program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3304.5.2"}, {"coremlc-version", "3304.6.2"}})]
{
    func main<ios16>(tensor<fp16, [1]> adjustment, tensor<fp16, [1, 3, 224, 224]> clip_input, tensor<fp16, [1, 512, 512, 3]> images) {
            tensor<int32, []> var_10 = const()[name = tensor<string, []>("op_10"), val = tensor<int32, []>(-1)];
            tensor<int32, []> var_13 = const()[name = tensor<string, []>("op_13"), val = tensor<int32, []>(1)];
            tensor<int32, [2]> var_37 = const()[name = tensor<string, []>("op_37"), val = tensor<int32, [2]>([14, 14])];
            tensor<int32, [2]> var_39 = const()[name = tensor<string, []>("op_39"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> patch_embeds_1_pad_type_0 = const()[name = tensor<string, []>("patch_embeds_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> patch_embeds_1_pad_0 = const()[name = tensor<string, []>("patch_embeds_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1024, 3, 14, 14]> vision_model_vision_model_embeddings_patch_embedding_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [451584]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451712))), name = tensor<string, []>("vision_model_vision_model_embeddings_patch_embedding_weight_to_fp16_palettized"), shape = tensor<uint32, [4]>([1024, 3, 14, 14])];
            tensor<fp16, [1, 1024, 16, 16]> patch_embeds_1_cast = conv(dilations = var_39, groups = var_13, pad = patch_embeds_1_pad_0, pad_type = patch_embeds_1_pad_type_0, strides = var_37, weight = vision_model_vision_model_embeddings_patch_embedding_weight_to_fp16_palettized, x = clip_input)[name = tensor<string, []>("patch_embeds_1_cast")];
            tensor<int32, [3]> concat_0 = const()[name = tensor<string, []>("concat_0"), val = tensor<int32, [3]>([1, 1024, 256])];
            tensor<fp16, [1, 1024, 256]> var_42_cast = reshape(shape = concat_0, x = patch_embeds_1_cast)[name = tensor<string, []>("op_42_cast")];
            tensor<int32, [3]> patch_embeds_perm_0 = const()[name = tensor<string, []>("patch_embeds_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> embeddings_1_interleave_0 = const()[name = tensor<string, []>("embeddings_1_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 1, 1024]> expand_dims_0_to_fp16 = const()[name = tensor<string, []>("expand_dims_0_to_fp16"), val = tensor<fp16, [1, 1, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451904)))];
            tensor<fp16, [1, 256, 1024]> transpose_120 = transpose(perm = patch_embeds_perm_0, x = var_42_cast)[name = tensor<string, []>("transpose_120")];
            tensor<fp16, [1, 257, 1024]> embeddings_1_cast = concat(axis = var_13, interleave = embeddings_1_interleave_0, values = (expand_dims_0_to_fp16, transpose_120))[name = tensor<string, []>("embeddings_1_cast")];
            tensor<fp16, [1, 257, 1024]> op_49_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [197376]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454016))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651456))), name = tensor<string, []>("op_49_to_fp16_palettized"), shape = tensor<uint32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 1024]> input_5_cast = add(x = embeddings_1_cast, y = op_49_to_fp16_palettized)[name = tensor<string, []>("input_5_cast")];
            tensor<int32, [1]> input_7_axes_0 = const()[name = tensor<string, []>("input_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_pre_layrnorm_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_pre_layrnorm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651648)))];
            tensor<fp16, [1024]> vision_model_vision_model_pre_layrnorm_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_pre_layrnorm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(653760)))];
            tensor<fp16, []> var_19_to_fp16 = const()[name = tensor<string, []>("op_19_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 257, 1024]> input_7_cast = layer_norm(axes = input_7_axes_0, beta = vision_model_vision_model_pre_layrnorm_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_pre_layrnorm_weight_to_fp16, x = input_5_cast)[name = tensor<string, []>("input_7_cast")];
            tensor<int32, [1]> hidden_states_1_axes_0 = const()[name = tensor<string, []>("hidden_states_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(655872)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(657984)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_1_cast = layer_norm(axes = hidden_states_1_axes_0, beta = vision_model_vision_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_7_cast)[name = tensor<string, []>("hidden_states_1_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(660096))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1446592))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1446784)))];
            tensor<fp16, [1, 257, 1024]> var_121_cast = linear(bias = vision_model_vision_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor<string, []>("op_121_cast")];
            tensor<fp16, []> var_122_to_fp16 = const()[name = tensor<string, []>("op_122_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_5_cast = mul(x = var_121_cast, y = var_122_to_fp16)[name = tensor<string, []>("tensor_5_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1448896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2235392))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2235584)))];
