_1120_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1127 = const()[name = tensor<string, []>("op_1127"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1128_cast_fp16 = reshape(shape = var_1127, x = tensor_71_cast_fp16)[name = tensor<string, []>("op_1128_cast_fp16")];
            tensor<int32, [4]> var_1129_perm_0 = const()[name = tensor<string, []>("op_1129_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1131 = const()[name = tensor<string, []>("op_1131"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1129_cast_fp16 = transpose(perm = var_1129_perm_0, x = var_1128_cast_fp16)[name = tensor<string, []>("transpose_83")];
            tensor<fp16, [20, 77, 64]> query_states_23_cast_fp16 = reshape(shape = var_1131, x = var_1129_cast_fp16)[name = tensor<string, []>("query_states_23_cast_fp16")];
            tensor<int32, [3]> var_1133 = const()[name = tensor<string, []>("op_1133"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1113_cast_fp16 = transpose(perm = var_1113_perm_0, x = var_1112_cast_fp16)[name = tensor<string, []>("transpose_82")];
            tensor<fp16, [20, 77, 64]> key_states_47_cast_fp16 = reshape(shape = var_1133, x = var_1113_cast_fp16)[name = tensor<string, []>("key_states_47_cast_fp16")];
            tensor<int32, [3]> var_1135 = const()[name = tensor<string, []>("op_1135"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1120_cast_fp16 = transpose(perm = var_1120_perm_0, x = var_1119_cast_fp16)[name = tensor<string, []>("transpose_81")];
            tensor<fp16, [20, 77, 64]> value_states_47_cast_fp16 = reshape(shape = var_1135, x = var_1120_cast_fp16)[name = tensor<string, []>("value_states_47_cast_fp16")];
            tensor<bool, []> attn_weights_67_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_67_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_67_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_67_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_67_cast_fp16 = matmul(transpose_x = attn_weights_67_transpose_x_1, transpose_y = attn_weights_67_transpose_y_1, x = query_states_23_cast_fp16, y = key_states_47_cast_fp16)[name = tensor<string, []>("attn_weights_67_cast_fp16")];
            tensor<int32, [4]> var_1140 = const()[name = tensor<string, []>("op_1140"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1141_cast_fp16 = reshape(shape = var_1140, x = attn_weights_67_cast_fp16)[name = tensor<string, []>("op_1141_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_69_cast_fp16 = add(x = var_1141_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_69_cast_fp16")];
            tensor<int32, [3]> var_1146 = const()[name = tensor<string, []>("op_1146"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_181_cast_fp16 = reshape(shape = var_1146, x = attn_weights_69_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_183_cast_fp16 = softmax(axis = var_5, x = input_181_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")];
            tensor<bool, []> attn_output_67_transpose_x_0 = const()[name = tensor<string, []>("attn_output_67_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_67_transpose_y_0 = const()[name = tensor<string, []>("attn_output_67_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_67_cast_fp16 = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast_fp16, y = value_states_47_cast_fp16)[name = tensor<string, []>("attn_output_67_cast_fp16")];
            tensor<int32, [4]> var_1151 = const()[name = tensor<string, []>("op_1151"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_69_cast_fp16 = reshape(shape = var_1151, x = attn_output_67_cast_fp16)[name = tensor<string, []>("attn_output_69_cast_fp16")];
            tensor<int32, [4]> attn_output_71_perm_0 = const()[name = tensor<string, []>("attn_output_71_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1154 = const()[name = tensor<string, []>("op_1154"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_71_cast_fp16 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast_fp16)[name = tensor<string, []>("transpose_80")];
            tensor<fp16, [1, 77, 1280]> input_185_cast_fp16 = reshape(shape = var_1154, x = attn_output_71_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(292855424))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294084288))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294084480)))];
            tensor<fp16, [1, 77, 1280]> linear_69_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_185_cast_fp16)[name = tensor<string, []>("linear_69_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_187_cast_fp16 = add(x = input_179_cast_fp16, y = linear_69_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
            tensor<int32, [1]> input_189_axes_0 = const()[name = tensor<string, []>("input_189_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294087104)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294089728)))];
            tensor<fp16, [1, 77, 1280]> input_189_cast_fp16 = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294092352))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(299007616))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(299007808)))];
            tensor<fp16, [1, 77, 5120]> linear_70_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_189_cast_fp16)[name = tensor<string, []>("linear_70_cast_fp16")];
            tensor<string, []> input_193_mode_0 = const()[name = tensor<string, []>("input_193_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_193_cast_fp16 = gelu(mode = input_193_mode_0, x = linear_70_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(299018112))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303933376))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303933568)))];
            tensor<fp16, [1, 77, 1280]> linear_71_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_193_cast_fp16)[name = tensor<string, []>("linear_71_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_195_cast_fp16 = add(x = input_187_cast_fp16, y = linear_71_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<int32, [1]> hidden_states_73_axes_0 = const()[name = tensor<string, []>("hidden_states_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303936192)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303938816)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_73_cast_fp16 = layer_norm(axes = hidden_states_73_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("hidden_states_73_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303941440))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(305170304))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(305170496)))];
            tensor<fp16, [1, 77, 1280]> linear_72_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_73_cast_fp16)[name = tensor<string, []>("linear_72_cast_fp16")];
            tensor<fp16, []> var_1193_to_fp16 = const()[name = tensor<string, []>("op_1193_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_77_cast_fp16 = mul(x = linear_72_cast_fp16, y = var_1193_to_fp16)[name = tensor<string, []>("tensor_77_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(305173120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(306401984))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(306402176)))];
            tensor<fp16, [1, 77, 1280]> linear_73_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_73_cast_fp16)[name = tensor<string, []>("linear_73_cast_fp16")];
            tensor<int32, [4]> var_1198 = const()[name = tensor<string, []>("op_1198"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1199_cast_fp16 = reshape(shape = var_1198, x = linear_73_cast_fp16)[name = tensor<string, []>("op_1199_cast_fp16")];
            tensor<int32, [4]> var_1200_perm_0 = const()[name = tensor<string, []>("op_1200_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(306404800))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(307633664))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(307633856)))];
            tensor<fp16, [1, 77, 1280]> linear_74_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_73_cast_fp16)[name = tensor<string, []>("linear_74_cast_fp16")];
            tensor<int32, [4]> var_1205 = const()[name = tensor<string, []>("op_1205"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1206_cast_fp16 = reshape(shape = var_1205, x = linear_74_cast_fp16)[name = tensor<string, []>("op_1206_cast_fp16")];
            tensor<int32, [4]> var_1207_perm_0 = const()[name = tensor<string, []>("op_1207_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1214 = const()[name = tensor<string, []>("op_1214"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1215_cast_fp16 = reshape(shape = var_1214, x = tensor_77_cast_fp16)[name = tensor<string, []>("op_1215_cast_fp16")];
            tensor<int32, [4]> var_1216_perm_0 = const()[name = tensor<string, []>("op_1216_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1218 = const()[name = tensor<string, []>("op_1218"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1216_cast_fp16 = transpose(perm = var_1216_perm_0, x = var_1215_cast_fp16)[name = tensor<string, []>("transpose_79")];
            tensor<fp16, [20, 77, 64]> query_states_25_cast_fp16 = reshape(shape = var_1218, x = var_1216_cast_fp16)[name = tensor<string, []>("query_states_25_cast_fp16")];
            tensor<int32, [3]> var_1220 = const()[name = tensor<string, []>("op_1220"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1200_cast_fp16 = transpose(perm = var_1200_perm_0, x = var_1199_cast_fp16)[name = tensor<string, []>("transpose_78")];
            tensor<fp16, [20, 77, 64]> key_states_51_cast_fp16 = reshape(shape = var_1220, x = var_1200_cast_fp16)[name = tensor<string, []>("key_states_51_cast_fp16")];
            tensor<int32, [3]> var_1222 = const()[name = tensor<string, []>("op_1222"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1207_cast_fp16 = transpose(perm = var_1207_perm_0, x = var_1206_cast_fp16)[name = tensor<string, []>("transpose_77")];
            tensor<fp16, [20, 77, 64]> value_states_51_cast_fp16 = reshape(shape = var_1222, x = var_1207_cast_fp16)[name = tensor<string, []>("value_states_51_cast_fp16")];
            tensor<bool, []> attn_weights_73_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_73_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_73_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_73_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_73_cast_fp16 = matmul(transpose_x = attn_weights_73_transpose_x_1, transpose_y = attn_weights_73_transpose_y_1, x = query_states_25_cast_fp16, y = key_states_51_cast_fp16)[name = tensor<string, []>("attn_weights_73_cast_fp16")];
            tensor<int32, [4]> var_1227 = const()[name = tensor<string, []>("op_1227"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1228_cast_fp16 = reshape(shape = var_1227, x = attn_weights_73_cast_fp16)[name = tensor<string, []>("op_1228_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_75_cast_fp16 = add(x = var_1228_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_75_cast_fp16")];
            tensor<int32, [3]> var_1233 = const()[name = tensor<string, []>("op_1233"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_197_cast_fp16 = reshape(shape = var_1233, x = attn_weights_75_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_199_cast_fp16 = softmax(axis = var_5, x = input_197_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
            tensor<bool, []> attn_output_73_transpose_x_0 = const()[name = tensor<string, []>("attn_output_73_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_73_transpose_y_0 = const()[name = tensor<string, []>("attn_output_73_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_73_cast_fp16 = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_199_cast_fp16, y = value_states_51_cast_fp16)[name = tensor<string, []>("attn_output_73_cast_fp16")];
            tensor<int32, [4]> var_1238 = const()[name = tensor<string, []>("op_1238"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_75_cast_fp16 = reshape(shape = var_1238, x = attn_output_73_cast_fp16)[name = tensor<string, []>("attn_output_75_cast_fp16")];
            tensor<int32, [4]> attn_output_77_perm_0 = const()[name = tensor<string, []>("attn_output_77_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1241 = const()[name = tensor<string, []>("op_1241"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_77_cast_fp16 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast_fp16)[name = tensor<string, []>("transpose_76")];
            tensor<fp16, [1, 77, 1280]> input_201_cast_fp16 = reshape(shape = var_1241, x = attn_output_77_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(307636480))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308865344))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308865536)))];
            tensor<fp16, [1, 77, 1280]> linear_75_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized, x = input_201_cast_fp16)[name = tensor<string, []>("linear_75_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_203_cast_fp16 = add(x = input_195_cast_fp16, y = linear_75_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<int32, [1]> input_205_axes_0 = const()[name = tensor<string, []>("input_205_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308868160)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308870784)))];
            tensor<fp16, [1, 77, 1280]> input_205_cast_fp16 = layer_norm(axes = input_205_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308873408))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313788672))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313788864)))];
            tensor<fp16, [1, 77, 5120]> linear_76_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized, x = input_205_cast_fp16)[name = tensor<string, []>("linear_76_cast_fp16")];
            tensor<string, []> input_209_mode_0 = const()[name = tensor<string, []>("input_209_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_209_cast_fp16 = gelu(mode = input_209_mode_0, x = linear_76_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313799168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318714432))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318714624)))];
            tensor<fp16, [1, 77, 1280]> linear_77_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized, x = input_209_cast_fp16)[name = tensor<string, []>("linear_77_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_211_cast_fp16 = add(x = input_203_cast_fp16, y = linear_77_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")];
            tensor<int32, [1]> hidden_states_79_axes_0 = const()[name = tensor<string, []>("hidden_states_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318717248)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318719872)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_79_cast_fp16 = layer_norm(axes = hidden_states_79_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("hidden_states_79_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318722496))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319951360))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319951552)))];
            tensor<fp16, [1, 77, 1280]> linear_78_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_79_cast_fp16)[name = tensor<string, []>("linear_78_cast_fp16")];
            tensor<fp16, []> var_1280_to_fp16 = const()[name = tensor<string, []>("op_1280_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_83_cast_fp16 = mul(x = linear_78_cast_fp16, y = var_1280_to_fp16)[name = tensor<string, []>("tensor_83_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319954176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(321183040))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(321183232)))];
            tensor<fp16, [1, 77, 1280]> linear_79_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_79_cast_fp16)[name = tensor<string, []>("linear_79_cast_fp16")];
            tensor<int32, [4]> var_1285 = const()[name = tensor<string, []>("op_1285"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1286_cast_fp16 = reshape(shape = var_1285, x = linear_79_cast_fp16)[name = tensor<string, []>("op_1286_cast_fp16")];
            tensor<int32, [4]> var_1287_perm_0 = const()[name = tensor<string, []>("op_1287_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(321185856))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(322414720))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(322414912)))];
            tensor<fp16, [1, 77, 1280]> linear_80_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_79_cast_fp16)[name = tensor<string, []>("linear_80_cast_fp16")];
            tensor<int32, [4]> var_1292 = const()[name = tensor<string, []>("op_1292"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1293_cast_fp16 = reshape(shape = var_1292, x = linear_80_cast_fp16)[name = tensor<string, []>("op_1293_cast_fp16")];
            tensor<int32, [4]> var_1294_perm_0 = const()[name = tensor<string, []>("op_1294_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1301 = const()[name = tensor<string, []>("op_1301"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1302_cast_fp16 = reshape(shape = var_1301, x = tensor_83_cast_fp16)[name = tensor<string, []>("op_1302_cast_fp16")];
            tensor<int32, [4]> var_1303_perm_0 = const()[name = tensor<string, []>("op_1303_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1305 = const()[name = tensor<string, []>("op_1305"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1303_cast_fp16 = transpose(perm = var_1303_perm_0, x = var_1302_cast_fp16)[name = tensor<string, []>("transpose_75")];
            tensor<fp16, [20, 77, 64]> query_states_27_cast_fp16 = reshape(shape = var_1305, x = var_1303_cast_fp16)[name = tensor<string, []>("query_states_27_cast_fp16")];
            tensor<int32, [3]> var_1307 = const()[name = tensor<string, []>("op_1307"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1287_cast_fp16 = transpose(perm = var_1287_perm_0, x = var_1286_cast_fp16)[name = tensor<string, []>("transpose_74")];
            tensor<fp16, [20, 77, 64]> key_states_55_cast_fp16 = reshape(shape = var_1307, x = var_1287_cast_fp16)[name = tensor<string, []>("key_states_55_cast_fp16")];
            tensor<int32, [3]> var_1309 = const()[name = tensor<string, []>("op_1309"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1294_cast_fp16 = transpose(perm = var_1294_perm_0, x = var_1293_cast_fp16)[name = tensor<string, []>("transpose_73")];
            tensor<fp16, [20, 77, 64]> value_states_55_cast_fp16 = reshape(shape = var_1309, x = var_1294_cast_fp16)[name = tensor<string, []>("value_states_55_cast_fp16")];
            tensor<bool, []> attn_weights_79_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_79_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_79_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_79_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_79_cast_fp16 = matmul(transpose_x = attn_weights_79_transpose_x_1, transpose_y = attn_weights_79_transpose_y_1, x = query_states_27_cast_fp16, y = key_states_55_cast_fp16)[name = tensor<string, []>("attn_weights_79_cast_fp16")];
            tensor<int32, [4]> var_1314 = const()[name = tensor<string, []>("op_1314"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1315_cast_fp16 = reshape(shape = var_1314, x = attn_weights_79_cast_fp16)[name = tensor<string, []>("op_1315_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_81_cast_fp16 = add(x = var_1315_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_81_cast_fp16")];
            tensor<int32, [3]> var_1320 = const()[name = tensor<string, []>("op_1320"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_213_cast_fp16 = reshape(shape = var_1320, x = attn_weights_81_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_215_cast_fp16 = softmax(axis = var_5, x = input_213_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
            tensor<bool, []> attn_output_79_transpose_x_0 = const()[name = tensor<string, []>("attn_output_79_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_79_transpose_y_0 = const()[name = tensor<string, []>("attn_output_79_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_79_cast_fp16 = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_215_cast_fp16, y = value_states_55_cast_fp16)[name = tensor<string, []>("attn_output_79_cast_fp16")];
            tensor<int32, [4]> var_1325 = const()[name = tensor<string, []>("op_1325"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_81_cast_fp16 = reshape(shape = var_1325, x = attn_output_79_cast_fp16)[name = tensor<string, []>("attn_output_81_cast_fp16")];
            tensor<int32, [4]> attn_output_83_perm_0 = const()[name = tensor<string, []>("attn_output_83_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1328 = const()[name = tensor<string, []>("op_1328"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_83_cast_fp16 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast_fp16)[name = tensor<string, []>("transpose_72")];
            tensor<fp16, [1, 77, 1280]> input_217_cast_fp16 = reshape(shape = var_1328, x = attn_output_83_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(322417536))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323646400))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323646592)))];
            tensor<fp16, [1, 77, 1280]> linear_81_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized, x = input_217_cast_fp16)[name = tensor<string, []>("linear_81_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_219_cast_fp16 = add(x = input_211_cast_fp16, y = linear_81_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
            tensor<int32, [1]> input_221_axes_0 = const()[name = tensor<string, []>("input_221_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323649216)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323651840)))];
            tensor<fp16, [1, 77, 1280]> input_221_cast_fp16 = layer_norm(axes = input_221_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16, x = input_219_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323654464))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328569728))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328569920)))];
            tensor<fp16, [1, 77, 5120]> linear_82_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized, x = input_221_cast_fp16)[name = tensor<string, []>("linear_82_cast_fp16")];
            tensor<string, []> input_225_mode_0 = const()[name = tensor<string, []>("input_225_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_225_cast_fp16 = gelu(mode = input_225_mode_0, x = linear_82_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328580224))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333495488))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333495680)))];
            tensor<fp16, [1, 77, 1280]> linear_83_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized, x = input_225_cast_fp16)[name = tensor<string, []>("linear_83_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_227_cast_fp16 = add(x = input_219_cast_fp16, y = linear_83_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<int32, [1]> hidden_states_85_axes_0 = const()[name = tensor<string, []>("hidden_states_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333498304)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333500928)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_85_cast_fp16 = layer_norm(axes = hidden_states_85_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("hidden_states_85_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333503552))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(334732416))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(334732608)))];