            tensor<fp16, [1, 257, 1024]> tensor_1_cast = linear(bias = vision_model_vision_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_1_cast")];
            tensor<int32, [4]> var_127 = const()[name = tensor<string, []>("op_127"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_128_cast = reshape(shape = var_127, x = tensor_1_cast)[name = tensor<string, []>("op_128_cast")];
            tensor<int32, [4]> var_129_perm_0 = const()[name = tensor<string, []>("op_129_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2237696))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3024192))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3024384)))];
            tensor<fp16, [1, 257, 1024]> tensor_3_cast = linear(bias = vision_model_vision_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_3_cast")];
            tensor<int32, [4]> var_134 = const()[name = tensor<string, []>("op_134"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_135_cast = reshape(shape = var_134, x = tensor_3_cast)[name = tensor<string, []>("op_135_cast")];
            tensor<int32, [4]> var_136_perm_0 = const()[name = tensor<string, []>("op_136_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_143 = const()[name = tensor<string, []>("op_143"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_144_cast = reshape(shape = var_143, x = tensor_5_cast)[name = tensor<string, []>("op_144_cast")];
            tensor<int32, [4]> var_145_perm_0 = const()[name = tensor<string, []>("op_145_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_147 = const()[name = tensor<string, []>("op_147"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_119 = transpose(perm = var_145_perm_0, x = var_144_cast)[name = tensor<string, []>("transpose_119")];
            tensor<fp16, [16, 257, 64]> query_states_1_cast = reshape(shape = var_147, x = transpose_119)[name = tensor<string, []>("query_states_1_cast")];
            tensor<int32, [3]> var_149 = const()[name = tensor<string, []>("op_149"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_118 = transpose(perm = var_129_perm_0, x = var_128_cast)[name = tensor<string, []>("transpose_118")];
            tensor<fp16, [16, 257, 64]> key_states_3_cast = reshape(shape = var_149, x = transpose_118)[name = tensor<string, []>("key_states_3_cast")];
            tensor<int32, [3]> var_151 = const()[name = tensor<string, []>("op_151"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_117 = transpose(perm = var_136_perm_0, x = var_135_cast)[name = tensor<string, []>("transpose_117")];
            tensor<fp16, [16, 257, 64]> value_states_3_cast = reshape(shape = var_151, x = transpose_117)[name = tensor<string, []>("value_states_3_cast")];
            tensor<int32, [3]> var_153_perm_0 = const()[name = tensor<string, []>("op_153_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_1_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_1_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_116 = transpose(perm = var_153_perm_0, x = key_states_3_cast)[name = tensor<string, []>("transpose_116")];
            tensor<fp16, [16, 257, 257]> attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_116)[name = tensor<string, []>("attn_weights_1_cast")];
            tensor<fp16, [16, 257, 257]> input_9_cast = softmax(axis = var_10, x = attn_weights_1_cast)[name = tensor<string, []>("input_9_cast")];
            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, [16, 257, 64]> attn_output_1_cast = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_9_cast, y = value_states_3_cast)[name = tensor<string, []>("attn_output_1_cast")];
            tensor<int32, [4]> var_158 = const()[name = tensor<string, []>("op_158"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_3_cast = reshape(shape = var_158, x = attn_output_1_cast)[name = tensor<string, []>("attn_output_3_cast")];
            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_161 = const()[name = tensor<string, []>("op_161"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_115 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor<string, []>("transpose_115")];
            tensor<fp16, [1, 257, 1024]> input_11_cast = reshape(shape = var_161, x = transpose_115)[name = tensor<string, []>("input_11_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3026496))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3812992))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3813184)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_3_cast = linear(bias = vision_model_vision_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_11_cast)[name = tensor<string, []>("hidden_states_3_cast")];
            tensor<fp16, [1, 257, 1024]> input_13_cast = add(x = input_7_cast, y = hidden_states_3_cast)[name = tensor<string, []>("input_13_cast")];
            tensor<int32, [1]> input_15_axes_0 = const()[name = tensor<string, []>("input_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3815296)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3817408)))];
            tensor<fp16, [1, 257, 1024]> input_15_cast = layer_norm(axes = input_15_axes_0, beta = vision_model_vision_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_13_cast)[name = tensor<string, []>("input_15_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3819520))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6965312))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6965504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6968640))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_17_cast = linear(bias = vision_model_vision_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_15_cast)[name = tensor<string, []>("input_17_cast")];
            tensor<fp16, []> var_176_to_fp16 = const()[name = tensor<string, []>("op_176_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_177_cast = mul(x = input_17_cast, y = var_176_to_fp16)[name = tensor<string, []>("op_177_cast")];
            tensor<fp16, [1, 257, 4096]> var_178_cast = sigmoid(x = var_177_cast)[name = tensor<string, []>("op_178_cast")];
            tensor<fp16, [1, 257, 4096]> input_19_cast = mul(x = input_17_cast, y = var_178_cast)[name = tensor<string, []>("input_19_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6968832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10114624))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10114816)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_5_cast = linear(bias = vision_model_vision_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized, x = input_19_cast)[name = tensor<string, []>("hidden_states_5_cast")];
            tensor<fp16, [1, 257, 1024]> input_21_cast = add(x = input_13_cast, y = hidden_states_5_cast)[name = tensor<string, []>("input_21_cast")];
            tensor<int32, [1]> hidden_states_7_axes_0 = const()[name = tensor<string, []>("hidden_states_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10116928)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10119040)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_7_cast = layer_norm(axes = hidden_states_7_axes_0, beta = vision_model_vision_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_21_cast)[name = tensor<string, []>("hidden_states_7_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10121152))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10907648))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10907840)))];
            tensor<fp16, [1, 257, 1024]> var_202_cast = linear(bias = vision_model_vision_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor<string, []>("op_202_cast")];
            tensor<fp16, []> var_203_to_fp16 = const()[name = tensor<string, []>("op_203_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_11_cast = mul(x = var_202_cast, y = var_203_to_fp16)[name = tensor<string, []>("tensor_11_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10909952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11696448))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11696640)))];
            tensor<fp16, [1, 257, 1024]> tensor_7_cast = linear(bias = vision_model_vision_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_7_cast")];
            tensor<int32, [4]> var_208 = const()[name = tensor<string, []>("op_208"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_209_cast = reshape(shape = var_208, x = tensor_7_cast)[name = tensor<string, []>("op_209_cast")];
            tensor<int32, [4]> var_210_perm_0 = const()[name = tensor<string, []>("op_210_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11698752))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12485248))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12485440)))];
            tensor<fp16, [1, 257, 1024]> tensor_9_cast = linear(bias = vision_model_vision_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_9_cast")];
            tensor<int32, [4]> var_215 = const()[name = tensor<string, []>("op_215"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_216_cast = reshape(shape = var_215, x = tensor_9_cast)[name = tensor<string, []>("op_216_cast")];
            tensor<int32, [4]> var_217_perm_0 = const()[name = tensor<string, []>("op_217_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_224 = const()[name = tensor<string, []>("op_224"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_225_cast = reshape(shape = var_224, x = tensor_11_cast)[name = tensor<string, []>("op_225_cast")];
            tensor<int32, [4]> var_226_perm_0 = const()[name = tensor<string, []>("op_226_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_228 = const()[name = tensor<string, []>("op_228"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_114 = transpose(perm = var_226_perm_0, x = var_225_cast)[name = tensor<string, []>("transpose_114")];
            tensor<fp16, [16, 257, 64]> query_states_3_cast = reshape(shape = var_228, x = transpose_114)[name = tensor<string, []>("query_states_3_cast")];
            tensor<int32, [3]> var_230 = const()[name = tensor<string, []>("op_230"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_113 = transpose(perm = var_210_perm_0, x = var_209_cast)[name = tensor<string, []>("transpose_113")];
            tensor<fp16, [16, 257, 64]> key_states_7_cast = reshape(shape = var_230, x = transpose_113)[name = tensor<string, []>("key_states_7_cast")];
            tensor<int32, [3]> var_232 = const()[name = tensor<string, []>("op_232"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_112 = transpose(perm = var_217_perm_0, x = var_216_cast)[name = tensor<string, []>("transpose_112")];
            tensor<fp16, [16, 257, 64]> value_states_7_cast = reshape(shape = var_232, x = transpose_112)[name = tensor<string, []>("value_states_7_cast")];
            tensor<int32, [3]> var_234_perm_0 = const()[name = tensor<string, []>("op_234_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_5_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_5_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_5_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_5_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_111 = transpose(perm = var_234_perm_0, x = key_states_7_cast)[name = tensor<string, []>("transpose_111")];