            tensor<fp16, [1, 77, 1280]> linear_84_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_85_cast_fp16)[name = tensor<string, []>("linear_84_cast_fp16")];
            tensor<fp16, []> var_1367_to_fp16 = const()[name = tensor<string, []>("op_1367_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_89_cast_fp16 = mul(x = linear_84_cast_fp16, y = var_1367_to_fp16)[name = tensor<string, []>("tensor_89_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(334735232))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335964096))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335964288)))];
            tensor<fp16, [1, 77, 1280]> linear_85_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_85_cast_fp16)[name = tensor<string, []>("linear_85_cast_fp16")];
            tensor<int32, [4]> var_1372 = const()[name = tensor<string, []>("op_1372"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1373_cast_fp16 = reshape(shape = var_1372, x = linear_85_cast_fp16)[name = tensor<string, []>("op_1373_cast_fp16")];
            tensor<int32, [4]> var_1374_perm_0 = const()[name = tensor<string, []>("op_1374_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335966912))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(337195776))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(337195968)))];
            tensor<fp16, [1, 77, 1280]> linear_86_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_85_cast_fp16)[name = tensor<string, []>("linear_86_cast_fp16")];
            tensor<int32, [4]> var_1379 = const()[name = tensor<string, []>("op_1379"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1380_cast_fp16 = reshape(shape = var_1379, x = linear_86_cast_fp16)[name = tensor<string, []>("op_1380_cast_fp16")];
            tensor<int32, [4]> var_1381_perm_0 = const()[name = tensor<string, []>("op_1381_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1388 = const()[name = tensor<string, []>("op_1388"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1389_cast_fp16 = reshape(shape = var_1388, x = tensor_89_cast_fp16)[name = tensor<string, []>("op_1389_cast_fp16")];
            tensor<int32, [4]> var_1390_perm_0 = const()[name = tensor<string, []>("op_1390_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1392 = const()[name = tensor<string, []>("op_1392"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1390_cast_fp16 = transpose(perm = var_1390_perm_0, x = var_1389_cast_fp16)[name = tensor<string, []>("transpose_71")];
            tensor<fp16, [20, 77, 64]> query_states_29_cast_fp16 = reshape(shape = var_1392, x = var_1390_cast_fp16)[name = tensor<string, []>("query_states_29_cast_fp16")];
            tensor<int32, [3]> var_1394 = const()[name = tensor<string, []>("op_1394"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1374_cast_fp16 = transpose(perm = var_1374_perm_0, x = var_1373_cast_fp16)[name = tensor<string, []>("transpose_70")];
            tensor<fp16, [20, 77, 64]> key_states_59_cast_fp16 = reshape(shape = var_1394, x = var_1374_cast_fp16)[name = tensor<string, []>("key_states_59_cast_fp16")];
            tensor<int32, [3]> var_1396 = const()[name = tensor<string, []>("op_1396"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1381_cast_fp16 = transpose(perm = var_1381_perm_0, x = var_1380_cast_fp16)[name = tensor<string, []>("transpose_69")];
            tensor<fp16, [20, 77, 64]> value_states_59_cast_fp16 = reshape(shape = var_1396, x = var_1381_cast_fp16)[name = tensor<string, []>("value_states_59_cast_fp16")];
            tensor<bool, []> attn_weights_85_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_85_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_85_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_85_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_85_cast_fp16 = matmul(transpose_x = attn_weights_85_transpose_x_1, transpose_y = attn_weights_85_transpose_y_1, x = query_states_29_cast_fp16, y = key_states_59_cast_fp16)[name = tensor<string, []>("attn_weights_85_cast_fp16")];
            tensor<int32, [4]> var_1401 = const()[name = tensor<string, []>("op_1401"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1402_cast_fp16 = reshape(shape = var_1401, x = attn_weights_85_cast_fp16)[name = tensor<string, []>("op_1402_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_87_cast_fp16 = add(x = var_1402_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_87_cast_fp16")];
            tensor<int32, [3]> var_1407 = const()[name = tensor<string, []>("op_1407"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_229_cast_fp16 = reshape(shape = var_1407, x = attn_weights_87_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_231_cast_fp16 = softmax(axis = var_5, x = input_229_cast_fp16)[name = tensor<string, []>("input_231_cast_fp16")];
            tensor<bool, []> attn_output_85_transpose_x_0 = const()[name = tensor<string, []>("attn_output_85_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_85_transpose_y_0 = const()[name = tensor<string, []>("attn_output_85_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_85_cast_fp16 = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_231_cast_fp16, y = value_states_59_cast_fp16)[name = tensor<string, []>("attn_output_85_cast_fp16")];
            tensor<int32, [4]> var_1412 = const()[name = tensor<string, []>("op_1412"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_87_cast_fp16 = reshape(shape = var_1412, x = attn_output_85_cast_fp16)[name = tensor<string, []>("attn_output_87_cast_fp16")];
            tensor<int32, [4]> attn_output_89_perm_0 = const()[name = tensor<string, []>("attn_output_89_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1415 = const()[name = tensor<string, []>("op_1415"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_89_cast_fp16 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast_fp16)[name = tensor<string, []>("transpose_68")];
            tensor<fp16, [1, 77, 1280]> input_233_cast_fp16 = reshape(shape = var_1415, x = attn_output_89_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(337198592))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338427456))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338427648)))];
            tensor<fp16, [1, 77, 1280]> linear_87_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized, x = input_233_cast_fp16)[name = tensor<string, []>("linear_87_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_235_cast_fp16 = add(x = input_227_cast_fp16, y = linear_87_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
            tensor<int32, [1]> input_237_axes_0 = const()[name = tensor<string, []>("input_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338430272)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338432896)))];
            tensor<fp16, [1, 77, 1280]> input_237_cast_fp16 = layer_norm(axes = input_237_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16, x = input_235_cast_fp16)[name = tensor<string, []>("input_237_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338435520))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343350784))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343350976)))];
            tensor<fp16, [1, 77, 5120]> linear_88_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized, x = input_237_cast_fp16)[name = tensor<string, []>("linear_88_cast_fp16")];
            tensor<string, []> input_241_mode_0 = const()[name = tensor<string, []>("input_241_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_241_cast_fp16 = gelu(mode = input_241_mode_0, x = linear_88_cast_fp16)[name = tensor<string, []>("input_241_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343361280))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348276544))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348276736)))];
            tensor<fp16, [1, 77, 1280]> linear_89_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized, x = input_241_cast_fp16)[name = tensor<string, []>("linear_89_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_243_cast_fp16 = add(x = input_235_cast_fp16, y = linear_89_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
            tensor<int32, [1]> hidden_states_91_axes_0 = const()[name = tensor<string, []>("hidden_states_91_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348279360)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348281984)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_91_cast_fp16 = layer_norm(axes = hidden_states_91_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16, x = input_243_cast_fp16)[name = tensor<string, []>("hidden_states_91_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348284608))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349513472))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349513664)))];
            tensor<fp16, [1, 77, 1280]> linear_90_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_91_cast_fp16)[name = tensor<string, []>("linear_90_cast_fp16")];
            tensor<fp16, []> var_1454_to_fp16 = const()[name = tensor<string, []>("op_1454_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_95_cast_fp16 = mul(x = linear_90_cast_fp16, y = var_1454_to_fp16)[name = tensor<string, []>("tensor_95_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349516288))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(350745152))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(350745344)))];
            tensor<fp16, [1, 77, 1280]> linear_91_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_91_cast_fp16)[name = tensor<string, []>("linear_91_cast_fp16")];
            tensor<int32, [4]> var_1459 = const()[name = tensor<string, []>("op_1459"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1460_cast_fp16 = reshape(shape = var_1459, x = linear_91_cast_fp16)[name = tensor<string, []>("op_1460_cast_fp16")];
            tensor<int32, [4]> var_1461_perm_0 = const()[name = tensor<string, []>("op_1461_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(350747968))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(351976832))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(351977024)))];
            tensor<fp16, [1, 77, 1280]> linear_92_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_91_cast_fp16)[name = tensor<string, []>("linear_92_cast_fp16")];
            tensor<int32, [4]> var_1466 = const()[name = tensor<string, []>("op_1466"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1467_cast_fp16 = reshape(shape = var_1466, x = linear_92_cast_fp16)[name = tensor<string, []>("op_1467_cast_fp16")];
            tensor<int32, [4]> var_1468_perm_0 = const()[name = tensor<string, []>("op_1468_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1475 = const()[name = tensor<string, []>("op_1475"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1476_cast_fp16 = reshape(shape = var_1475, x = tensor_95_cast_fp16)[name = tensor<string, []>("op_1476_cast_fp16")];
            tensor<int32, [4]> var_1477_perm_0 = const()[name = tensor<string, []>("op_1477_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1479 = const()[name = tensor<string, []>("op_1479"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1477_cast_fp16 = transpose(perm = var_1477_perm_0, x = var_1476_cast_fp16)[name = tensor<string, []>("transpose_67")];
            tensor<fp16, [20, 77, 64]> query_states_31_cast_fp16 = reshape(shape = var_1479, x = var_1477_cast_fp16)[name = tensor<string, []>("query_states_31_cast_fp16")];
            tensor<int32, [3]> var_1481 = const()[name = tensor<string, []>("op_1481"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1461_cast_fp16 = transpose(perm = var_1461_perm_0, x = var_1460_cast_fp16)[name = tensor<string, []>("transpose_66")];
            tensor<fp16, [20, 77, 64]> key_states_63_cast_fp16 = reshape(shape = var_1481, x = var_1461_cast_fp16)[name = tensor<string, []>("key_states_63_cast_fp16")];
            tensor<int32, [3]> var_1483 = const()[name = tensor<string, []>("op_1483"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1468_cast_fp16 = transpose(perm = var_1468_perm_0, x = var_1467_cast_fp16)[name = tensor<string, []>("transpose_65")];
            tensor<fp16, [20, 77, 64]> value_states_63_cast_fp16 = reshape(shape = var_1483, x = var_1468_cast_fp16)[name = tensor<string, []>("value_states_63_cast_fp16")];
            tensor<bool, []> attn_weights_91_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_91_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_91_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_91_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_91_cast_fp16 = matmul(transpose_x = attn_weights_91_transpose_x_1, transpose_y = attn_weights_91_transpose_y_1, x = query_states_31_cast_fp16, y = key_states_63_cast_fp16)[name = tensor<string, []>("attn_weights_91_cast_fp16")];
            tensor<int32, [4]> var_1488 = const()[name = tensor<string, []>("op_1488"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1489_cast_fp16 = reshape(shape = var_1488, x = attn_weights_91_cast_fp16)[name = tensor<string, []>("op_1489_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_93_cast_fp16 = add(x = var_1489_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_93_cast_fp16")];
            tensor<int32, [3]> var_1494 = const()[name = tensor<string, []>("op_1494"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_245_cast_fp16 = reshape(shape = var_1494, x = attn_weights_93_cast_fp16)[name = tensor<string, []>("input_245_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_247_cast_fp16 = softmax(axis = var_5, x = input_245_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
            tensor<bool, []> attn_output_91_transpose_x_0 = const()[name = tensor<string, []>("attn_output_91_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_91_transpose_y_0 = const()[name = tensor<string, []>("attn_output_91_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_91_cast_fp16 = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_247_cast_fp16, y = value_states_63_cast_fp16)[name = tensor<string, []>("attn_output_91_cast_fp16")];
            tensor<int32, [4]> var_1499 = const()[name = tensor<string, []>("op_1499"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_93_cast_fp16 = reshape(shape = var_1499, x = attn_output_91_cast_fp16)[name = tensor<string, []>("attn_output_93_cast_fp16")];
            tensor<int32, [4]> attn_output_95_perm_0 = const()[name = tensor<string, []>("attn_output_95_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1502 = const()[name = tensor<string, []>("op_1502"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_95_cast_fp16 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast_fp16)[name = tensor<string, []>("transpose_64")];
            tensor<fp16, [1, 77, 1280]> input_249_cast_fp16 = reshape(shape = var_1502, x = attn_output_95_cast_fp16)[name = tensor<string, []>("input_249_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(351979648))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(353208512))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(353208704)))];
            tensor<fp16, [1, 77, 1280]> linear_93_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized, x = input_249_cast_fp16)[name = tensor<string, []>("linear_93_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_251_cast_fp16 = add(x = input_243_cast_fp16, y = linear_93_cast_fp16)[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<int32, [1]> input_253_axes_0 = const()[name = tensor<string, []>("input_253_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(353211328)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(353213952)))];
            tensor<fp16, [1, 77, 1280]> input_253_cast_fp16 = layer_norm(axes = input_253_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16, x = input_251_cast_fp16)[name = tensor<string, []>("input_253_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(353216576))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(358131840))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(358132032)))];
            tensor<fp16, [1, 77, 5120]> linear_94_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized, x = input_253_cast_fp16)[name = tensor<string, []>("linear_94_cast_fp16")];
            tensor<string, []> input_257_mode_0 = const()[name = tensor<string, []>("input_257_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_257_cast_fp16 = gelu(mode = input_257_mode_0, x = linear_94_cast_fp16)[name = tensor<string, []>("input_257_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(358142336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(363057600))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(363057792)))];
            tensor<fp16, [1, 77, 1280]> linear_95_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized, x = input_257_cast_fp16)[name = tensor<string, []>("linear_95_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_259_cast_fp16 = add(x = input_251_cast_fp16, y = linear_95_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<int32, [1]> hidden_states_97_axes_0 = const()[name = tensor<string, []>("hidden_states_97_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(363060416)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(363063040)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_97_cast_fp16 = layer_norm(axes = hidden_states_97_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16, x = input_259_cast_fp16)[name = tensor<string, []>("hidden_states_97_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(363065664))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(364294528))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(364294720)))];
            tensor<fp16, [1, 77, 1280]> linear_96_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_97_cast_fp16)[name = tensor<string, []>("linear_96_cast_fp16")];
            tensor<fp16, []> var_1541_to_fp16 = const()[name = tensor<string, []>("op_1541_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_101_cast_fp16 = mul(x = linear_96_cast_fp16, y = var_1541_to_fp16)[name = tensor<string, []>("tensor_101_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(364297344))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(365526208))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(365526400)))];
            tensor<fp16, [1, 77, 1280]> linear_97_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_97_cast_fp16)[name = tensor<string, []>("linear_97_cast_fp16")];
            tensor<int32, [4]> var_1546 = const()[name = tensor<string, []>("op_1546"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1547_cast_fp16 = reshape(shape = var_1546, x = linear_97_cast_fp16)[name = tensor<string, []>("op_1547_cast_fp16")];
            tensor<int32, [4]> var_1548_perm_0 = const()[name = tensor<string, []>("op_1548_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(365529024))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366757888))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366758080)))];
            tensor<fp16, [1, 77, 1280]> linear_98_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_97_cast_fp16)[name = tensor<string, []>("linear_98_cast_fp16")];
            tensor<int32, [4]> var_1553 = const()[name = tensor<string, []>("op_1553"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1554_cast_fp16 = reshape(shape = var_1553, x = linear_98_cast_fp16)[name = tensor<string, []>("op_1554_cast_fp16")];
            tensor<int32, [4]> var_1555_perm_0 = const()[name = tensor<string, []>("op_1555_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1562 = const()[name = tensor<string, []>("op_1562"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1563_cast_fp16 = reshape(shape = var_1562, x = tensor_101_cast_fp16)[name = tensor<string, []>("op_1563_cast_fp16")];
            tensor<int32, [4]> var_1564_perm_0 = const()[name = tensor<string, []>("op_1564_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1566 = const()[name = tensor<string, []>("op_1566"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1564_cast_fp16 = transpose(perm = var_1564_perm_0, x = var_1563_cast_fp16)[name = tensor<string, []>("transpose_63")];
            tensor<fp16, [20, 77, 64]> query_states_33_cast_fp16 = reshape(shape = var_1566, x = var_1564_cast_fp16)[name = tensor<string, []>("query_states_33_cast_fp16")];
            tensor<int32, [3]> var_1568 = const()[name = tensor<string, []>("op_1568"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1548_cast_fp16 = transpose(perm = var_1548_perm_0, x = var_1547_cast_fp16)[name = tensor<string, []>("transpose_62")];
            tensor<fp16, [20, 77, 64]> key_states_67_cast_fp16 = reshape(shape = var_1568, x = var_1548_cast_fp16)[name = tensor<string, []>("key_states_67_cast_fp16")];
            tensor<int32, [3]> var_1570 = const()[name = tensor<string, []>("op_1570"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1555_cast_fp16 = transpose(perm = var_1555_perm_0, x = var_1554_cast_fp16)[name = tensor<string, []>("transpose_61")];
            tensor<fp16, [20, 77, 64]> value_states_67_cast_fp16 = reshape(shape = var_1570, x = var_1555_cast_fp16)[name = tensor<string, []>("value_states_67_cast_fp16")];
            tensor<bool, []> attn_weights_97_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_97_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_97_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_97_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_97_cast_fp16 = matmul(transpose_x = attn_weights_97_transpose_x_1, transpose_y = attn_weights_97_transpose_y_1, x = query_states_33_cast_fp16, y = key_states_67_cast_fp16)[name = tensor<string, []>("attn_weights_97_cast_fp16")];
            tensor<int32, [4]> var_1575 = const()[name = tensor<string, []>("op_1575"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1576_cast_fp16 = reshape(shape = var_1575, x = attn_weights_97_cast_fp16)[name = tensor<string, []>("op_1576_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_99_cast_fp16 = add(x = var_1576_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_99_cast_fp16")];
            tensor<int32, [3]> var_1581 = const()[name = tensor<string, []>("op_1581"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_261_cast_fp16 = reshape(shape = var_1581, x = attn_weights_99_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_263_cast_fp16 = softmax(axis = var_5, x = input_261_cast_fp16)[name = tensor<string, []>("input_263_cast_fp16")];
            tensor<bool, []> attn_output_97_transpose_x_0 = const()[name = tensor<string, []>("attn_output_97_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_97_transpose_y_0 = const()[name = tensor<string, []>("attn_output_97_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_97_cast_fp16 = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_263_cast_fp16, y = value_states_67_cast_fp16)[name = tensor<string, []>("attn_output_97_cast_fp16")];
            tensor<int32, [4]> var_1586 = const()[name = tensor<string, []>("op_1586"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_99_cast_fp16 = reshape(shape = var_1586, x = attn_output_97_cast_fp16)[name = tensor<string, []>("attn_output_99_cast_fp16")];
            tensor<int32, [4]> attn_output_101_perm_0 = const()[name = tensor<string, []>("attn_output_101_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1589 = const()[name = tensor<string, []>("op_1589"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_101_cast_fp16 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast_fp16)[name = tensor<string, []>("transpose_60")];
            tensor<fp16, [1, 77, 1280]> input_265_cast_fp16 = reshape(shape = var_1589, x = attn_output_101_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366760704))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367989568))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367989760)))];
            tensor<fp16, [1, 77, 1280]> linear_99_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized, x = input_265_cast_fp16)[name = tensor<string, []>("linear_99_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_267_cast_fp16 = add(x = input_259_cast_fp16, y = linear_99_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<int32, [1]> input_269_axes_0 = const()[name = tensor<string, []>("input_269_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367992384)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367995008)))];
            tensor<fp16, [1, 77, 1280]> input_269_cast_fp16 = layer_norm(axes = input_269_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16, x = input_267_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367997632))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372912896))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372913088)))];
            tensor<fp16, [1, 77, 5120]> linear_100_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized, x = input_269_cast_fp16)[name = tensor<string, []>("linear_100_cast_fp16")];
            tensor<string, []> input_273_mode_0 = const()[name = tensor<string, []>("input_273_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_273_cast_fp16 = gelu(mode = input_273_mode_0, x = linear_100_cast_fp16)[name = tensor<string, []>("input_273_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372923392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377838656))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377838848)))];
            tensor<fp16, [1, 77, 1280]> linear_101_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized, x = input_273_cast_fp16)[name = tensor<string, []>("linear_101_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_275_cast_fp16 = add(x = input_267_cast_fp16, y = linear_101_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
            tensor<int32, [1]> hidden_states_103_axes_0 = const()[name = tensor<string, []>("hidden_states_103_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377841472)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377844096)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_103_cast_fp16 = layer_norm(axes = hidden_states_103_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16, x = input_275_cast_fp16)[name = tensor<string, []>("hidden_states_103_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377846720))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(379075584))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(379075776)))];
            tensor<fp16, [1, 77, 1280]> linear_102_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_103_cast_fp16)[name = tensor<string, []>("linear_102_cast_fp16")];
            tensor<fp16, []> var_1628_to_fp16 = const()[name = tensor<string, []>("op_1628_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_107_cast_fp16 = mul(x = linear_102_cast_fp16, y = var_1628_to_fp16)[name = tensor<string, []>("tensor_107_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(379078400))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(380307264))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(380307456)))];
            tensor<fp16, [1, 77, 1280]> linear_103_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_103_cast_fp16)[name = tensor<string, []>("linear_103_cast_fp16")];
            tensor<int32, [4]> var_1633 = const()[name = tensor<string, []>("op_1633"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1634_cast_fp16 = reshape(shape = var_1633, x = linear_103_cast_fp16)[name = tensor<string, []>("op_1634_cast_fp16")];
            tensor<int32, [4]> var_1635_perm_0 = const()[name = tensor<string, []>("op_1635_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(380310080))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(381538944))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(381539136)))];
            tensor<fp16, [1, 77, 1280]> linear_104_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_103_cast_fp16)[name = tensor<string, []>("linear_104_cast_fp16")];
            tensor<int32, [4]> var_1640 = const()[name = tensor<string, []>("op_1640"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1641_cast_fp16 = reshape(shape = var_1640, x = linear_104_cast_fp16)[name = tensor<string, []>("op_1641_cast_fp16")];
            tensor<int32, [4]> var_1642_perm_0 = const()[name = tensor<string, []>("op_1642_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1649 = const()[name = tensor<string, []>("op_1649"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1650_cast_fp16 = reshape(shape = var_1649, x = tensor_107_cast_fp16)[name = tensor<string, []>("op_1650_cast_fp16")];
            tensor<int32, [4]> var_1651_perm_0 = const()[name = tensor<string, []>("op_1651_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1653 = const()[name = tensor<string, []>("op_1653"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1651_cast_fp16 = transpose(perm = var_1651_perm_0, x = var_1650_cast_fp16)[name = tensor<string, []>("transpose_59")];
            tensor<fp16, [20, 77, 64]> query_states_35_cast_fp16 = reshape(shape = var_1653, x = var_1651_cast_fp16)[name = tensor<string, []>("query_states_35_cast_fp16")];
            tensor<int32, [3]> var_1655 = const()[name = tensor<string, []>("op_1655"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1635_cast_fp16 = transpose(perm = var_1635_perm_0, x = var_1634_cast_fp16)[name = tensor<string, []>("transpose_58")];
            tensor<fp16, [20, 77, 64]> key_states_71_cast_fp16 = reshape(shape = var_1655, x = var_1635_cast_fp16)[name = tensor<string, []>("key_states_71_cast_fp16")];
            tensor<int32, [3]> var_1657 = const()[name = tensor<string, []>("op_1657"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1642_cast_fp16 = transpose(perm = var_1642_perm_0, x = var_1641_cast_fp16)[name = tensor<string, []>("transpose_57")];
            tensor<fp16, [20, 77, 64]> value_states_71_cast_fp16 = reshape(shape = var_1657, x = var_1642_cast_fp16)[name = tensor<string, []>("value_states_71_cast_fp16")];
            tensor<bool, []> attn_weights_103_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_103_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_103_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_103_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_103_cast_fp16 = matmul(transpose_x = attn_weights_103_transpose_x_1, transpose_y = attn_weights_103_transpose_y_1, x = query_states_35_cast_fp16, y = key_states_71_cast_fp16)[name = tensor<string, []>("attn_weights_103_cast_fp16")];
            tensor<int32, [4]> var_1662 = const()[name = tensor<string, []>("op_1662"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1663_cast_fp16 = reshape(shape = var_1662, x = attn_weights_103_cast_fp16)[name = tensor<string, []>("op_1663_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_105_cast_fp16 = add(x = var_1663_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_105_cast_fp16")];
            tensor<int32, [3]> var_1668 = const()[name = tensor<string, []>("op_1668"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_277_cast_fp16 = reshape(shape = var_1668, x = attn_weights_105_cast_fp16)[name = tensor<string, []>("input_277_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_279_cast_fp16 = softmax(axis = var_5, x = input_277_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<bool, []> attn_output_103_transpose_x_0 = const()[name = tensor<string, []>("attn_output_103_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_103_transpose_y_0 = const()[name = tensor<string, []>("attn_output_103_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_103_cast_fp16 = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_279_cast_fp16, y = value_states_71_cast_fp16)[name = tensor<string, []>("attn_output_103_cast_fp16")];
            tensor<int32, [4]> var_1673 = const()[name = tensor<string, []>("op_1673"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_105_cast_fp16 = reshape(shape = var_1673, x = attn_output_103_cast_fp16)[name = tensor<string, []>("attn_output_105_cast_fp16")];
            tensor<int32, [4]> attn_output_107_perm_0 = const()[name = tensor<string, []>("attn_output_107_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1676 = const()[name = tensor<string, []>("op_1676"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_107_cast_fp16 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast_fp16)[name = tensor<string, []>("transpose_56")];
            tensor<fp16, [1, 77, 1280]> input_281_cast_fp16 = reshape(shape = var_1676, x = attn_output_107_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(381541760))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382770624))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382770816)))];
            tensor<fp16, [1, 77, 1280]> linear_105_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized, x = input_281_cast_fp16)[name = tensor<string, []>("linear_105_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_283_cast_fp16 = add(x = input_275_cast_fp16, y = linear_105_cast_fp16)[name = tensor<string, []>("input_283_cast_fp16")];
            tensor<int32, [1]> input_285_axes_0 = const()[name = tensor<string, []>("input_285_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382773440)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382776064)))];
            tensor<fp16, [1, 77, 1280]> input_285_cast_fp16 = layer_norm(axes = input_285_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16, x = input_283_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382778688))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387693952))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387694144)))];
            tensor<fp16, [1, 77, 5120]> linear_106_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized, x = input_285_cast_fp16)[name = tensor<string, []>("linear_106_cast_fp16")];
            tensor<string, []> input_289_mode_0 = const()[name = tensor<string, []>("input_289_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_289_cast_fp16 = gelu(mode = input_289_mode_0, x = linear_106_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387704448))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392619712))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392619904)))];
            tensor<fp16, [1, 77, 1280]> linear_107_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized, x = input_289_cast_fp16)[name = tensor<string, []>("linear_107_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_291_cast_fp16 = add(x = input_283_cast_fp16, y = linear_107_cast_fp16)[name = tensor<string, []>("input_291_cast_fp16")];
            tensor<int32, [1]> hidden_states_109_axes_0 = const()[name = tensor<string, []>("hidden_states_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392622528)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392625152)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_109_cast_fp16 = layer_norm(axes = hidden_states_109_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("hidden_states_109_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392627776))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(393856640))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(393856832)))];
            tensor<fp16, [1, 77, 1280]> linear_108_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_109_cast_fp16)[name = tensor<string, []>("linear_108_cast_fp16")];
            tensor<fp16, []> var_1715_to_fp16 = const()[name = tensor<string, []>("op_1715_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_113_cast_fp16 = mul(x = linear_108_cast_fp16, y = var_1715_to_fp16)[name = tensor<string, []>("tensor_113_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(393859456))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(395088320))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(395088512)))];
            tensor<fp16, [1, 77, 1280]> linear_109_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_109_cast_fp16)[name = tensor<string, []>("linear_109_cast_fp16")];
            tensor<int32, [4]> var_1720 = const()[name = tensor<string, []>("op_1720"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1721_cast_fp16 = reshape(shape = var_1720, x = linear_109_cast_fp16)[name = tensor<string, []>("op_1721_cast_fp16")];
            tensor<int32, [4]> var_1722_perm_0 = const()[name = tensor<string, []>("op_1722_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(395091136))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(396320000))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(396320192)))];
            tensor<fp16, [1, 77, 1280]> linear_110_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_109_cast_fp16)[name = tensor<string, []>("linear_110_cast_fp16")];
            tensor<int32, [4]> var_1727 = const()[name = tensor<string, []>("op_1727"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1728_cast_fp16 = reshape(shape = var_1727, x = linear_110_cast_fp16)[name = tensor<string, []>("op_1728_cast_fp16")];
            tensor<int32, [4]> var_1729_perm_0 = const()[name = tensor<string, []>("op_1729_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1736 = const()[name = tensor<string, []>("op_1736"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1737_cast_fp16 = reshape(shape = var_1736, x = tensor_113_cast_fp16)[name = tensor<string, []>("op_1737_cast_fp16")];
            tensor<int32, [4]> var_1738_perm_0 = const()[name = tensor<string, []>("op_1738_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1740 = const()[name = tensor<string, []>("op_1740"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1738_cast_fp16 = transpose(perm = var_1738_perm_0, x = var_1737_cast_fp16)[name = tensor<string, []>("transpose_55")];
            tensor<fp16, [20, 77, 64]> query_states_37_cast_fp16 = reshape(shape = var_1740, x = var_1738_cast_fp16)[name = tensor<string, []>("query_states_37_cast_fp16")];
            tensor<int32, [3]> var_1742 = const()[name = tensor<string, []>("op_1742"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1722_cast_fp16 = transpose(perm = var_1722_perm_0, x = var_1721_cast_fp16)[name = tensor<string, []>("transpose_54")];
            tensor<fp16, [20, 77, 64]> key_states_75_cast_fp16 = reshape(shape = var_1742, x = var_1722_cast_fp16)[name = tensor<string, []>("key_states_75_cast_fp16")];
            tensor<int32, [3]> var_1744 = const()[name = tensor<string, []>("op_1744"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1729_cast_fp16 = transpose(perm = var_1729_perm_0, x = var_1728_cast_fp16)[name = tensor<string, []>("transpose_53")];
            tensor<fp16, [20, 77, 64]> value_states_75_cast_fp16 = reshape(shape = var_1744, x = var_1729_cast_fp16)[name = tensor<string, []>("value_states_75_cast_fp16")];
            tensor<bool, []> attn_weights_109_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_109_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_109_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_109_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_109_cast_fp16 = matmul(transpose_x = attn_weights_109_transpose_x_1, transpose_y = attn_weights_109_transpose_y_1, x = query_states_37_cast_fp16, y = key_states_75_cast_fp16)[name = tensor<string, []>("attn_weights_109_cast_fp16")];
            tensor<int32, [4]> var_1749 = const()[name = tensor<string, []>("op_1749"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1750_cast_fp16 = reshape(shape = var_1749, x = attn_weights_109_cast_fp16)[name = tensor<string, []>("op_1750_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_111_cast_fp16 = add(x = var_1750_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_111_cast_fp16")];
            tensor<int32, [3]> var_1755 = const()[name = tensor<string, []>("op_1755"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_293_cast_fp16 = reshape(shape = var_1755, x = attn_weights_111_cast_fp16)[name = tensor<string, []>("input_293_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_295_cast_fp16 = softmax(axis = var_5, x = input_293_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
            tensor<bool, []> attn_output_109_transpose_x_0 = const()[name = tensor<string, []>("attn_output_109_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_109_transpose_y_0 = const()[name = tensor<string, []>("attn_output_109_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_109_cast_fp16 = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_295_cast_fp16, y = value_states_75_cast_fp16)[name = tensor<string, []>("attn_output_109_cast_fp16")];
            tensor<int32, [4]> var_1760 = const()[name = tensor<string, []>("op_1760"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_111_cast_fp16 = reshape(shape = var_1760, x = attn_output_109_cast_fp16)[name = tensor<string, []>("attn_output_111_cast_fp16")];
            tensor<int32, [4]> attn_output_113_perm_0 = const()[name = tensor<string, []>("attn_output_113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1763 = const()[name = tensor<string, []>("op_1763"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_113_cast_fp16 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast_fp16)[name = tensor<string, []>("transpose_52")];
            tensor<fp16, [1, 77, 1280]> input_297_cast_fp16 = reshape(shape = var_1763, x = attn_output_113_cast_fp16)[name = tensor<string, []>("input_297_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(396322816))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397551680))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397551872)))];
            tensor<fp16, [1, 77, 1280]> linear_111_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized, x = input_297_cast_fp16)[name = tensor<string, []>("linear_111_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_299_cast_fp16 = add(x = input_291_cast_fp16, y = linear_111_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<int32, [1]> input_301_axes_0 = const()[name = tensor<string, []>("input_301_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397554496)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397557120)))];
            tensor<fp16, [1, 77, 1280]> input_301_cast_fp16 = layer_norm(axes = input_301_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("input_301_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397559744))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402475008))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402475200)))];
            tensor<fp16, [1, 77, 5120]> linear_112_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized, x = input_301_cast_fp16)[name = tensor<string, []>("linear_112_cast_fp16")];
            tensor<string, []> input_305_mode_0 = const()[name = tensor<string, []>("input_305_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_305_cast_fp16 = gelu(mode = input_305_mode_0, x = linear_112_cast_fp16)[name = tensor<string, []>("input_305_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402485504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407400768))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407400960)))];
            tensor<fp16, [1, 77, 1280]> linear_113_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized, x = input_305_cast_fp16)[name = tensor<string, []>("linear_113_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_307_cast_fp16 = add(x = input_299_cast_fp16, y = linear_113_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
            tensor<int32, [1]> hidden_states_115_axes_0 = const()[name = tensor<string, []>("hidden_states_115_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407403584)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407406208)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_115_cast_fp16 = layer_norm(axes = hidden_states_115_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16, x = input_307_cast_fp16)[name = tensor<string, []>("hidden_states_115_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407408832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408637696))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408637888)))];
            tensor<fp16, [1, 77, 1280]> linear_114_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_115_cast_fp16)[name = tensor<string, []>("linear_114_cast_fp16")];
            tensor<fp16, []> var_1802_to_fp16 = const()[name = tensor<string, []>("op_1802_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_119_cast_fp16 = mul(x = linear_114_cast_fp16, y = var_1802_to_fp16)[name = tensor<string, []>("tensor_119_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408640512))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(409869376))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(409869568)))];
            tensor<fp16, [1, 77, 1280]> linear_115_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_115_cast_fp16)[name = tensor<string, []>("linear_115_cast_fp16")];
            tensor<int32, [4]> var_1807 = const()[name = tensor<string, []>("op_1807"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1808_cast_fp16 = reshape(shape = var_1807, x = linear_115_cast_fp16)[name = tensor<string, []>("op_1808_cast_fp16")];
            tensor<int32, [4]> var_1809_perm_0 = const()[name = tensor<string, []>("op_1809_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(409872192))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(411101056))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(411101248)))];
            tensor<fp16, [1, 77, 1280]> linear_116_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_115_cast_fp16)[name = tensor<string, []>("linear_116_cast_fp16")];
            tensor<int32, [4]> var_1814 = const()[name = tensor<string, []>("op_1814"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1815_cast_fp16 = reshape(shape = var_1814, x = linear_116_cast_fp16)[name = tensor<string, []>("op_1815_cast_fp16")];
            tensor<int32, [4]> var_1816_perm_0 = const()[name = tensor<string, []>("op_1816_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1823 = const()[name = tensor<string, []>("op_1823"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1824_cast_fp16 = reshape(shape = var_1823, x = tensor_119_cast_fp16)[name = tensor<string, []>("op_1824_cast_fp16")];