            tensor<fp16, [16, 257, 257]> attn_weights_5_cast = matmul(transpose_x = attn_weights_5_transpose_x_0, transpose_y = attn_weights_5_transpose_y_0, x = query_states_3_cast, y = transpose_111)[name = tensor<string, []>("attn_weights_5_cast")];
            tensor<fp16, [16, 257, 257]> input_23_cast = softmax(axis = var_10, x = attn_weights_5_cast)[name = tensor<string, []>("input_23_cast")];
            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, [16, 257, 64]> attn_output_7_cast = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor<string, []>("attn_output_7_cast")];
            tensor<int32, [4]> var_239 = const()[name = tensor<string, []>("op_239"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_9_cast = reshape(shape = var_239, x = attn_output_7_cast)[name = tensor<string, []>("attn_output_9_cast")];
            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_242 = const()[name = tensor<string, []>("op_242"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_110 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor<string, []>("transpose_110")];
            tensor<fp16, [1, 257, 1024]> input_25_cast = reshape(shape = var_242, x = transpose_110)[name = tensor<string, []>("input_25_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12487552))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13274048))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13274240)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_9_cast = linear(bias = vision_model_vision_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast)[name = tensor<string, []>("hidden_states_9_cast")];
            tensor<fp16, [1, 257, 1024]> input_27_cast = add(x = input_21_cast, y = hidden_states_9_cast)[name = tensor<string, []>("input_27_cast")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = tensor<string, []>("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13276352)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13278464)))];
            tensor<fp16, [1, 257, 1024]> input_29_cast = layer_norm(axes = input_29_axes_0, beta = vision_model_vision_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast)[name = tensor<string, []>("input_29_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13280576))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16426368))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16426560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16429696))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_31_cast = linear(bias = vision_model_vision_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast)[name = tensor<string, []>("input_31_cast")];
            tensor<fp16, []> var_257_to_fp16 = const()[name = tensor<string, []>("op_257_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_258_cast = mul(x = input_31_cast, y = var_257_to_fp16)[name = tensor<string, []>("op_258_cast")];
            tensor<fp16, [1, 257, 4096]> var_259_cast = sigmoid(x = var_258_cast)[name = tensor<string, []>("op_259_cast")];
            tensor<fp16, [1, 257, 4096]> input_33_cast = mul(x = input_31_cast, y = var_259_cast)[name = tensor<string, []>("input_33_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16429888))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19575680))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19575872)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_11_cast = linear(bias = vision_model_vision_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized, x = input_33_cast)[name = tensor<string, []>("hidden_states_11_cast")];
            tensor<fp16, [1, 257, 1024]> input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor<string, []>("input_35_cast")];
            tensor<int32, [1]> hidden_states_13_axes_0 = const()[name = tensor<string, []>("hidden_states_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19577984)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19580096)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_13_cast = layer_norm(axes = hidden_states_13_axes_0, beta = vision_model_vision_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast)[name = tensor<string, []>("hidden_states_13_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19582208))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20368704))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20368896)))];
            tensor<fp16, [1, 257, 1024]> var_283_cast = linear(bias = vision_model_vision_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor<string, []>("op_283_cast")];
            tensor<fp16, []> var_284_to_fp16 = const()[name = tensor<string, []>("op_284_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_17_cast = mul(x = var_283_cast, y = var_284_to_fp16)[name = tensor<string, []>("tensor_17_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20371008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21157504))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21157696)))];
            tensor<fp16, [1, 257, 1024]> tensor_13_cast = linear(bias = vision_model_vision_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_13_cast")];
            tensor<int32, [4]> var_289 = const()[name = tensor<string, []>("op_289"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_290_cast = reshape(shape = var_289, x = tensor_13_cast)[name = tensor<string, []>("op_290_cast")];
            tensor<int32, [4]> var_291_perm_0 = const()[name = tensor<string, []>("op_291_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21159808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21946304))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21946496)))];
            tensor<fp16, [1, 257, 1024]> tensor_15_cast = linear(bias = vision_model_vision_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_15_cast")];
            tensor<int32, [4]> var_296 = const()[name = tensor<string, []>("op_296"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_297_cast = reshape(shape = var_296, x = tensor_15_cast)[name = tensor<string, []>("op_297_cast")];
            tensor<int32, [4]> var_298_perm_0 = const()[name = tensor<string, []>("op_298_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_305 = const()[name = tensor<string, []>("op_305"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_306_cast = reshape(shape = var_305, x = tensor_17_cast)[name = tensor<string, []>("op_306_cast")];
            tensor<int32, [4]> var_307_perm_0 = const()[name = tensor<string, []>("op_307_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_309 = const()[name = tensor<string, []>("op_309"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_109 = transpose(perm = var_307_perm_0, x = var_306_cast)[name = tensor<string, []>("transpose_109")];
            tensor<fp16, [16, 257, 64]> query_states_5_cast = reshape(shape = var_309, x = transpose_109)[name = tensor<string, []>("query_states_5_cast")];
            tensor<int32, [3]> var_311 = const()[name = tensor<string, []>("op_311"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_108 = transpose(perm = var_291_perm_0, x = var_290_cast)[name = tensor<string, []>("transpose_108")];
            tensor<fp16, [16, 257, 64]> key_states_11_cast = reshape(shape = var_311, x = transpose_108)[name = tensor<string, []>("key_states_11_cast")];
            tensor<int32, [3]> var_313 = const()[name = tensor<string, []>("op_313"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_107 = transpose(perm = var_298_perm_0, x = var_297_cast)[name = tensor<string, []>("transpose_107")];
            tensor<fp16, [16, 257, 64]> value_states_11_cast = reshape(shape = var_313, x = transpose_107)[name = tensor<string, []>("value_states_11_cast")];
            tensor<int32, [3]> var_315_perm_0 = const()[name = tensor<string, []>("op_315_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_9_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_9_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_9_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_9_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_106 = transpose(perm = var_315_perm_0, x = key_states_11_cast)[name = tensor<string, []>("transpose_106")];
            tensor<fp16, [16, 257, 257]> attn_weights_9_cast = matmul(transpose_x = attn_weights_9_transpose_x_0, transpose_y = attn_weights_9_transpose_y_0, x = query_states_5_cast, y = transpose_106)[name = tensor<string, []>("attn_weights_9_cast")];
            tensor<fp16, [16, 257, 257]> input_37_cast = softmax(axis = var_10, x = attn_weights_9_cast)[name = tensor<string, []>("input_37_cast")];
            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, [16, 257, 64]> attn_output_13_cast = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_37_cast, y = value_states_11_cast)[name = tensor<string, []>("attn_output_13_cast")];
            tensor<int32, [4]> var_320 = const()[name = tensor<string, []>("op_320"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_15_cast = reshape(shape = var_320, x = attn_output_13_cast)[name = tensor<string, []>("attn_output_15_cast")];
            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_323 = const()[name = tensor<string, []>("op_323"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_105 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor<string, []>("transpose_105")];
            tensor<fp16, [1, 257, 1024]> input_39_cast = reshape(shape = var_323, x = transpose_105)[name = tensor<string, []>("input_39_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21948608))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22735104))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22735296)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_15_cast = linear(bias = vision_model_vision_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_39_cast)[name = tensor<string, []>("hidden_states_15_cast")];
            tensor<fp16, [1, 257, 1024]> input_41_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor<string, []>("input_41_cast")];
            tensor<int32, [1]> input_43_axes_0 = const()[name = tensor<string, []>("input_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22737408)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22739520)))];
            tensor<fp16, [1, 257, 1024]> input_43_cast = layer_norm(axes = input_43_axes_0, beta = vision_model_vision_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_41_cast)[name = tensor<string, []>("input_43_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22741632))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25887424))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25887616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25890752))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_45_cast = linear(bias = vision_model_vision_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_43_cast)[name = tensor<string, []>("input_45_cast")];