            tensor<int32, [4]> var_1825_perm_0 = const()[name = tensor<string, []>("op_1825_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1827 = const()[name = tensor<string, []>("op_1827"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1825_cast_fp16 = transpose(perm = var_1825_perm_0, x = var_1824_cast_fp16)[name = tensor<string, []>("transpose_51")];
            tensor<fp16, [20, 77, 64]> query_states_39_cast_fp16 = reshape(shape = var_1827, x = var_1825_cast_fp16)[name = tensor<string, []>("query_states_39_cast_fp16")];
            tensor<int32, [3]> var_1829 = const()[name = tensor<string, []>("op_1829"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1809_cast_fp16 = transpose(perm = var_1809_perm_0, x = var_1808_cast_fp16)[name = tensor<string, []>("transpose_50")];
            tensor<fp16, [20, 77, 64]> key_states_79_cast_fp16 = reshape(shape = var_1829, x = var_1809_cast_fp16)[name = tensor<string, []>("key_states_79_cast_fp16")];
            tensor<int32, [3]> var_1831 = const()[name = tensor<string, []>("op_1831"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1816_cast_fp16 = transpose(perm = var_1816_perm_0, x = var_1815_cast_fp16)[name = tensor<string, []>("transpose_49")];
            tensor<fp16, [20, 77, 64]> value_states_79_cast_fp16 = reshape(shape = var_1831, x = var_1816_cast_fp16)[name = tensor<string, []>("value_states_79_cast_fp16")];
            tensor<bool, []> attn_weights_115_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_115_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_115_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_115_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_115_cast_fp16 = matmul(transpose_x = attn_weights_115_transpose_x_1, transpose_y = attn_weights_115_transpose_y_1, x = query_states_39_cast_fp16, y = key_states_79_cast_fp16)[name = tensor<string, []>("attn_weights_115_cast_fp16")];
            tensor<int32, [4]> var_1836 = const()[name = tensor<string, []>("op_1836"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1837_cast_fp16 = reshape(shape = var_1836, x = attn_weights_115_cast_fp16)[name = tensor<string, []>("op_1837_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_117_cast_fp16 = add(x = var_1837_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_117_cast_fp16")];
            tensor<int32, [3]> var_1842 = const()[name = tensor<string, []>("op_1842"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_309_cast_fp16 = reshape(shape = var_1842, x = attn_weights_117_cast_fp16)[name = tensor<string, []>("input_309_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_311_cast_fp16 = softmax(axis = var_5, x = input_309_cast_fp16)[name = tensor<string, []>("input_311_cast_fp16")];
            tensor<bool, []> attn_output_115_transpose_x_0 = const()[name = tensor<string, []>("attn_output_115_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_115_transpose_y_0 = const()[name = tensor<string, []>("attn_output_115_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_115_cast_fp16 = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_311_cast_fp16, y = value_states_79_cast_fp16)[name = tensor<string, []>("attn_output_115_cast_fp16")];
            tensor<int32, [4]> var_1847 = const()[name = tensor<string, []>("op_1847"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_117_cast_fp16 = reshape(shape = var_1847, x = attn_output_115_cast_fp16)[name = tensor<string, []>("attn_output_117_cast_fp16")];
            tensor<int32, [4]> attn_output_119_perm_0 = const()[name = tensor<string, []>("attn_output_119_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1850 = const()[name = tensor<string, []>("op_1850"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_119_cast_fp16 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast_fp16)[name = tensor<string, []>("transpose_48")];
            tensor<fp16, [1, 77, 1280]> input_313_cast_fp16 = reshape(shape = var_1850, x = attn_output_119_cast_fp16)[name = tensor<string, []>("input_313_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(411103872))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412332736))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412332928)))];
            tensor<fp16, [1, 77, 1280]> linear_117_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized, x = input_313_cast_fp16)[name = tensor<string, []>("linear_117_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_315_cast_fp16 = add(x = input_307_cast_fp16, y = linear_117_cast_fp16)[name = tensor<string, []>("input_315_cast_fp16")];
            tensor<int32, [1]> input_317_axes_0 = const()[name = tensor<string, []>("input_317_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412335552)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412338176)))];
            tensor<fp16, [1, 77, 1280]> input_317_cast_fp16 = layer_norm(axes = input_317_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16, x = input_315_cast_fp16)[name = tensor<string, []>("input_317_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412340800))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417256064))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417256256)))];
            tensor<fp16, [1, 77, 5120]> linear_118_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized, x = input_317_cast_fp16)[name = tensor<string, []>("linear_118_cast_fp16")];
            tensor<string, []> input_321_mode_0 = const()[name = tensor<string, []>("input_321_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_321_cast_fp16 = gelu(mode = input_321_mode_0, x = linear_118_cast_fp16)[name = tensor<string, []>("input_321_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417266560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422181824))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422182016)))];
            tensor<fp16, [1, 77, 1280]> linear_119_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized, x = input_321_cast_fp16)[name = tensor<string, []>("linear_119_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_323_cast_fp16 = add(x = input_315_cast_fp16, y = linear_119_cast_fp16)[name = tensor<string, []>("input_323_cast_fp16")];
            tensor<int32, [1]> hidden_states_121_axes_0 = const()[name = tensor<string, []>("hidden_states_121_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422184640)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422187264)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_121_cast_fp16 = layer_norm(axes = hidden_states_121_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16, x = input_323_cast_fp16)[name = tensor<string, []>("hidden_states_121_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422189888))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(423418752))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(423418944)))];
            tensor<fp16, [1, 77, 1280]> linear_120_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_121_cast_fp16)[name = tensor<string, []>("linear_120_cast_fp16")];
            tensor<fp16, []> var_1889_to_fp16 = const()[name = tensor<string, []>("op_1889_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_125_cast_fp16 = mul(x = linear_120_cast_fp16, y = var_1889_to_fp16)[name = tensor<string, []>("tensor_125_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(423421568))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424650432))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424650624)))];
            tensor<fp16, [1, 77, 1280]> linear_121_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_121_cast_fp16)[name = tensor<string, []>("linear_121_cast_fp16")];
            tensor<int32, [4]> var_1894 = const()[name = tensor<string, []>("op_1894"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1895_cast_fp16 = reshape(shape = var_1894, x = linear_121_cast_fp16)[name = tensor<string, []>("op_1895_cast_fp16")];
            tensor<int32, [4]> var_1896_perm_0 = const()[name = tensor<string, []>("op_1896_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424653248))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425882112))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425882304)))];
            tensor<fp16, [1, 77, 1280]> linear_122_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_121_cast_fp16)[name = tensor<string, []>("linear_122_cast_fp16")];
            tensor<int32, [4]> var_1901 = const()[name = tensor<string, []>("op_1901"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1902_cast_fp16 = reshape(shape = var_1901, x = linear_122_cast_fp16)[name = tensor<string, []>("op_1902_cast_fp16")];
            tensor<int32, [4]> var_1903_perm_0 = const()[name = tensor<string, []>("op_1903_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1910 = const()[name = tensor<string, []>("op_1910"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1911_cast_fp16 = reshape(shape = var_1910, x = tensor_125_cast_fp16)[name = tensor<string, []>("op_1911_cast_fp16")];
            tensor<int32, [4]> var_1912_perm_0 = const()[name = tensor<string, []>("op_1912_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1914 = const()[name = tensor<string, []>("op_1914"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1912_cast_fp16 = transpose(perm = var_1912_perm_0, x = var_1911_cast_fp16)[name = tensor<string, []>("transpose_47")];
            tensor<fp16, [20, 77, 64]> query_states_41_cast_fp16 = reshape(shape = var_1914, x = var_1912_cast_fp16)[name = tensor<string, []>("query_states_41_cast_fp16")];
            tensor<int32, [3]> var_1916 = const()[name = tensor<string, []>("op_1916"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1896_cast_fp16 = transpose(perm = var_1896_perm_0, x = var_1895_cast_fp16)[name = tensor<string, []>("transpose_46")];
            tensor<fp16, [20, 77, 64]> key_states_83_cast_fp16 = reshape(shape = var_1916, x = var_1896_cast_fp16)[name = tensor<string, []>("key_states_83_cast_fp16")];
            tensor<int32, [3]> var_1918 = const()[name = tensor<string, []>("op_1918"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1903_cast_fp16 = transpose(perm = var_1903_perm_0, x = var_1902_cast_fp16)[name = tensor<string, []>("transpose_45")];
            tensor<fp16, [20, 77, 64]> value_states_83_cast_fp16 = reshape(shape = var_1918, x = var_1903_cast_fp16)[name = tensor<string, []>("value_states_83_cast_fp16")];
            tensor<bool, []> attn_weights_121_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_121_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_121_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_121_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_121_cast_fp16 = matmul(transpose_x = attn_weights_121_transpose_x_1, transpose_y = attn_weights_121_transpose_y_1, x = query_states_41_cast_fp16, y = key_states_83_cast_fp16)[name = tensor<string, []>("attn_weights_121_cast_fp16")];
            tensor<int32, [4]> var_1923 = const()[name = tensor<string, []>("op_1923"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1924_cast_fp16 = reshape(shape = var_1923, x = attn_weights_121_cast_fp16)[name = tensor<string, []>("op_1924_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_123_cast_fp16 = add(x = var_1924_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_123_cast_fp16")];
            tensor<int32, [3]> var_1929 = const()[name = tensor<string, []>("op_1929"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_325_cast_fp16 = reshape(shape = var_1929, x = attn_weights_123_cast_fp16)[name = tensor<string, []>("input_325_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_327_cast_fp16 = softmax(axis = var_5, x = input_325_cast_fp16)[name = tensor<string, []>("input_327_cast_fp16")];
            tensor<bool, []> attn_output_121_transpose_x_0 = const()[name = tensor<string, []>("attn_output_121_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_121_transpose_y_0 = const()[name = tensor<string, []>("attn_output_121_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_121_cast_fp16 = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_327_cast_fp16, y = value_states_83_cast_fp16)[name = tensor<string, []>("attn_output_121_cast_fp16")];
            tensor<int32, [4]> var_1934 = const()[name = tensor<string, []>("op_1934"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_123_cast_fp16 = reshape(shape = var_1934, x = attn_output_121_cast_fp16)[name = tensor<string, []>("attn_output_123_cast_fp16")];
            tensor<int32, [4]> attn_output_125_perm_0 = const()[name = tensor<string, []>("attn_output_125_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1937 = const()[name = tensor<string, []>("op_1937"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_125_cast_fp16 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast_fp16)[name = tensor<string, []>("transpose_44")];
            tensor<fp16, [1, 77, 1280]> input_329_cast_fp16 = reshape(shape = var_1937, x = attn_output_125_cast_fp16)[name = tensor<string, []>("input_329_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425884928))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427113792))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427113984)))];
            tensor<fp16, [1, 77, 1280]> linear_123_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized, x = input_329_cast_fp16)[name = tensor<string, []>("linear_123_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_331_cast_fp16 = add(x = input_323_cast_fp16, y = linear_123_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
            tensor<int32, [1]> input_333_axes_0 = const()[name = tensor<string, []>("input_333_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427116608)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427119232)))];
            tensor<fp16, [1, 77, 1280]> input_333_cast_fp16 = layer_norm(axes = input_333_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16, x = input_331_cast_fp16)[name = tensor<string, []>("input_333_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427121856))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(432037120))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(432037312)))];
            tensor<fp16, [1, 77, 5120]> linear_124_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized, x = input_333_cast_fp16)[name = tensor<string, []>("linear_124_cast_fp16")];
            tensor<string, []> input_337_mode_0 = const()[name = tensor<string, []>("input_337_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_337_cast_fp16 = gelu(mode = input_337_mode_0, x = linear_124_cast_fp16)[name = tensor<string, []>("input_337_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(432047616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436962880))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436963072)))];
            tensor<fp16, [1, 77, 1280]> linear_125_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized, x = input_337_cast_fp16)[name = tensor<string, []>("linear_125_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_339_cast_fp16 = add(x = input_331_cast_fp16, y = linear_125_cast_fp16)[name = tensor<string, []>("input_339_cast_fp16")];
            tensor<int32, [1]> hidden_states_127_axes_0 = const()[name = tensor<string, []>("hidden_states_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436965696)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436968320)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_127_cast_fp16 = layer_norm(axes = hidden_states_127_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16, x = input_339_cast_fp16)[name = tensor<string, []>("hidden_states_127_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436970944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(438199808))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(438200000)))];
            tensor<fp16, [1, 77, 1280]> linear_126_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_127_cast_fp16)[name = tensor<string, []>("linear_126_cast_fp16")];
            tensor<fp16, []> var_1976_to_fp16 = const()[name = tensor<string, []>("op_1976_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_131_cast_fp16 = mul(x = linear_126_cast_fp16, y = var_1976_to_fp16)[name = tensor<string, []>("tensor_131_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(438202624))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(439431488))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(439431680)))];
            tensor<fp16, [1, 77, 1280]> linear_127_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_127_cast_fp16)[name = tensor<string, []>("linear_127_cast_fp16")];
            tensor<int32, [4]> var_1981 = const()[name = tensor<string, []>("op_1981"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1982_cast_fp16 = reshape(shape = var_1981, x = linear_127_cast_fp16)[name = tensor<string, []>("op_1982_cast_fp16")];
            tensor<int32, [4]> var_1983_perm_0 = const()[name = tensor<string, []>("op_1983_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(439434304))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(440663168))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(440663360)))];
            tensor<fp16, [1, 77, 1280]> linear_128_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_127_cast_fp16)[name = tensor<string, []>("linear_128_cast_fp16")];
            tensor<int32, [4]> var_1988 = const()[name = tensor<string, []>("op_1988"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1989_cast_fp16 = reshape(shape = var_1988, x = linear_128_cast_fp16)[name = tensor<string, []>("op_1989_cast_fp16")];
            tensor<int32, [4]> var_1990_perm_0 = const()[name = tensor<string, []>("op_1990_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1997 = const()[name = tensor<string, []>("op_1997"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1998_cast_fp16 = reshape(shape = var_1997, x = tensor_131_cast_fp16)[name = tensor<string, []>("op_1998_cast_fp16")];
            tensor<int32, [4]> var_1999_perm_0 = const()[name = tensor<string, []>("op_1999_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2001 = const()[name = tensor<string, []>("op_2001"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1999_cast_fp16 = transpose(perm = var_1999_perm_0, x = var_1998_cast_fp16)[name = tensor<string, []>("transpose_43")];
            tensor<fp16, [20, 77, 64]> query_states_43_cast_fp16 = reshape(shape = var_2001, x = var_1999_cast_fp16)[name = tensor<string, []>("query_states_43_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = tensor<string, []>("op_2003"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1983_cast_fp16 = transpose(perm = var_1983_perm_0, x = var_1982_cast_fp16)[name = tensor<string, []>("transpose_42")];
            tensor<fp16, [20, 77, 64]> key_states_87_cast_fp16 = reshape(shape = var_2003, x = var_1983_cast_fp16)[name = tensor<string, []>("key_states_87_cast_fp16")];
            tensor<int32, [3]> var_2005 = const()[name = tensor<string, []>("op_2005"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1990_cast_fp16 = transpose(perm = var_1990_perm_0, x = var_1989_cast_fp16)[name = tensor<string, []>("transpose_41")];
            tensor<fp16, [20, 77, 64]> value_states_87_cast_fp16 = reshape(shape = var_2005, x = var_1990_cast_fp16)[name = tensor<string, []>("value_states_87_cast_fp16")];
            tensor<bool, []> attn_weights_127_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_127_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_127_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_127_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_127_cast_fp16 = matmul(transpose_x = attn_weights_127_transpose_x_1, transpose_y = attn_weights_127_transpose_y_1, x = query_states_43_cast_fp16, y = key_states_87_cast_fp16)[name = tensor<string, []>("attn_weights_127_cast_fp16")];
            tensor<int32, [4]> var_2010 = const()[name = tensor<string, []>("op_2010"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2011_cast_fp16 = reshape(shape = var_2010, x = attn_weights_127_cast_fp16)[name = tensor<string, []>("op_2011_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_129_cast_fp16 = add(x = var_2011_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_129_cast_fp16")];
            tensor<int32, [3]> var_2016 = const()[name = tensor<string, []>("op_2016"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_341_cast_fp16 = reshape(shape = var_2016, x = attn_weights_129_cast_fp16)[name = tensor<string, []>("input_341_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_343_cast_fp16 = softmax(axis = var_5, x = input_341_cast_fp16)[name = tensor<string, []>("input_343_cast_fp16")];
            tensor<bool, []> attn_output_127_transpose_x_0 = const()[name = tensor<string, []>("attn_output_127_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_127_transpose_y_0 = const()[name = tensor<string, []>("attn_output_127_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_127_cast_fp16 = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_343_cast_fp16, y = value_states_87_cast_fp16)[name = tensor<string, []>("attn_output_127_cast_fp16")];
            tensor<int32, [4]> var_2021 = const()[name = tensor<string, []>("op_2021"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_129_cast_fp16 = reshape(shape = var_2021, x = attn_output_127_cast_fp16)[name = tensor<string, []>("attn_output_129_cast_fp16")];
            tensor<int32, [4]> attn_output_131_perm_0 = const()[name = tensor<string, []>("attn_output_131_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2024 = const()[name = tensor<string, []>("op_2024"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_131_cast_fp16 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast_fp16)[name = tensor<string, []>("transpose_40")];
            tensor<fp16, [1, 77, 1280]> input_345_cast_fp16 = reshape(shape = var_2024, x = attn_output_131_cast_fp16)[name = tensor<string, []>("input_345_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(440665984))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441894848))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441895040)))];
            tensor<fp16, [1, 77, 1280]> linear_129_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized, x = input_345_cast_fp16)[name = tensor<string, []>("linear_129_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_347_cast_fp16 = add(x = input_339_cast_fp16, y = linear_129_cast_fp16)[name = tensor<string, []>("input_347_cast_fp16")];
            tensor<int32, [1]> input_349_axes_0 = const()[name = tensor<string, []>("input_349_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441897664)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441900288)))];
            tensor<fp16, [1, 77, 1280]> input_349_cast_fp16 = layer_norm(axes = input_349_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16, x = input_347_cast_fp16)[name = tensor<string, []>("input_349_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441902912))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446818176))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446818368)))];
            tensor<fp16, [1, 77, 5120]> linear_130_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized, x = input_349_cast_fp16)[name = tensor<string, []>("linear_130_cast_fp16")];