            tensor<fp16, []> var_338_to_fp16 = const()[name = tensor<string, []>("op_338_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_339_cast = mul(x = input_45_cast, y = var_338_to_fp16)[name = tensor<string, []>("op_339_cast")];
            tensor<fp16, [1, 257, 4096]> var_340_cast = sigmoid(x = var_339_cast)[name = tensor<string, []>("op_340_cast")];
            tensor<fp16, [1, 257, 4096]> input_47_cast = mul(x = input_45_cast, y = var_340_cast)[name = tensor<string, []>("input_47_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25890944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29036736))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29036928)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_17_cast = linear(bias = vision_model_vision_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized, x = input_47_cast)[name = tensor<string, []>("hidden_states_17_cast")];
            tensor<fp16, [1, 257, 1024]> input_49_cast = add(x = input_41_cast, y = hidden_states_17_cast)[name = tensor<string, []>("input_49_cast")];
            tensor<int32, [1]> hidden_states_19_axes_0 = const()[name = tensor<string, []>("hidden_states_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29039040)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29041152)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_19_cast = layer_norm(axes = hidden_states_19_axes_0, beta = vision_model_vision_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_49_cast)[name = tensor<string, []>("hidden_states_19_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29043264))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29829760))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29829952)))];
            tensor<fp16, [1, 257, 1024]> var_364_cast = linear(bias = vision_model_vision_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor<string, []>("op_364_cast")];
            tensor<fp16, []> var_365_to_fp16 = const()[name = tensor<string, []>("op_365_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_23_cast = mul(x = var_364_cast, y = var_365_to_fp16)[name = tensor<string, []>("tensor_23_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29832064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30618560))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30618752)))];
            tensor<fp16, [1, 257, 1024]> tensor_19_cast = linear(bias = vision_model_vision_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_19_cast")];
            tensor<int32, [4]> var_370 = const()[name = tensor<string, []>("op_370"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_371_cast = reshape(shape = var_370, x = tensor_19_cast)[name = tensor<string, []>("op_371_cast")];
            tensor<int32, [4]> var_372_perm_0 = const()[name = tensor<string, []>("op_372_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30620864))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31407360))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31407552)))];
            tensor<fp16, [1, 257, 1024]> tensor_21_cast = linear(bias = vision_model_vision_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_21_cast")];
            tensor<int32, [4]> var_377 = const()[name = tensor<string, []>("op_377"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_378_cast = reshape(shape = var_377, x = tensor_21_cast)[name = tensor<string, []>("op_378_cast")];
            tensor<int32, [4]> var_379_perm_0 = const()[name = tensor<string, []>("op_379_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_386 = const()[name = tensor<string, []>("op_386"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_387_cast = reshape(shape = var_386, x = tensor_23_cast)[name = tensor<string, []>("op_387_cast")];
            tensor<int32, [4]> var_388_perm_0 = const()[name = tensor<string, []>("op_388_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_390 = const()[name = tensor<string, []>("op_390"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_104 = transpose(perm = var_388_perm_0, x = var_387_cast)[name = tensor<string, []>("transpose_104")];
            tensor<fp16, [16, 257, 64]> query_states_7_cast = reshape(shape = var_390, x = transpose_104)[name = tensor<string, []>("query_states_7_cast")];
            tensor<int32, [3]> var_392 = const()[name = tensor<string, []>("op_392"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_103 = transpose(perm = var_372_perm_0, x = var_371_cast)[name = tensor<string, []>("transpose_103")];
            tensor<fp16, [16, 257, 64]> key_states_15_cast = reshape(shape = var_392, x = transpose_103)[name = tensor<string, []>("key_states_15_cast")];
            tensor<int32, [3]> var_394 = const()[name = tensor<string, []>("op_394"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_102 = transpose(perm = var_379_perm_0, x = var_378_cast)[name = tensor<string, []>("transpose_102")];
            tensor<fp16, [16, 257, 64]> value_states_15_cast = reshape(shape = var_394, x = transpose_102)[name = tensor<string, []>("value_states_15_cast")];
            tensor<int32, [3]> var_396_perm_0 = const()[name = tensor<string, []>("op_396_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_13_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_13_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_101 = transpose(perm = var_396_perm_0, x = key_states_15_cast)[name = tensor<string, []>("transpose_101")];