            tensor<string, []> input_353_mode_0 = const()[name = tensor<string, []>("input_353_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_353_cast_fp16 = gelu(mode = input_353_mode_0, x = linear_130_cast_fp16)[name = tensor<string, []>("input_353_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446828672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451743936))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451744128)))];
            tensor<fp16, [1, 77, 1280]> linear_131_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized, x = input_353_cast_fp16)[name = tensor<string, []>("linear_131_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_355_cast_fp16 = add(x = input_347_cast_fp16, y = linear_131_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
            tensor<int32, [1]> hidden_states_133_axes_0 = const()[name = tensor<string, []>("hidden_states_133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451746752)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451749376)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_133_cast_fp16 = layer_norm(axes = hidden_states_133_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16, x = input_355_cast_fp16)[name = tensor<string, []>("hidden_states_133_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451752000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(452980864))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(452981056)))];
            tensor<fp16, [1, 77, 1280]> linear_132_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_133_cast_fp16)[name = tensor<string, []>("linear_132_cast_fp16")];
            tensor<fp16, []> var_2063_to_fp16 = const()[name = tensor<string, []>("op_2063_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_137_cast_fp16 = mul(x = linear_132_cast_fp16, y = var_2063_to_fp16)[name = tensor<string, []>("tensor_137_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(452983680))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454212544))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454212736)))];
            tensor<fp16, [1, 77, 1280]> linear_133_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_133_cast_fp16)[name = tensor<string, []>("linear_133_cast_fp16")];
            tensor<int32, [4]> var_2068 = const()[name = tensor<string, []>("op_2068"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2069_cast_fp16 = reshape(shape = var_2068, x = linear_133_cast_fp16)[name = tensor<string, []>("op_2069_cast_fp16")];
            tensor<int32, [4]> var_2070_perm_0 = const()[name = tensor<string, []>("op_2070_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454215360))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(455444224))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(455444416)))];
            tensor<fp16, [1, 77, 1280]> linear_134_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_133_cast_fp16)[name = tensor<string, []>("linear_134_cast_fp16")];
            tensor<int32, [4]> var_2075 = const()[name = tensor<string, []>("op_2075"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2076_cast_fp16 = reshape(shape = var_2075, x = linear_134_cast_fp16)[name = tensor<string, []>("op_2076_cast_fp16")];
            tensor<int32, [4]> var_2077_perm_0 = const()[name = tensor<string, []>("op_2077_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2084 = const()[name = tensor<string, []>("op_2084"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2085_cast_fp16 = reshape(shape = var_2084, x = tensor_137_cast_fp16)[name = tensor<string, []>("op_2085_cast_fp16")];
            tensor<int32, [4]> var_2086_perm_0 = const()[name = tensor<string, []>("op_2086_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2088 = const()[name = tensor<string, []>("op_2088"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2086_cast_fp16 = transpose(perm = var_2086_perm_0, x = var_2085_cast_fp16)[name = tensor<string, []>("transpose_39")];
            tensor<fp16, [20, 77, 64]> query_states_45_cast_fp16 = reshape(shape = var_2088, x = var_2086_cast_fp16)[name = tensor<string, []>("query_states_45_cast_fp16")];
            tensor<int32, [3]> var_2090 = const()[name = tensor<string, []>("op_2090"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2070_cast_fp16 = transpose(perm = var_2070_perm_0, x = var_2069_cast_fp16)[name = tensor<string, []>("transpose_38")];
            tensor<fp16, [20, 77, 64]> key_states_91_cast_fp16 = reshape(shape = var_2090, x = var_2070_cast_fp16)[name = tensor<string, []>("key_states_91_cast_fp16")];
            tensor<int32, [3]> var_2092 = const()[name = tensor<string, []>("op_2092"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2077_cast_fp16 = transpose(perm = var_2077_perm_0, x = var_2076_cast_fp16)[name = tensor<string, []>("transpose_37")];
            tensor<fp16, [20, 77, 64]> value_states_91_cast_fp16 = reshape(shape = var_2092, x = var_2077_cast_fp16)[name = tensor<string, []>("value_states_91_cast_fp16")];
            tensor<bool, []> attn_weights_133_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_133_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_133_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_133_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_133_cast_fp16 = matmul(transpose_x = attn_weights_133_transpose_x_1, transpose_y = attn_weights_133_transpose_y_1, x = query_states_45_cast_fp16, y = key_states_91_cast_fp16)[name = tensor<string, []>("attn_weights_133_cast_fp16")];
            tensor<int32, [4]> var_2097 = const()[name = tensor<string, []>("op_2097"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2098_cast_fp16 = reshape(shape = var_2097, x = attn_weights_133_cast_fp16)[name = tensor<string, []>("op_2098_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_135_cast_fp16 = add(x = var_2098_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_135_cast_fp16")];
            tensor<int32, [3]> var_2103 = const()[name = tensor<string, []>("op_2103"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_357_cast_fp16 = reshape(shape = var_2103, x = attn_weights_135_cast_fp16)[name = tensor<string, []>("input_357_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_359_cast_fp16 = softmax(axis = var_5, x = input_357_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
            tensor<bool, []> attn_output_133_transpose_x_0 = const()[name = tensor<string, []>("attn_output_133_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_133_transpose_y_0 = const()[name = tensor<string, []>("attn_output_133_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_133_cast_fp16 = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_359_cast_fp16, y = value_states_91_cast_fp16)[name = tensor<string, []>("attn_output_133_cast_fp16")];
            tensor<int32, [4]> var_2108 = const()[name = tensor<string, []>("op_2108"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_135_cast_fp16 = reshape(shape = var_2108, x = attn_output_133_cast_fp16)[name = tensor<string, []>("attn_output_135_cast_fp16")];
            tensor<int32, [4]> attn_output_137_perm_0 = const()[name = tensor<string, []>("attn_output_137_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2111 = const()[name = tensor<string, []>("op_2111"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_137_cast_fp16 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast_fp16)[name = tensor<string, []>("transpose_36")];
            tensor<fp16, [1, 77, 1280]> input_361_cast_fp16 = reshape(shape = var_2111, x = attn_output_137_cast_fp16)[name = tensor<string, []>("input_361_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(455447040))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456675904))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456676096)))];
            tensor<fp16, [1, 77, 1280]> linear_135_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized, x = input_361_cast_fp16)[name = tensor<string, []>("linear_135_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_363_cast_fp16 = add(x = input_355_cast_fp16, y = linear_135_cast_fp16)[name = tensor<string, []>("input_363_cast_fp16")];
            tensor<int32, [1]> input_365_axes_0 = const()[name = tensor<string, []>("input_365_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456678720)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456681344)))];
            tensor<fp16, [1, 77, 1280]> input_365_cast_fp16 = layer_norm(axes = input_365_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16, x = input_363_cast_fp16)[name = tensor<string, []>("input_365_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456683968))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461599232))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461599424)))];
            tensor<fp16, [1, 77, 5120]> linear_136_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized, x = input_365_cast_fp16)[name = tensor<string, []>("linear_136_cast_fp16")];
            tensor<string, []> input_369_mode_0 = const()[name = tensor<string, []>("input_369_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_369_cast_fp16 = gelu(mode = input_369_mode_0, x = linear_136_cast_fp16)[name = tensor<string, []>("input_369_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461609728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466524992))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466525184)))];
            tensor<fp16, [1, 77, 1280]> linear_137_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized, x = input_369_cast_fp16)[name = tensor<string, []>("linear_137_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_371_cast_fp16 = add(x = input_363_cast_fp16, y = linear_137_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
            tensor<int32, [1]> hidden_states_139_axes_0 = const()[name = tensor<string, []>("hidden_states_139_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466527808)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466530432)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_139_cast_fp16 = layer_norm(axes = hidden_states_139_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16, x = input_371_cast_fp16)[name = tensor<string, []>("hidden_states_139_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466533056))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467761920))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467762112)))];
            tensor<fp16, [1, 77, 1280]> linear_138_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_139_cast_fp16)[name = tensor<string, []>("linear_138_cast_fp16")];
            tensor<fp16, []> var_2150_to_fp16 = const()[name = tensor<string, []>("op_2150_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_143_cast_fp16 = mul(x = linear_138_cast_fp16, y = var_2150_to_fp16)[name = tensor<string, []>("tensor_143_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467764736))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(468993600))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(468993792)))];
            tensor<fp16, [1, 77, 1280]> linear_139_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_139_cast_fp16)[name = tensor<string, []>("linear_139_cast_fp16")];
            tensor<int32, [4]> var_2155 = const()[name = tensor<string, []>("op_2155"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2156_cast_fp16 = reshape(shape = var_2155, x = linear_139_cast_fp16)[name = tensor<string, []>("op_2156_cast_fp16")];
            tensor<int32, [4]> var_2157_perm_0 = const()[name = tensor<string, []>("op_2157_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(468996416))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(470225280))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(470225472)))];
            tensor<fp16, [1, 77, 1280]> linear_140_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_139_cast_fp16)[name = tensor<string, []>("linear_140_cast_fp16")];
            tensor<int32, [4]> var_2162 = const()[name = tensor<string, []>("op_2162"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2163_cast_fp16 = reshape(shape = var_2162, x = linear_140_cast_fp16)[name = tensor<string, []>("op_2163_cast_fp16")];
            tensor<int32, [4]> var_2164_perm_0 = const()[name = tensor<string, []>("op_2164_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2171 = const()[name = tensor<string, []>("op_2171"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2172_cast_fp16 = reshape(shape = var_2171, x = tensor_143_cast_fp16)[name = tensor<string, []>("op_2172_cast_fp16")];
            tensor<int32, [4]> var_2173_perm_0 = const()[name = tensor<string, []>("op_2173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2175 = const()[name = tensor<string, []>("op_2175"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2173_cast_fp16 = transpose(perm = var_2173_perm_0, x = var_2172_cast_fp16)[name = tensor<string, []>("transpose_35")];
            tensor<fp16, [20, 77, 64]> query_states_47_cast_fp16 = reshape(shape = var_2175, x = var_2173_cast_fp16)[name = tensor<string, []>("query_states_47_cast_fp16")];
            tensor<int32, [3]> var_2177 = const()[name = tensor<string, []>("op_2177"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2157_cast_fp16 = transpose(perm = var_2157_perm_0, x = var_2156_cast_fp16)[name = tensor<string, []>("transpose_34")];
            tensor<fp16, [20, 77, 64]> key_states_95_cast_fp16 = reshape(shape = var_2177, x = var_2157_cast_fp16)[name = tensor<string, []>("key_states_95_cast_fp16")];
            tensor<int32, [3]> var_2179 = const()[name = tensor<string, []>("op_2179"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2164_cast_fp16 = transpose(perm = var_2164_perm_0, x = var_2163_cast_fp16)[name = tensor<string, []>("transpose_33")];
            tensor<fp16, [20, 77, 64]> value_states_95_cast_fp16 = reshape(shape = var_2179, x = var_2164_cast_fp16)[name = tensor<string, []>("value_states_95_cast_fp16")];
            tensor<bool, []> attn_weights_139_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_139_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_139_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_139_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_139_cast_fp16 = matmul(transpose_x = attn_weights_139_transpose_x_1, transpose_y = attn_weights_139_transpose_y_1, x = query_states_47_cast_fp16, y = key_states_95_cast_fp16)[name = tensor<string, []>("attn_weights_139_cast_fp16")];
            tensor<int32, [4]> var_2184 = const()[name = tensor<string, []>("op_2184"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2185_cast_fp16 = reshape(shape = var_2184, x = attn_weights_139_cast_fp16)[name = tensor<string, []>("op_2185_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_141_cast_fp16 = add(x = var_2185_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_141_cast_fp16")];
            tensor<int32, [3]> var_2190 = const()[name = tensor<string, []>("op_2190"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_373_cast_fp16 = reshape(shape = var_2190, x = attn_weights_141_cast_fp16)[name = tensor<string, []>("input_373_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_375_cast_fp16 = softmax(axis = var_5, x = input_373_cast_fp16)[name = tensor<string, []>("input_375_cast_fp16")];
            tensor<bool, []> attn_output_139_transpose_x_0 = const()[name = tensor<string, []>("attn_output_139_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_139_transpose_y_0 = const()[name = tensor<string, []>("attn_output_139_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_139_cast_fp16 = matmul(transpose_x = attn_output_139_transpose_x_0, transpose_y = attn_output_139_transpose_y_0, x = input_375_cast_fp16, y = value_states_95_cast_fp16)[name = tensor<string, []>("attn_output_139_cast_fp16")];
            tensor<int32, [4]> var_2195 = const()[name = tensor<string, []>("op_2195"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_141_cast_fp16 = reshape(shape = var_2195, x = attn_output_139_cast_fp16)[name = tensor<string, []>("attn_output_141_cast_fp16")];
            tensor<int32, [4]> attn_output_143_perm_0 = const()[name = tensor<string, []>("attn_output_143_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2198 = const()[name = tensor<string, []>("op_2198"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_143_cast_fp16 = transpose(perm = attn_output_143_perm_0, x = attn_output_141_cast_fp16)[name = tensor<string, []>("transpose_32")];
            tensor<fp16, [1, 77, 1280]> input_377_cast_fp16 = reshape(shape = var_2198, x = attn_output_143_cast_fp16)[name = tensor<string, []>("input_377_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(470228096))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471456960))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471457152)))];
            tensor<fp16, [1, 77, 1280]> linear_141_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized, x = input_377_cast_fp16)[name = tensor<string, []>("linear_141_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_379_cast_fp16 = add(x = input_371_cast_fp16, y = linear_141_cast_fp16)[name = tensor<string, []>("input_379_cast_fp16")];
            tensor<int32, [1]> input_381_axes_0 = const()[name = tensor<string, []>("input_381_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471459776)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471462400)))];
            tensor<fp16, [1, 77, 1280]> input_381_cast_fp16 = layer_norm(axes = input_381_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16, x = input_379_cast_fp16)[name = tensor<string, []>("input_381_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471465024))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476380288))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476380480)))];
            tensor<fp16, [1, 77, 5120]> linear_142_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized, x = input_381_cast_fp16)[name = tensor<string, []>("linear_142_cast_fp16")];
            tensor<string, []> input_385_mode_0 = const()[name = tensor<string, []>("input_385_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_385_cast_fp16 = gelu(mode = input_385_mode_0, x = linear_142_cast_fp16)[name = tensor<string, []>("input_385_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476390784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481306048))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481306240)))];
            tensor<fp16, [1, 77, 1280]> linear_143_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized, x = input_385_cast_fp16)[name = tensor<string, []>("linear_143_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_387_cast_fp16 = add(x = input_379_cast_fp16, y = linear_143_cast_fp16)[name = tensor<string, []>("input_387_cast_fp16")];
            tensor<int32, [1]> hidden_states_145_axes_0 = const()[name = tensor<string, []>("hidden_states_145_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481308864)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481311488)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_145_cast_fp16 = layer_norm(axes = hidden_states_145_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16, x = input_387_cast_fp16)[name = tensor<string, []>("hidden_states_145_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481314112))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482542976))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482543168)))];
            tensor<fp16, [1, 77, 1280]> linear_144_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_145_cast_fp16)[name = tensor<string, []>("linear_144_cast_fp16")];
            tensor<fp16, []> var_2237_to_fp16 = const()[name = tensor<string, []>("op_2237_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_149_cast_fp16 = mul(x = linear_144_cast_fp16, y = var_2237_to_fp16)[name = tensor<string, []>("tensor_149_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482545792))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(483774656))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(483774848)))];
            tensor<fp16, [1, 77, 1280]> linear_145_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_145_cast_fp16)[name = tensor<string, []>("linear_145_cast_fp16")];
            tensor<int32, [4]> var_2242 = const()[name = tensor<string, []>("op_2242"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2243_cast_fp16 = reshape(shape = var_2242, x = linear_145_cast_fp16)[name = tensor<string, []>("op_2243_cast_fp16")];
            tensor<int32, [4]> var_2244_perm_0 = const()[name = tensor<string, []>("op_2244_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(483777472))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(485006336))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(485006528)))];
            tensor<fp16, [1, 77, 1280]> linear_146_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_145_cast_fp16)[name = tensor<string, []>("linear_146_cast_fp16")];
            tensor<int32, [4]> var_2249 = const()[name = tensor<string, []>("op_2249"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2250_cast_fp16 = reshape(shape = var_2249, x = linear_146_cast_fp16)[name = tensor<string, []>("op_2250_cast_fp16")];
            tensor<int32, [4]> var_2251_perm_0 = const()[name = tensor<string, []>("op_2251_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2258 = const()[name = tensor<string, []>("op_2258"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2259_cast_fp16 = reshape(shape = var_2258, x = tensor_149_cast_fp16)[name = tensor<string, []>("op_2259_cast_fp16")];
            tensor<int32, [4]> var_2260_perm_0 = const()[name = tensor<string, []>("op_2260_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2262 = const()[name = tensor<string, []>("op_2262"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2260_cast_fp16 = transpose(perm = var_2260_perm_0, x = var_2259_cast_fp16)[name = tensor<string, []>("transpose_31")];
            tensor<fp16, [20, 77, 64]> query_states_49_cast_fp16 = reshape(shape = var_2262, x = var_2260_cast_fp16)[name = tensor<string, []>("query_states_49_cast_fp16")];
            tensor<int32, [3]> var_2264 = const()[name = tensor<string, []>("op_2264"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2244_cast_fp16 = transpose(perm = var_2244_perm_0, x = var_2243_cast_fp16)[name = tensor<string, []>("transpose_30")];
            tensor<fp16, [20, 77, 64]> key_states_99_cast_fp16 = reshape(shape = var_2264, x = var_2244_cast_fp16)[name = tensor<string, []>("key_states_99_cast_fp16")];
            tensor<int32, [3]> var_2266 = const()[name = tensor<string, []>("op_2266"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2251_cast_fp16 = transpose(perm = var_2251_perm_0, x = var_2250_cast_fp16)[name = tensor<string, []>("transpose_29")];
            tensor<fp16, [20, 77, 64]> value_states_99_cast_fp16 = reshape(shape = var_2266, x = var_2251_cast_fp16)[name = tensor<string, []>("value_states_99_cast_fp16")];
            tensor<bool, []> attn_weights_145_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_145_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_145_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_145_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_145_cast_fp16 = matmul(transpose_x = attn_weights_145_transpose_x_1, transpose_y = attn_weights_145_transpose_y_1, x = query_states_49_cast_fp16, y = key_states_99_cast_fp16)[name = tensor<string, []>("attn_weights_145_cast_fp16")];