            tensor<fp16, [16, 257, 257]> attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_7_cast, y = transpose_101)[name = tensor<string, []>("attn_weights_13_cast")];
            tensor<fp16, [16, 257, 257]> input_51_cast = softmax(axis = var_10, x = attn_weights_13_cast)[name = tensor<string, []>("input_51_cast")];
            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, [16, 257, 64]> attn_output_19_cast = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_51_cast, y = value_states_15_cast)[name = tensor<string, []>("attn_output_19_cast")];
            tensor<int32, [4]> var_401 = const()[name = tensor<string, []>("op_401"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_21_cast = reshape(shape = var_401, x = attn_output_19_cast)[name = tensor<string, []>("attn_output_21_cast")];
            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_404 = const()[name = tensor<string, []>("op_404"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_100 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor<string, []>("transpose_100")];
            tensor<fp16, [1, 257, 1024]> input_53_cast = reshape(shape = var_404, x = transpose_100)[name = tensor<string, []>("input_53_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31409664))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32196160))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32196352)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_21_cast = linear(bias = vision_model_vision_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_53_cast)[name = tensor<string, []>("hidden_states_21_cast")];
            tensor<fp16, [1, 257, 1024]> input_55_cast = add(x = input_49_cast, y = hidden_states_21_cast)[name = tensor<string, []>("input_55_cast")];
            tensor<int32, [1]> input_57_axes_0 = const()[name = tensor<string, []>("input_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32198464)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32200576)))];
            tensor<fp16, [1, 257, 1024]> input_57_cast = layer_norm(axes = input_57_axes_0, beta = vision_model_vision_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_55_cast)[name = tensor<string, []>("input_57_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32202688))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35348480))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35348672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35351808))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_59_cast = linear(bias = vision_model_vision_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_57_cast)[name = tensor<string, []>("input_59_cast")];
            tensor<fp16, []> var_419_to_fp16 = const()[name = tensor<string, []>("op_419_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_420_cast = mul(x = input_59_cast, y = var_419_to_fp16)[name = tensor<string, []>("op_420_cast")];
            tensor<fp16, [1, 257, 4096]> var_421_cast = sigmoid(x = var_420_cast)[name = tensor<string, []>("op_421_cast")];
            tensor<fp16, [1, 257, 4096]> input_61_cast = mul(x = input_59_cast, y = var_421_cast)[name = tensor<string, []>("input_61_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35352000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38497792))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38497984)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_23_cast = linear(bias = vision_model_vision_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized, x = input_61_cast)[name = tensor<string, []>("hidden_states_23_cast")];
            tensor<fp16, [1, 257, 1024]> input_63_cast = add(x = input_55_cast, y = hidden_states_23_cast)[name = tensor<string, []>("input_63_cast")];
            tensor<int32, [1]> hidden_states_25_axes_0 = const()[name = tensor<string, []>("hidden_states_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38500096)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38502208)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_25_cast = layer_norm(axes = hidden_states_25_axes_0, beta = vision_model_vision_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_63_cast)[name = tensor<string, []>("hidden_states_25_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38504320))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39290816))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39291008)))];
            tensor<fp16, [1, 257, 1024]> var_445_cast = linear(bias = vision_model_vision_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor<string, []>("op_445_cast")];
            tensor<fp16, []> var_446_to_fp16 = const()[name = tensor<string, []>("op_446_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_29_cast = mul(x = var_445_cast, y = var_446_to_fp16)[name = tensor<string, []>("tensor_29_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39293120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40079616))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40079808)))];
            tensor<fp16, [1, 257, 1024]> tensor_25_cast = linear(bias = vision_model_vision_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_25_cast")];
            tensor<int32, [4]> var_451 = const()[name = tensor<string, []>("op_451"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_452_cast = reshape(shape = var_451, x = tensor_25_cast)[name = tensor<string, []>("op_452_cast")];