            tensor<int32, [4]> var_2271 = const()[name = tensor<string, []>("op_2271"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2272_cast_fp16 = reshape(shape = var_2271, x = attn_weights_145_cast_fp16)[name = tensor<string, []>("op_2272_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_147_cast_fp16 = add(x = var_2272_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_147_cast_fp16")];
            tensor<int32, [3]> var_2277 = const()[name = tensor<string, []>("op_2277"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_389_cast_fp16 = reshape(shape = var_2277, x = attn_weights_147_cast_fp16)[name = tensor<string, []>("input_389_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_391_cast_fp16 = softmax(axis = var_5, x = input_389_cast_fp16)[name = tensor<string, []>("input_391_cast_fp16")];
            tensor<bool, []> attn_output_145_transpose_x_0 = const()[name = tensor<string, []>("attn_output_145_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_145_transpose_y_0 = const()[name = tensor<string, []>("attn_output_145_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_145_cast_fp16 = matmul(transpose_x = attn_output_145_transpose_x_0, transpose_y = attn_output_145_transpose_y_0, x = input_391_cast_fp16, y = value_states_99_cast_fp16)[name = tensor<string, []>("attn_output_145_cast_fp16")];
            tensor<int32, [4]> var_2282 = const()[name = tensor<string, []>("op_2282"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_147_cast_fp16 = reshape(shape = var_2282, x = attn_output_145_cast_fp16)[name = tensor<string, []>("attn_output_147_cast_fp16")];
            tensor<int32, [4]> attn_output_149_perm_0 = const()[name = tensor<string, []>("attn_output_149_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2285 = const()[name = tensor<string, []>("op_2285"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_149_cast_fp16 = transpose(perm = attn_output_149_perm_0, x = attn_output_147_cast_fp16)[name = tensor<string, []>("transpose_28")];
            tensor<fp16, [1, 77, 1280]> input_393_cast_fp16 = reshape(shape = var_2285, x = attn_output_149_cast_fp16)[name = tensor<string, []>("input_393_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(485009152))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486238016))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486238208)))];
            tensor<fp16, [1, 77, 1280]> linear_147_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized, x = input_393_cast_fp16)[name = tensor<string, []>("linear_147_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_395_cast_fp16 = add(x = input_387_cast_fp16, y = linear_147_cast_fp16)[name = tensor<string, []>("input_395_cast_fp16")];
            tensor<int32, [1]> input_397_axes_0 = const()[name = tensor<string, []>("input_397_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486240832)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486243456)))];
            tensor<fp16, [1, 77, 1280]> input_397_cast_fp16 = layer_norm(axes = input_397_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16, x = input_395_cast_fp16)[name = tensor<string, []>("input_397_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486246080))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(491161344))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(491161536)))];
            tensor<fp16, [1, 77, 5120]> linear_148_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized, x = input_397_cast_fp16)[name = tensor<string, []>("linear_148_cast_fp16")];
            tensor<string, []> input_401_mode_0 = const()[name = tensor<string, []>("input_401_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_401_cast_fp16 = gelu(mode = input_401_mode_0, x = linear_148_cast_fp16)[name = tensor<string, []>("input_401_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(491171840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(496087104))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(496087296)))];
            tensor<fp16, [1, 77, 1280]> linear_149_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized, x = input_401_cast_fp16)[name = tensor<string, []>("linear_149_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_403_cast_fp16 = add(x = input_395_cast_fp16, y = linear_149_cast_fp16)[name = tensor<string, []>("input_403_cast_fp16")];
            tensor<int32, [1]> hidden_states_151_axes_0 = const()[name = tensor<string, []>("hidden_states_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(496089920)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(496092544)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_151_cast_fp16 = layer_norm(axes = hidden_states_151_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16, x = input_403_cast_fp16)[name = tensor<string, []>("hidden_states_151_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(496095168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(497324032))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(497324224)))];
            tensor<fp16, [1, 77, 1280]> linear_150_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_151_cast_fp16)[name = tensor<string, []>("linear_150_cast_fp16")];
            tensor<fp16, []> var_2324_to_fp16 = const()[name = tensor<string, []>("op_2324_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_155_cast_fp16 = mul(x = linear_150_cast_fp16, y = var_2324_to_fp16)[name = tensor<string, []>("tensor_155_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(497326848))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(498555712))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(498555904)))];
            tensor<fp16, [1, 77, 1280]> linear_151_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_151_cast_fp16)[name = tensor<string, []>("linear_151_cast_fp16")];
            tensor<int32, [4]> var_2329 = const()[name = tensor<string, []>("op_2329"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2330_cast_fp16 = reshape(shape = var_2329, x = linear_151_cast_fp16)[name = tensor<string, []>("op_2330_cast_fp16")];
            tensor<int32, [4]> var_2331_perm_0 = const()[name = tensor<string, []>("op_2331_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(498558528))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499787392))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499787584)))];
            tensor<fp16, [1, 77, 1280]> linear_152_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_151_cast_fp16)[name = tensor<string, []>("linear_152_cast_fp16")];
            tensor<int32, [4]> var_2336 = const()[name = tensor<string, []>("op_2336"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2337_cast_fp16 = reshape(shape = var_2336, x = linear_152_cast_fp16)[name = tensor<string, []>("op_2337_cast_fp16")];
            tensor<int32, [4]> var_2338_perm_0 = const()[name = tensor<string, []>("op_2338_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2345 = const()[name = tensor<string, []>("op_2345"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2346_cast_fp16 = reshape(shape = var_2345, x = tensor_155_cast_fp16)[name = tensor<string, []>("op_2346_cast_fp16")];
            tensor<int32, [4]> var_2347_perm_0 = const()[name = tensor<string, []>("op_2347_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2349 = const()[name = tensor<string, []>("op_2349"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2347_cast_fp16 = transpose(perm = var_2347_perm_0, x = var_2346_cast_fp16)[name = tensor<string, []>("transpose_27")];
            tensor<fp16, [20, 77, 64]> query_states_51_cast_fp16 = reshape(shape = var_2349, x = var_2347_cast_fp16)[name = tensor<string, []>("query_states_51_cast_fp16")];
            tensor<int32, [3]> var_2351 = const()[name = tensor<string, []>("op_2351"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2331_cast_fp16 = transpose(perm = var_2331_perm_0, x = var_2330_cast_fp16)[name = tensor<string, []>("transpose_26")];
            tensor<fp16, [20, 77, 64]> key_states_103_cast_fp16 = reshape(shape = var_2351, x = var_2331_cast_fp16)[name = tensor<string, []>("key_states_103_cast_fp16")];
            tensor<int32, [3]> var_2353 = const()[name = tensor<string, []>("op_2353"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2338_cast_fp16 = transpose(perm = var_2338_perm_0, x = var_2337_cast_fp16)[name = tensor<string, []>("transpose_25")];
            tensor<fp16, [20, 77, 64]> value_states_103_cast_fp16 = reshape(shape = var_2353, x = var_2338_cast_fp16)[name = tensor<string, []>("value_states_103_cast_fp16")];
            tensor<bool, []> attn_weights_151_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_151_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_151_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_151_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_151_cast_fp16 = matmul(transpose_x = attn_weights_151_transpose_x_1, transpose_y = attn_weights_151_transpose_y_1, x = query_states_51_cast_fp16, y = key_states_103_cast_fp16)[name = tensor<string, []>("attn_weights_151_cast_fp16")];
            tensor<int32, [4]> var_2358 = const()[name = tensor<string, []>("op_2358"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2359_cast_fp16 = reshape(shape = var_2358, x = attn_weights_151_cast_fp16)[name = tensor<string, []>("op_2359_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_153_cast_fp16 = add(x = var_2359_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_153_cast_fp16")];
            tensor<int32, [3]> var_2364 = const()[name = tensor<string, []>("op_2364"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_405_cast_fp16 = reshape(shape = var_2364, x = attn_weights_153_cast_fp16)[name = tensor<string, []>("input_405_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_407_cast_fp16 = softmax(axis = var_5, x = input_405_cast_fp16)[name = tensor<string, []>("input_407_cast_fp16")];
            tensor<bool, []> attn_output_151_transpose_x_0 = const()[name = tensor<string, []>("attn_output_151_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_151_transpose_y_0 = const()[name = tensor<string, []>("attn_output_151_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_151_cast_fp16 = matmul(transpose_x = attn_output_151_transpose_x_0, transpose_y = attn_output_151_transpose_y_0, x = input_407_cast_fp16, y = value_states_103_cast_fp16)[name = tensor<string, []>("attn_output_151_cast_fp16")];
            tensor<int32, [4]> var_2369 = const()[name = tensor<string, []>("op_2369"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_153_cast_fp16 = reshape(shape = var_2369, x = attn_output_151_cast_fp16)[name = tensor<string, []>("attn_output_153_cast_fp16")];
            tensor<int32, [4]> attn_output_155_perm_0 = const()[name = tensor<string, []>("attn_output_155_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2372 = const()[name = tensor<string, []>("op_2372"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_155_cast_fp16 = transpose(perm = attn_output_155_perm_0, x = attn_output_153_cast_fp16)[name = tensor<string, []>("transpose_24")];
            tensor<fp16, [1, 77, 1280]> input_409_cast_fp16 = reshape(shape = var_2372, x = attn_output_155_cast_fp16)[name = tensor<string, []>("input_409_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499790208))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(501019072))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(501019264)))];
            tensor<fp16, [1, 77, 1280]> linear_153_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized, x = input_409_cast_fp16)[name = tensor<string, []>("linear_153_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_411_cast_fp16 = add(x = input_403_cast_fp16, y = linear_153_cast_fp16)[name = tensor<string, []>("input_411_cast_fp16")];
            tensor<int32, [1]> input_413_axes_0 = const()[name = tensor<string, []>("input_413_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(501021888)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(501024512)))];
            tensor<fp16, [1, 77, 1280]> input_413_cast_fp16 = layer_norm(axes = input_413_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16, x = input_411_cast_fp16)[name = tensor<string, []>("input_413_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(501027136))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505942400))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505942592)))];
            tensor<fp16, [1, 77, 5120]> linear_154_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized, x = input_413_cast_fp16)[name = tensor<string, []>("linear_154_cast_fp16")];
            tensor<string, []> input_417_mode_0 = const()[name = tensor<string, []>("input_417_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_417_cast_fp16 = gelu(mode = input_417_mode_0, x = linear_154_cast_fp16)[name = tensor<string, []>("input_417_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505952896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510868160))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510868352)))];
            tensor<fp16, [1, 77, 1280]> linear_155_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized, x = input_417_cast_fp16)[name = tensor<string, []>("linear_155_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_419_cast_fp16 = add(x = input_411_cast_fp16, y = linear_155_cast_fp16)[name = tensor<string, []>("input_419_cast_fp16")];
            tensor<int32, [1]> hidden_states_157_axes_0 = const()[name = tensor<string, []>("hidden_states_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510870976)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510873600)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_157_cast_fp16 = layer_norm(axes = hidden_states_157_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16, x = input_419_cast_fp16)[name = tensor<string, []>("hidden_states_157_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510876224))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(512105088))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(512105280)))];
            tensor<fp16, [1, 77, 1280]> linear_156_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_157_cast_fp16)[name = tensor<string, []>("linear_156_cast_fp16")];
            tensor<fp16, []> var_2411_to_fp16 = const()[name = tensor<string, []>("op_2411_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_161_cast_fp16 = mul(x = linear_156_cast_fp16, y = var_2411_to_fp16)[name = tensor<string, []>("tensor_161_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(512107904))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(513336768))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(513336960)))];
            tensor<fp16, [1, 77, 1280]> linear_157_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_157_cast_fp16)[name = tensor<string, []>("linear_157_cast_fp16")];
            tensor<int32, [4]> var_2416 = const()[name = tensor<string, []>("op_2416"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2417_cast_fp16 = reshape(shape = var_2416, x = linear_157_cast_fp16)[name = tensor<string, []>("op_2417_cast_fp16")];
            tensor<int32, [4]> var_2418_perm_0 = const()[name = tensor<string, []>("op_2418_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(513339584))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(514568448))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(514568640)))];
            tensor<fp16, [1, 77, 1280]> linear_158_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_157_cast_fp16)[name = tensor<string, []>("linear_158_cast_fp16")];
            tensor<int32, [4]> var_2423 = const()[name = tensor<string, []>("op_2423"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2424_cast_fp16 = reshape(shape = var_2423, x = linear_158_cast_fp16)[name = tensor<string, []>("op_2424_cast_fp16")];
            tensor<int32, [4]> var_2425_perm_0 = const()[name = tensor<string, []>("op_2425_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2432 = const()[name = tensor<string, []>("op_2432"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2433_cast_fp16 = reshape(shape = var_2432, x = tensor_161_cast_fp16)[name = tensor<string, []>("op_2433_cast_fp16")];
            tensor<int32, [4]> var_2434_perm_0 = const()[name = tensor<string, []>("op_2434_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2436 = const()[name = tensor<string, []>("op_2436"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2434_cast_fp16 = transpose(perm = var_2434_perm_0, x = var_2433_cast_fp16)[name = tensor<string, []>("transpose_23")];
            tensor<fp16, [20, 77, 64]> query_states_53_cast_fp16 = reshape(shape = var_2436, x = var_2434_cast_fp16)[name = tensor<string, []>("query_states_53_cast_fp16")];
            tensor<int32, [3]> var_2438 = const()[name = tensor<string, []>("op_2438"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2418_cast_fp16 = transpose(perm = var_2418_perm_0, x = var_2417_cast_fp16)[name = tensor<string, []>("transpose_22")];
            tensor<fp16, [20, 77, 64]> key_states_107_cast_fp16 = reshape(shape = var_2438, x = var_2418_cast_fp16)[name = tensor<string, []>("key_states_107_cast_fp16")];
            tensor<int32, [3]> var_2440 = const()[name = tensor<string, []>("op_2440"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2425_cast_fp16 = transpose(perm = var_2425_perm_0, x = var_2424_cast_fp16)[name = tensor<string, []>("transpose_21")];
            tensor<fp16, [20, 77, 64]> value_states_107_cast_fp16 = reshape(shape = var_2440, x = var_2425_cast_fp16)[name = tensor<string, []>("value_states_107_cast_fp16")];
            tensor<bool, []> attn_weights_157_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_157_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_157_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_157_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_157_cast_fp16 = matmul(transpose_x = attn_weights_157_transpose_x_1, transpose_y = attn_weights_157_transpose_y_1, x = query_states_53_cast_fp16, y = key_states_107_cast_fp16)[name = tensor<string, []>("attn_weights_157_cast_fp16")];
            tensor<int32, [4]> var_2445 = const()[name = tensor<string, []>("op_2445"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2446_cast_fp16 = reshape(shape = var_2445, x = attn_weights_157_cast_fp16)[name = tensor<string, []>("op_2446_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_159_cast_fp16 = add(x = var_2446_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_159_cast_fp16")];
            tensor<int32, [3]> var_2451 = const()[name = tensor<string, []>("op_2451"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_421_cast_fp16 = reshape(shape = var_2451, x = attn_weights_159_cast_fp16)[name = tensor<string, []>("input_421_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_423_cast_fp16 = softmax(axis = var_5, x = input_421_cast_fp16)[name = tensor<string, []>("input_423_cast_fp16")];
            tensor<bool, []> attn_output_157_transpose_x_0 = const()[name = tensor<string, []>("attn_output_157_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_157_transpose_y_0 = const()[name = tensor<string, []>("attn_output_157_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_157_cast_fp16 = matmul(transpose_x = attn_output_157_transpose_x_0, transpose_y = attn_output_157_transpose_y_0, x = input_423_cast_fp16, y = value_states_107_cast_fp16)[name = tensor<string, []>("attn_output_157_cast_fp16")];
            tensor<int32, [4]> var_2456 = const()[name = tensor<string, []>("op_2456"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_159_cast_fp16 = reshape(shape = var_2456, x = attn_output_157_cast_fp16)[name = tensor<string, []>("attn_output_159_cast_fp16")];
            tensor<int32, [4]> attn_output_161_perm_0 = const()[name = tensor<string, []>("attn_output_161_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2459 = const()[name = tensor<string, []>("op_2459"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_161_cast_fp16 = transpose(perm = attn_output_161_perm_0, x = attn_output_159_cast_fp16)[name = tensor<string, []>("transpose_20")];
            tensor<fp16, [1, 77, 1280]> input_425_cast_fp16 = reshape(shape = var_2459, x = attn_output_161_cast_fp16)[name = tensor<string, []>("input_425_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(514571264))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515800128))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515800320)))];
            tensor<fp16, [1, 77, 1280]> linear_159_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized, x = input_425_cast_fp16)[name = tensor<string, []>("linear_159_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_427_cast_fp16 = add(x = input_419_cast_fp16, y = linear_159_cast_fp16)[name = tensor<string, []>("input_427_cast_fp16")];
            tensor<int32, [1]> input_429_axes_0 = const()[name = tensor<string, []>("input_429_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515802944)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515805568)))];
            tensor<fp16, [1, 77, 1280]> input_429_cast_fp16 = layer_norm(axes = input_429_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16, x = input_427_cast_fp16)[name = tensor<string, []>("input_429_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515808192))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520723456))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520723648)))];
            tensor<fp16, [1, 77, 5120]> linear_160_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized, x = input_429_cast_fp16)[name = tensor<string, []>("linear_160_cast_fp16")];
            tensor<string, []> input_433_mode_0 = const()[name = tensor<string, []>("input_433_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_433_cast_fp16 = gelu(mode = input_433_mode_0, x = linear_160_cast_fp16)[name = tensor<string, []>("input_433_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520733952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525649216))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525649408)))];
            tensor<fp16, [1, 77, 1280]> linear_161_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized, x = input_433_cast_fp16)[name = tensor<string, []>("linear_161_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_435_cast_fp16 = add(x = input_427_cast_fp16, y = linear_161_cast_fp16)[name = tensor<string, []>("input_435_cast_fp16")];
            tensor<int32, [1]> hidden_states_163_axes_0 = const()[name = tensor<string, []>("hidden_states_163_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525652032)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525654656)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_163_cast_fp16 = layer_norm(axes = hidden_states_163_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16, x = input_435_cast_fp16)[name = tensor<string, []>("hidden_states_163_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525657280))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526886144))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526886336)))];
            tensor<fp16, [1, 77, 1280]> linear_162_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_163_cast_fp16)[name = tensor<string, []>("linear_162_cast_fp16")];
            tensor<fp16, []> var_2498_to_fp16 = const()[name = tensor<string, []>("op_2498_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_167_cast_fp16 = mul(x = linear_162_cast_fp16, y = var_2498_to_fp16)[name = tensor<string, []>("tensor_167_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526888960))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(528117824))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(528118016)))];
            tensor<fp16, [1, 77, 1280]> linear_163_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_163_cast_fp16)[name = tensor<string, []>("linear_163_cast_fp16")];
            tensor<int32, [4]> var_2503 = const()[name = tensor<string, []>("op_2503"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2504_cast_fp16 = reshape(shape = var_2503, x = linear_163_cast_fp16)[name = tensor<string, []>("op_2504_cast_fp16")];
            tensor<int32, [4]> var_2505_perm_0 = const()[name = tensor<string, []>("op_2505_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(528120640))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529349504))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529349696)))];
            tensor<fp16, [1, 77, 1280]> linear_164_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_163_cast_fp16)[name = tensor<string, []>("linear_164_cast_fp16")];
            tensor<int32, [4]> var_2510 = const()[name = tensor<string, []>("op_2510"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2511_cast_fp16 = reshape(shape = var_2510, x = linear_164_cast_fp16)[name = tensor<string, []>("op_2511_cast_fp16")];
            tensor<int32, [4]> var_2512_perm_0 = const()[name = tensor<string, []>("op_2512_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2519 = const()[name = tensor<string, []>("op_2519"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2520_cast_fp16 = reshape(shape = var_2519, x = tensor_167_cast_fp16)[name = tensor<string, []>("op_2520_cast_fp16")];
            tensor<int32, [4]> var_2521_perm_0 = const()[name = tensor<string, []>("op_2521_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2523 = const()[name = tensor<string, []>("op_2523"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2521_cast_fp16 = transpose(perm = var_2521_perm_0, x = var_2520_cast_fp16)[name = tensor<string, []>("transpose_19")];
            tensor<fp16, [20, 77, 64]> query_states_55_cast_fp16 = reshape(shape = var_2523, x = var_2521_cast_fp16)[name = tensor<string, []>("query_states_55_cast_fp16")];
            tensor<int32, [3]> var_2525 = const()[name = tensor<string, []>("op_2525"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2505_cast_fp16 = transpose(perm = var_2505_perm_0, x = var_2504_cast_fp16)[name = tensor<string, []>("transpose_18")];
            tensor<fp16, [20, 77, 64]> key_states_111_cast_fp16 = reshape(shape = var_2525, x = var_2505_cast_fp16)[name = tensor<string, []>("key_states_111_cast_fp16")];
            tensor<int32, [3]> var_2527 = const()[name = tensor<string, []>("op_2527"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2512_cast_fp16 = transpose(perm = var_2512_perm_0, x = var_2511_cast_fp16)[name = tensor<string, []>("transpose_17")];
            tensor<fp16, [20, 77, 64]> value_states_111_cast_fp16 = reshape(shape = var_2527, x = var_2512_cast_fp16)[name = tensor<string, []>("value_states_111_cast_fp16")];
            tensor<bool, []> attn_weights_163_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_163_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_163_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_163_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_163_cast_fp16 = matmul(transpose_x = attn_weights_163_transpose_x_1, transpose_y = attn_weights_163_transpose_y_1, x = query_states_55_cast_fp16, y = key_states_111_cast_fp16)[name = tensor<string, []>("attn_weights_163_cast_fp16")];
            tensor<int32, [4]> var_2532 = const()[name = tensor<string, []>("op_2532"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2533_cast_fp16 = reshape(shape = var_2532, x = attn_weights_163_cast_fp16)[name = tensor<string, []>("op_2533_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_165_cast_fp16 = add(x = var_2533_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_165_cast_fp16")];
            tensor<int32, [3]> var_2538 = const()[name = tensor<string, []>("op_2538"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_437_cast_fp16 = reshape(shape = var_2538, x = attn_weights_165_cast_fp16)[name = tensor<string, []>("input_437_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_439_cast_fp16 = softmax(axis = var_5, x = input_437_cast_fp16)[name = tensor<string, []>("input_439_cast_fp16")];
            tensor<bool, []> attn_output_163_transpose_x_0 = const()[name = tensor<string, []>("attn_output_163_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_163_transpose_y_0 = const()[name = tensor<string, []>("attn_output_163_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_163_cast_fp16 = matmul(transpose_x = attn_output_163_transpose_x_0, transpose_y = attn_output_163_transpose_y_0, x = input_439_cast_fp16, y = value_states_111_cast_fp16)[name = tensor<string, []>("attn_output_163_cast_fp16")];
            tensor<int32, [4]> var_2543 = const()[name = tensor<string, []>("op_2543"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_165_cast_fp16 = reshape(shape = var_2543, x = attn_output_163_cast_fp16)[name = tensor<string, []>("attn_output_165_cast_fp16")];
            tensor<int32, [4]> attn_output_167_perm_0 = const()[name = tensor<string, []>("attn_output_167_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2546 = const()[name = tensor<string, []>("op_2546"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_167_cast_fp16 = transpose(perm = attn_output_167_perm_0, x = attn_output_165_cast_fp16)[name = tensor<string, []>("transpose_16")];
            tensor<fp16, [1, 77, 1280]> input_441_cast_fp16 = reshape(shape = var_2546, x = attn_output_167_cast_fp16)[name = tensor<string, []>("input_441_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529352320))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530581184))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530581376)))];
            tensor<fp16, [1, 77, 1280]> linear_165_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized, x = input_441_cast_fp16)[name = tensor<string, []>("linear_165_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_443_cast_fp16 = add(x = input_435_cast_fp16, y = linear_165_cast_fp16)[name = tensor<string, []>("input_443_cast_fp16")];
            tensor<int32, [1]> input_445_axes_0 = const()[name = tensor<string, []>("input_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530584000)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530586624)))];
            tensor<fp16, [1, 77, 1280]> input_445_cast_fp16 = layer_norm(axes = input_445_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16, x = input_443_cast_fp16)[name = tensor<string, []>("input_445_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530589248))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(535504512))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(535504704)))];
            tensor<fp16, [1, 77, 5120]> linear_166_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized, x = input_445_cast_fp16)[name = tensor<string, []>("linear_166_cast_fp16")];
            tensor<string, []> input_449_mode_0 = const()[name = tensor<string, []>("input_449_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_449_cast_fp16 = gelu(mode = input_449_mode_0, x = linear_166_cast_fp16)[name = tensor<string, []>("input_449_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(535515008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540430272))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540430464)))];
            tensor<fp16, [1, 77, 1280]> linear_167_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized, x = input_449_cast_fp16)[name = tensor<string, []>("linear_167_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_451_cast_fp16 = add(x = input_443_cast_fp16, y = linear_167_cast_fp16)[name = tensor<string, []>("input_451_cast_fp16")];
            tensor<int32, [1]> hidden_states_169_axes_0 = const()[name = tensor<string, []>("hidden_states_169_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540433088)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540435712)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_169_cast_fp16 = layer_norm(axes = hidden_states_169_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16, x = input_451_cast_fp16)[name = tensor<string, []>("hidden_states_169_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540438336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(541667200))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(541667392)))];
            tensor<fp16, [1, 77, 1280]> linear_168_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_169_cast_fp16)[name = tensor<string, []>("linear_168_cast_fp16")];
            tensor<fp16, []> var_2585_to_fp16 = const()[name = tensor<string, []>("op_2585_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_173_cast_fp16 = mul(x = linear_168_cast_fp16, y = var_2585_to_fp16)[name = tensor<string, []>("tensor_173_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(541670016))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(542898880))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(542899072)))];
            tensor<fp16, [1, 77, 1280]> linear_169_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_169_cast_fp16)[name = tensor<string, []>("linear_169_cast_fp16")];
            tensor<int32, [4]> var_2590 = const()[name = tensor<string, []>("op_2590"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2591_cast_fp16 = reshape(shape = var_2590, x = linear_169_cast_fp16)[name = tensor<string, []>("op_2591_cast_fp16")];
            tensor<int32, [4]> var_2592_perm_0 = const()[name = tensor<string, []>("op_2592_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(542901696))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(544130560))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(544130752)))];
            tensor<fp16, [1, 77, 1280]> linear_170_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_169_cast_fp16)[name = tensor<string, []>("linear_170_cast_fp16")];
            tensor<int32, [4]> var_2597 = const()[name = tensor<string, []>("op_2597"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2598_cast_fp16 = reshape(shape = var_2597, x = linear_170_cast_fp16)[name = tensor<string, []>("op_2598_cast_fp16")];
            tensor<int32, [4]> var_2599_perm_0 = const()[name = tensor<string, []>("op_2599_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2606 = const()[name = tensor<string, []>("op_2606"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2607_cast_fp16 = reshape(shape = var_2606, x = tensor_173_cast_fp16)[name = tensor<string, []>("op_2607_cast_fp16")];
            tensor<int32, [4]> var_2608_perm_0 = const()[name = tensor<string, []>("op_2608_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2610 = const()[name = tensor<string, []>("op_2610"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2608_cast_fp16 = transpose(perm = var_2608_perm_0, x = var_2607_cast_fp16)[name = tensor<string, []>("transpose_15")];
            tensor<fp16, [20, 77, 64]> query_states_57_cast_fp16 = reshape(shape = var_2610, x = var_2608_cast_fp16)[name = tensor<string, []>("query_states_57_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = tensor<string, []>("op_2612"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2592_cast_fp16 = transpose(perm = var_2592_perm_0, x = var_2591_cast_fp16)[name = tensor<string, []>("transpose_14")];
            tensor<fp16, [20, 77, 64]> key_states_115_cast_fp16 = reshape(shape = var_2612, x = var_2592_cast_fp16)[name = tensor<string, []>("key_states_115_cast_fp16")];
            tensor<int32, [3]> var_2614 = const()[name = tensor<string, []>("op_2614"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2599_cast_fp16 = transpose(perm = var_2599_perm_0, x = var_2598_cast_fp16)[name = tensor<string, []>("transpose_13")];
            tensor<fp16, [20, 77, 64]> value_states_115_cast_fp16 = reshape(shape = var_2614, x = var_2599_cast_fp16)[name = tensor<string, []>("value_states_115_cast_fp16")];
            tensor<bool, []> attn_weights_169_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_169_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_169_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_169_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_169_cast_fp16 = matmul(transpose_x = attn_weights_169_transpose_x_1, transpose_y = attn_weights_169_transpose_y_1, x = query_states_57_cast_fp16, y = key_states_115_cast_fp16)[name = tensor<string, []>("attn_weights_169_cast_fp16")];
            tensor<int32, [4]> var_2619 = const()[name = tensor<string, []>("op_2619"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2620_cast_fp16 = reshape(shape = var_2619, x = attn_weights_169_cast_fp16)[name = tensor<string, []>("op_2620_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_171_cast_fp16 = add(x = var_2620_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_171_cast_fp16")];
            tensor<int32, [3]> var_2625 = const()[name = tensor<string, []>("op_2625"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_453_cast_fp16 = reshape(shape = var_2625, x = attn_weights_171_cast_fp16)[name = tensor<string, []>("input_453_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_455_cast_fp16 = softmax(axis = var_5, x = input_453_cast_fp16)[name = tensor<string, []>("input_455_cast_fp16")];
            tensor<bool, []> attn_output_169_transpose_x_0 = const()[name = tensor<string, []>("attn_output_169_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_169_transpose_y_0 = const()[name = tensor<string, []>("attn_output_169_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_169_cast_fp16 = matmul(transpose_x = attn_output_169_transpose_x_0, transpose_y = attn_output_169_transpose_y_0, x = input_455_cast_fp16, y = value_states_115_cast_fp16)[name = tensor<string, []>("attn_output_169_cast_fp16")];
            tensor<int32, [4]> var_2630 = const()[name = tensor<string, []>("op_2630"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_171_cast_fp16 = reshape(shape = var_2630, x = attn_output_169_cast_fp16)[name = tensor<string, []>("attn_output_171_cast_fp16")];
            tensor<int32, [4]> attn_output_173_perm_0 = const()[name = tensor<string, []>("attn_output_173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2633 = const()[name = tensor<string, []>("op_2633"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_173_cast_fp16 = transpose(perm = attn_output_173_perm_0, x = attn_output_171_cast_fp16)[name = tensor<string, []>("transpose_12")];
            tensor<fp16, [1, 77, 1280]> input_457_cast_fp16 = reshape(shape = var_2633, x = attn_output_173_cast_fp16)[name = tensor<string, []>("input_457_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(544133376))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(545362240))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(545362432)))];
            tensor<fp16, [1, 77, 1280]> linear_171_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized, x = input_457_cast_fp16)[name = tensor<string, []>("linear_171_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_459_cast_fp16 = add(x = input_451_cast_fp16, y = linear_171_cast_fp16)[name = tensor<string, []>("input_459_cast_fp16")];
            tensor<int32, [1]> input_461_axes_0 = const()[name = tensor<string, []>("input_461_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(545365056)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(545367680)))];
            tensor<fp16, [1, 77, 1280]> input_461_cast_fp16 = layer_norm(axes = input_461_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16, x = input_459_cast_fp16)[name = tensor<string, []>("input_461_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(545370304))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(550285568))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(550285760)))];
            tensor<fp16, [1, 77, 5120]> linear_172_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized, x = input_461_cast_fp16)[name = tensor<string, []>("linear_172_cast_fp16")];
            tensor<string, []> input_465_mode_0 = const()[name = tensor<string, []>("input_465_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_465_cast_fp16 = gelu(mode = input_465_mode_0, x = linear_172_cast_fp16)[name = tensor<string, []>("input_465_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(550296064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(555211328))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(555211520)))];
            tensor<fp16, [1, 77, 1280]> linear_173_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized, x = input_465_cast_fp16)[name = tensor<string, []>("linear_173_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_467_cast_fp16 = add(x = input_459_cast_fp16, y = linear_173_cast_fp16)[name = tensor<string, []>("input_467_cast_fp16")];
            tensor<int32, [1]> hidden_states_175_axes_0 = const()[name = tensor<string, []>("hidden_states_175_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(555214144)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(555216768)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_175_cast_fp16 = layer_norm(axes = hidden_states_175_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16, x = input_467_cast_fp16)[name = tensor<string, []>("hidden_states_175_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(555219392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(556448256))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(556448448)))];
            tensor<fp16, [1, 77, 1280]> linear_174_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_175_cast_fp16)[name = tensor<string, []>("linear_174_cast_fp16")];
            tensor<fp16, []> var_2672_to_fp16 = const()[name = tensor<string, []>("op_2672_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_179_cast_fp16 = mul(x = linear_174_cast_fp16, y = var_2672_to_fp16)[name = tensor<string, []>("tensor_179_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(556451072))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(557679936))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(557680128)))];
            tensor<fp16, [1, 77, 1280]> linear_175_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_175_cast_fp16)[name = tensor<string, []>("linear_175_cast_fp16")];
            tensor<int32, [4]> var_2677 = const()[name = tensor<string, []>("op_2677"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2678_cast_fp16 = reshape(shape = var_2677, x = linear_175_cast_fp16)[name = tensor<string, []>("op_2678_cast_fp16")];
            tensor<int32, [4]> var_2679_perm_0 = const()[name = tensor<string, []>("op_2679_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(557682752))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(558911616))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(558911808)))];
            tensor<fp16, [1, 77, 1280]> linear_176_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_175_cast_fp16)[name = tensor<string, []>("linear_176_cast_fp16")];
            tensor<int32, [4]> var_2684 = const()[name = tensor<string, []>("op_2684"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2685_cast_fp16 = reshape(shape = var_2684, x = linear_176_cast_fp16)[name = tensor<string, []>("op_2685_cast_fp16")];
            tensor<int32, [4]> var_2686_perm_0 = const()[name = tensor<string, []>("op_2686_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2693 = const()[name = tensor<string, []>("op_2693"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2694_cast_fp16 = reshape(shape = var_2693, x = tensor_179_cast_fp16)[name = tensor<string, []>("op_2694_cast_fp16")];
            tensor<int32, [4]> var_2695_perm_0 = const()[name = tensor<string, []>("op_2695_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2697 = const()[name = tensor<string, []>("op_2697"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2695_cast_fp16 = transpose(perm = var_2695_perm_0, x = var_2694_cast_fp16)[name = tensor<string, []>("transpose_11")];
            tensor<fp16, [20, 77, 64]> query_states_59_cast_fp16 = reshape(shape = var_2697, x = var_2695_cast_fp16)[name = tensor<string, []>("query_states_59_cast_fp16")];
            tensor<int32, [3]> var_2699 = const()[name = tensor<string, []>("op_2699"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2679_cast_fp16 = transpose(perm = var_2679_perm_0, x = var_2678_cast_fp16)[name = tensor<string, []>("transpose_10")];
            tensor<fp16, [20, 77, 64]> key_states_119_cast_fp16 = reshape(shape = var_2699, x = var_2679_cast_fp16)[name = tensor<string, []>("key_states_119_cast_fp16")];
            tensor<int32, [3]> var_2701 = const()[name = tensor<string, []>("op_2701"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2686_cast_fp16 = transpose(perm = var_2686_perm_0, x = var_2685_cast_fp16)[name = tensor<string, []>("transpose_9")];
            tensor<fp16, [20, 77, 64]> value_states_119_cast_fp16 = reshape(shape = var_2701, x = var_2686_cast_fp16)[name = tensor<string, []>("value_states_119_cast_fp16")];
            tensor<bool, []> attn_weights_175_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_175_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_175_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_175_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_175_cast_fp16 = matmul(transpose_x = attn_weights_175_transpose_x_1, transpose_y = attn_weights_175_transpose_y_1, x = query_states_59_cast_fp16, y = key_states_119_cast_fp16)[name = tensor<string, []>("attn_weights_175_cast_fp16")];
            tensor<int32, [4]> var_2706 = const()[name = tensor<string, []>("op_2706"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2707_cast_fp16 = reshape(shape = var_2706, x = attn_weights_175_cast_fp16)[name = tensor<string, []>("op_2707_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_177_cast_fp16 = add(x = var_2707_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_177_cast_fp16")];
            tensor<int32, [3]> var_2712 = const()[name = tensor<string, []>("op_2712"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_469_cast_fp16 = reshape(shape = var_2712, x = attn_weights_177_cast_fp16)[name = tensor<string, []>("input_469_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_471_cast_fp16 = softmax(axis = var_5, x = input_469_cast_fp16)[name = tensor<string, []>("input_471_cast_fp16")];
            tensor<bool, []> attn_output_175_transpose_x_0 = const()[name = tensor<string, []>("attn_output_175_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_175_transpose_y_0 = const()[name = tensor<string, []>("attn_output_175_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_175_cast_fp16 = matmul(transpose_x = attn_output_175_transpose_x_0, transpose_y = attn_output_175_transpose_y_0, x = input_471_cast_fp16, y = value_states_119_cast_fp16)[name = tensor<string, []>("attn_output_175_cast_fp16")];
            tensor<int32, [4]> var_2717 = const()[name = tensor<string, []>("op_2717"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_177_cast_fp16 = reshape(shape = var_2717, x = attn_output_175_cast_fp16)[name = tensor<string, []>("attn_output_177_cast_fp16")];
            tensor<int32, [4]> attn_output_179_perm_0 = const()[name = tensor<string, []>("attn_output_179_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2720 = const()[name = tensor<string, []>("op_2720"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_179_cast_fp16 = transpose(perm = attn_output_179_perm_0, x = attn_output_177_cast_fp16)[name = tensor<string, []>("transpose_8")];
            tensor<fp16, [1, 77, 1280]> input_473_cast_fp16 = reshape(shape = var_2720, x = attn_output_179_cast_fp16)[name = tensor<string, []>("input_473_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(558914432))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(560143296))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(560143488)))];
            tensor<fp16, [1, 77, 1280]> linear_177_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized, x = input_473_cast_fp16)[name = tensor<string, []>("linear_177_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_475_cast_fp16 = add(x = input_467_cast_fp16, y = linear_177_cast_fp16)[name = tensor<string, []>("input_475_cast_fp16")];
            tensor<int32, [1]> input_477_axes_0 = const()[name = tensor<string, []>("input_477_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(560146112)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(560148736)))];
            tensor<fp16, [1, 77, 1280]> input_477_cast_fp16 = layer_norm(axes = input_477_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16, x = input_475_cast_fp16)[name = tensor<string, []>("input_477_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(560151360))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565066624))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565066816)))];
            tensor<fp16, [1, 77, 5120]> linear_178_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized, x = input_477_cast_fp16)[name = tensor<string, []>("linear_178_cast_fp16")];
            tensor<string, []> input_481_mode_0 = const()[name = tensor<string, []>("input_481_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_481_cast_fp16 = gelu(mode = input_481_mode_0, x = linear_178_cast_fp16)[name = tensor<string, []>("input_481_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565077120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569992384))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569992576)))];
            tensor<fp16, [1, 77, 1280]> linear_179_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized, x = input_481_cast_fp16)[name = tensor<string, []>("linear_179_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_483_cast_fp16 = add(x = input_475_cast_fp16, y = linear_179_cast_fp16)[name = tensor<string, []>("input_483_cast_fp16")];
            tensor<int32, [1]> hidden_states_181_axes_0 = const()[name = tensor<string, []>("hidden_states_181_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569995200)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569997824)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_181_cast_fp16 = layer_norm(axes = hidden_states_181_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16, x = input_483_cast_fp16)[name = tensor<string, []>("hidden_states_181_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(570000448))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571229312))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571229504)))];
            tensor<fp16, [1, 77, 1280]> linear_180_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_181_cast_fp16)[name = tensor<string, []>("linear_180_cast_fp16")];
            tensor<fp16, []> var_2759_to_fp16 = const()[name = tensor<string, []>("op_2759_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_185_cast_fp16 = mul(x = linear_180_cast_fp16, y = var_2759_to_fp16)[name = tensor<string, []>("tensor_185_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571232128))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572460992))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572461184)))];
            tensor<fp16, [1, 77, 1280]> linear_181_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_181_cast_fp16)[name = tensor<string, []>("linear_181_cast_fp16")];
            tensor<int32, [4]> var_2764 = const()[name = tensor<string, []>("op_2764"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2765_cast_fp16 = reshape(shape = var_2764, x = linear_181_cast_fp16)[name = tensor<string, []>("op_2765_cast_fp16")];
            tensor<int32, [4]> var_2766_perm_0 = const()[name = tensor<string, []>("op_2766_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572463808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(573692672))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(573692864)))];
            tensor<fp16, [1, 77, 1280]> linear_182_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_181_cast_fp16)[name = tensor<string, []>("linear_182_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = tensor<string, []>("op_2771"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2772_cast_fp16 = reshape(shape = var_2771, x = linear_182_cast_fp16)[name = tensor<string, []>("op_2772_cast_fp16")];
            tensor<int32, [4]> var_2773_perm_0 = const()[name = tensor<string, []>("op_2773_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2780 = const()[name = tensor<string, []>("op_2780"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2781_cast_fp16 = reshape(shape = var_2780, x = tensor_185_cast_fp16)[name = tensor<string, []>("op_2781_cast_fp16")];
            tensor<int32, [4]> var_2782_perm_0 = const()[name = tensor<string, []>("op_2782_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2784 = const()[name = tensor<string, []>("op_2784"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2782_cast_fp16 = transpose(perm = var_2782_perm_0, x = var_2781_cast_fp16)[name = tensor<string, []>("transpose_7")];
            tensor<fp16, [20, 77, 64]> query_states_61_cast_fp16 = reshape(shape = var_2784, x = var_2782_cast_fp16)[name = tensor<string, []>("query_states_61_cast_fp16")];
            tensor<int32, [3]> var_2786 = const()[name = tensor<string, []>("op_2786"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2766_cast_fp16 = transpose(perm = var_2766_perm_0, x = var_2765_cast_fp16)[name = tensor<string, []>("transpose_6")];
            tensor<fp16, [20, 77, 64]> key_states_123_cast_fp16 = reshape(shape = var_2786, x = var_2766_cast_fp16)[name = tensor<string, []>("key_states_123_cast_fp16")];
            tensor<int32, [3]> var_2788 = const()[name = tensor<string, []>("op_2788"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2773_cast_fp16 = transpose(perm = var_2773_perm_0, x = var_2772_cast_fp16)[name = tensor<string, []>("transpose_5")];
            tensor<fp16, [20, 77, 64]> value_states_123_cast_fp16 = reshape(shape = var_2788, x = var_2773_cast_fp16)[name = tensor<string, []>("value_states_123_cast_fp16")];
            tensor<bool, []> attn_weights_181_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_181_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_181_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_181_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_181_cast_fp16 = matmul(transpose_x = attn_weights_181_transpose_x_1, transpose_y = attn_weights_181_transpose_y_1, x = query_states_61_cast_fp16, y = key_states_123_cast_fp16)[name = tensor<string, []>("attn_weights_181_cast_fp16")];
            tensor<int32, [4]> var_2793 = const()[name = tensor<string, []>("op_2793"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2794_cast_fp16 = reshape(shape = var_2793, x = attn_weights_181_cast_fp16)[name = tensor<string, []>("op_2794_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_183_cast_fp16 = add(x = var_2794_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_183_cast_fp16")];
            tensor<int32, [3]> var_2799 = const()[name = tensor<string, []>("op_2799"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_485_cast_fp16 = reshape(shape = var_2799, x = attn_weights_183_cast_fp16)[name = tensor<string, []>("input_485_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_487_cast_fp16 = softmax(axis = var_5, x = input_485_cast_fp16)[name = tensor<string, []>("input_487_cast_fp16")];
            tensor<bool, []> attn_output_181_transpose_x_0 = const()[name = tensor<string, []>("attn_output_181_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_181_transpose_y_0 = const()[name = tensor<string, []>("attn_output_181_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_181_cast_fp16 = matmul(transpose_x = attn_output_181_transpose_x_0, transpose_y = attn_output_181_transpose_y_0, x = input_487_cast_fp16, y = value_states_123_cast_fp16)[name = tensor<string, []>("attn_output_181_cast_fp16")];
            tensor<int32, [4]> var_2804 = const()[name = tensor<string, []>("op_2804"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_183_cast_fp16 = reshape(shape = var_2804, x = attn_output_181_cast_fp16)[name = tensor<string, []>("attn_output_183_cast_fp16")];
            tensor<int32, [4]> attn_output_185_perm_0 = const()[name = tensor<string, []>("attn_output_185_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2807 = const()[name = tensor<string, []>("op_2807"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_185_cast_fp16 = transpose(perm = attn_output_185_perm_0, x = attn_output_183_cast_fp16)[name = tensor<string, []>("transpose_4")];
            tensor<fp16, [1, 77, 1280]> input_489_cast_fp16 = reshape(shape = var_2807, x = attn_output_185_cast_fp16)[name = tensor<string, []>("input_489_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(573695488))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574924352))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574924544)))];
            tensor<fp16, [1, 77, 1280]> linear_183_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized, x = input_489_cast_fp16)[name = tensor<string, []>("linear_183_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_491_cast_fp16 = add(x = input_483_cast_fp16, y = linear_183_cast_fp16)[name = tensor<string, []>("input_491_cast_fp16")];
            tensor<int32, [1]> input_493_axes_0 = const()[name = tensor<string, []>("input_493_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574927168)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574929792)))];
            tensor<fp16, [1, 77, 1280]> input_493_cast_fp16 = layer_norm(axes = input_493_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16, x = input_491_cast_fp16)[name = tensor<string, []>("input_493_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574932416))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(579847680))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(579847872)))];
            tensor<fp16, [1, 77, 5120]> linear_184_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized, x = input_493_cast_fp16)[name = tensor<string, []>("linear_184_cast_fp16")];
            tensor<string, []> input_497_mode_0 = const()[name = tensor<string, []>("input_497_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_497_cast_fp16 = gelu(mode = input_497_mode_0, x = linear_184_cast_fp16)[name = tensor<string, []>("input_497_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(579858176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(584773440))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(584773632)))];
            tensor<fp16, [1, 77, 1280]> linear_185_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized, x = input_497_cast_fp16)[name = tensor<string, []>("linear_185_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_499_cast_fp16 = add(x = input_491_cast_fp16, y = linear_185_cast_fp16)[name = tensor<string, []>("input_499_cast_fp16")];
            tensor<string, []> input_499_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("input_499_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<int32, [1]> hidden_states_187_axes_0 = const()[name = tensor<string, []>("hidden_states_187_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(584776256)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(584778880)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_187_cast_fp16 = layer_norm(axes = hidden_states_187_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16, x = input_499_cast_fp16)[name = tensor<string, []>("hidden_states_187_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(584781504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(586010368))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(586010560)))];
            tensor<fp16, [1, 77, 1280]> linear_186_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_187_cast_fp16)[name = tensor<string, []>("linear_186_cast_fp16")];
            tensor<fp16, []> var_2846_to_fp16 = const()[name = tensor<string, []>("op_2846_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_cast_fp16 = mul(x = linear_186_cast_fp16, y = var_2846_to_fp16)[name = tensor<string, []>("tensor_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(586013184))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(587242048))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(587242240)))];
            tensor<fp16, [1, 77, 1280]> linear_187_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_187_cast_fp16)[name = tensor<string, []>("linear_187_cast_fp16")];
            tensor<int32, [4]> var_2851 = const()[name = tensor<string, []>("op_2851"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2852_cast_fp16 = reshape(shape = var_2851, x = linear_187_cast_fp16)[name = tensor<string, []>("op_2852_cast_fp16")];
            tensor<int32, [4]> var_2853_perm_0 = const()[name = tensor<string, []>("op_2853_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(587244864))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(588473728))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(588473920)))];
            tensor<fp16, [1, 77, 1280]> linear_188_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_187_cast_fp16)[name = tensor<string, []>("linear_188_cast_fp16")];
            tensor<int32, [4]> var_2858 = const()[name = tensor<string, []>("op_2858"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2859_cast_fp16 = reshape(shape = var_2858, x = linear_188_cast_fp16)[name = tensor<string, []>("op_2859_cast_fp16")];
            tensor<int32, [4]> var_2860_perm_0 = const()[name = tensor<string, []>("op_2860_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2867 = const()[name = tensor<string, []>("op_2867"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2868_cast_fp16 = reshape(shape = var_2867, x = tensor_cast_fp16)[name = tensor<string, []>("op_2868_cast_fp16")];
            tensor<int32, [4]> var_2869_perm_0 = const()[name = tensor<string, []>("op_2869_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2871 = const()[name = tensor<string, []>("op_2871"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2869_cast_fp16 = transpose(perm = var_2869_perm_0, x = var_2868_cast_fp16)[name = tensor<string, []>("transpose_3")];
            tensor<fp16, [20, 77, 64]> query_states_cast_fp16 = reshape(shape = var_2871, x = var_2869_cast_fp16)[name = tensor<string, []>("query_states_cast_fp16")];
            tensor<int32, [3]> var_2873 = const()[name = tensor<string, []>("op_2873"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2853_cast_fp16 = transpose(perm = var_2853_perm_0, x = var_2852_cast_fp16)[name = tensor<string, []>("transpose_2")];
            tensor<fp16, [20, 77, 64]> key_states_cast_fp16 = reshape(shape = var_2873, x = var_2853_cast_fp16)[name = tensor<string, []>("key_states_cast_fp16")];
            tensor<int32, [3]> var_2875 = const()[name = tensor<string, []>("op_2875"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2860_cast_fp16 = transpose(perm = var_2860_perm_0, x = var_2859_cast_fp16)[name = tensor<string, []>("transpose_1")];
            tensor<fp16, [20, 77, 64]> value_states_cast_fp16 = reshape(shape = var_2875, x = var_2860_cast_fp16)[name = tensor<string, []>("value_states_cast_fp16")];
            tensor<bool, []> attn_weights_187_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_187_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_187_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_187_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_187_cast_fp16 = matmul(transpose_x = attn_weights_187_transpose_x_1, transpose_y = attn_weights_187_transpose_y_1, x = query_states_cast_fp16, y = key_states_cast_fp16)[name = tensor<string, []>("attn_weights_187_cast_fp16")];
            tensor<int32, [4]> var_2880 = const()[name = tensor<string, []>("op_2880"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2881_cast_fp16 = reshape(shape = var_2880, x = attn_weights_187_cast_fp16)[name = tensor<string, []>("op_2881_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_189_cast_fp16 = add(x = var_2881_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_189_cast_fp16")];
            tensor<int32, [3]> var_2886 = const()[name = tensor<string, []>("op_2886"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_501_cast_fp16 = reshape(shape = var_2886, x = attn_weights_189_cast_fp16)[name = tensor<string, []>("input_501_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_503_cast_fp16 = softmax(axis = var_5, x = input_501_cast_fp16)[name = tensor<string, []>("input_503_cast_fp16")];
            tensor<bool, []> attn_output_187_transpose_x_0 = const()[name = tensor<string, []>("attn_output_187_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_187_transpose_y_0 = const()[name = tensor<string, []>("attn_output_187_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_187_cast_fp16 = matmul(transpose_x = attn_output_187_transpose_x_0, transpose_y = attn_output_187_transpose_y_0, x = input_503_cast_fp16, y = value_states_cast_fp16)[name = tensor<string, []>("attn_output_187_cast_fp16")];
            tensor<int32, [4]> var_2891 = const()[name = tensor<string, []>("op_2891"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_189_cast_fp16 = reshape(shape = var_2891, x = attn_output_187_cast_fp16)[name = tensor<string, []>("attn_output_189_cast_fp16")];
            tensor<int32, [4]> attn_output_perm_0 = const()[name = tensor<string, []>("attn_output_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2894 = const()[name = tensor<string, []>("op_2894"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_cast_fp16 = transpose(perm = attn_output_perm_0, x = attn_output_189_cast_fp16)[name = tensor<string, []>("transpose_0")];
            tensor<fp16, [1, 77, 1280]> input_505_cast_fp16 = reshape(shape = var_2894, x = attn_output_cast_fp16)[name = tensor<string, []>("input_505_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(588476544))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589705408))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589705600)))];
            tensor<fp16, [1, 77, 1280]> linear_189_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized, x = input_505_cast_fp16)[name = tensor<string, []>("linear_189_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_507_cast_fp16 = add(x = input_499_cast_fp16, y = linear_189_cast_fp16)[name = tensor<string, []>("input_507_cast_fp16")];
            tensor<int32, [1]> input_509_axes_0 = const()[name = tensor<string, []>("input_509_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589708224)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589710848)))];
            tensor<fp16, [1, 77, 1280]> input_509_cast_fp16 = layer_norm(axes = input_509_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16, x = input_507_cast_fp16)[name = tensor<string, []>("input_509_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589713472))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(594628736))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(594628928)))];
            tensor<fp16, [1, 77, 5120]> linear_190_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized, x = input_509_cast_fp16)[name = tensor<string, []>("linear_190_cast_fp16")];
            tensor<string, []> input_513_mode_0 = const()[name = tensor<string, []>("input_513_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_513_cast_fp16 = gelu(mode = input_513_mode_0, x = linear_190_cast_fp16)[name = tensor<string, []>("input_513_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(594639232))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(599554496))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(599554688)))];
            tensor<fp16, [1, 77, 1280]> linear_191_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized, x = input_513_cast_fp16)[name = tensor<string, []>("linear_191_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_515_cast_fp16 = add(x = input_507_cast_fp16, y = linear_191_cast_fp16)[name = tensor<string, []>("input_515_cast_fp16")];
            tensor<int32, [1]> last_hidden_state_axes_0 = const()[name = tensor<string, []>("last_hidden_state_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(599557312)))];
            tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(599559936)))];
            tensor<fp16, [1, 77, 1280]> last_hidden_state_cast_fp16 = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_515_cast_fp16)[name = tensor<string, []>("last_hidden_state_cast_fp16")];
            tensor<int32, [1]> var_2922 = const()[name = tensor<string, []>("op_2922"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> var_2924 = reduce_argmax(axis = var_5, keep_dims = var_6, x = cast_1)[name = tensor<string, []>("op_2924")];
            tensor<int32, []> stack_0_axis_0 = const()[name = tensor<string, []>("stack_0_axis_0"), val = tensor<int32, []>(1)];
            tensor<int32, [1, 2]> stack_0 = stack(axis = stack_0_axis_0, values = (var_2922, var_2924))[name = tensor<string, []>("stack_0")];
            tensor<int32, []> input_transpose_batch_dims_0 = const()[name = tensor<string, []>("input_transpose_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [1, 1280]> input_transpose_cast_fp16 = gather_nd(batch_dims = input_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast_fp16)[name = tensor<string, []>("input_transpose_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_projection_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(599562560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(600791424))), name = tensor<string, []>("text_encoder_text_projection_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> linear_192_bias_0_to_fp16 = const()[name = tensor<string, []>("linear_192_bias_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(600791616)))];
            tensor<fp16, [1, 1280]> linear_192_cast_fp16 = linear(bias = linear_192_bias_0_to_fp16, weight = text_encoder_text_projection_weight_to_fp16_palettized, x = input_transpose_cast_fp16)[name = tensor<string, []>("linear_192_cast_fp16")];
            tensor<string, []> linear_192_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("linear_192_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 77, 1280]> hidden_embeds = cast(dtype = input_499_cast_fp16_to_fp32_dtype_0, x = input_499_cast_fp16)[name = tensor<string, []>("cast_0")];
            tensor<fp32, [1, 1280]> pooled_outputs = cast(dtype = linear_192_cast_fp16_to_fp32_dtype_0, x = linear_192_cast_fp16)[name = tensor<string, []>("cast_1")];
        } -> (hidden_embeds, pooled_outputs);
}