            tensor<int32, [4]> var_453_perm_0 = const()[name = tensor<string, []>("op_453_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40081920))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40868416))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40868608)))];
            tensor<fp16, [1, 257, 1024]> tensor_27_cast = linear(bias = vision_model_vision_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_27_cast")];
            tensor<int32, [4]> var_458 = const()[name = tensor<string, []>("op_458"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_459_cast = reshape(shape = var_458, x = tensor_27_cast)[name = tensor<string, []>("op_459_cast")];
            tensor<int32, [4]> var_460_perm_0 = const()[name = tensor<string, []>("op_460_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_467 = const()[name = tensor<string, []>("op_467"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_468_cast = reshape(shape = var_467, x = tensor_29_cast)[name = tensor<string, []>("op_468_cast")];
            tensor<int32, [4]> var_469_perm_0 = const()[name = tensor<string, []>("op_469_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_471 = const()[name = tensor<string, []>("op_471"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_99 = transpose(perm = var_469_perm_0, x = var_468_cast)[name = tensor<string, []>("transpose_99")];
            tensor<fp16, [16, 257, 64]> query_states_9_cast = reshape(shape = var_471, x = transpose_99)[name = tensor<string, []>("query_states_9_cast")];
            tensor<int32, [3]> var_473 = const()[name = tensor<string, []>("op_473"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_98 = transpose(perm = var_453_perm_0, x = var_452_cast)[name = tensor<string, []>("transpose_98")];
            tensor<fp16, [16, 257, 64]> key_states_19_cast = reshape(shape = var_473, x = transpose_98)[name = tensor<string, []>("key_states_19_cast")];
            tensor<int32, [3]> var_475 = const()[name = tensor<string, []>("op_475"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_97 = transpose(perm = var_460_perm_0, x = var_459_cast)[name = tensor<string, []>("transpose_97")];
            tensor<fp16, [16, 257, 64]> value_states_19_cast = reshape(shape = var_475, x = transpose_97)[name = tensor<string, []>("value_states_19_cast")];
            tensor<int32, [3]> var_477_perm_0 = const()[name = tensor<string, []>("op_477_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_17_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_17_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_17_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_17_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_96 = transpose(perm = var_477_perm_0, x = key_states_19_cast)[name = tensor<string, []>("transpose_96")];
            tensor<fp16, [16, 257, 257]> attn_weights_17_cast = matmul(transpose_x = attn_weights_17_transpose_x_0, transpose_y = attn_weights_17_transpose_y_0, x = query_states_9_cast, y = transpose_96)[name = tensor<string, []>("attn_weights_17_cast")];
            tensor<fp16, [16, 257, 257]> input_65_cast = softmax(axis = var_10, x = attn_weights_17_cast)[name = tensor<string, []>("input_65_cast")];
            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, [16, 257, 64]> attn_output_25_cast = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_65_cast, y = value_states_19_cast)[name = tensor<string, []>("attn_output_25_cast")];
            tensor<int32, [4]> var_482 = const()[name = tensor<string, []>("op_482"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_27_cast = reshape(shape = var_482, x = attn_output_25_cast)[name = tensor<string, []>("attn_output_27_cast")];
            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_485 = const()[name = tensor<string, []>("op_485"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_95 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor<string, []>("transpose_95")];
            tensor<fp16, [1, 257, 1024]> input_67_cast = reshape(shape = var_485, x = transpose_95)[name = tensor<string, []>("input_67_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40870720))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41657216))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41657408)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_27_cast = linear(bias = vision_model_vision_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_67_cast)[name = tensor<string, []>("hidden_states_27_cast")];
            tensor<fp16, [1, 257, 1024]> input_69_cast = add(x = input_63_cast, y = hidden_states_27_cast)[name = tensor<string, []>("input_69_cast")];
            tensor<int32, [1]> input_71_axes_0 = const()[name = tensor<string, []>("input_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41659520)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41661632)))];
            tensor<fp16, [1, 257, 1024]> input_71_cast = layer_norm(axes = input_71_axes_0, beta = vision_model_vision_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_69_cast)[name = tensor<string, []>("input_71_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41663744))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44809536))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44809728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44812864))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_73_cast = linear(bias = vision_model_vision_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_71_cast)[name = tensor<string, []>("input_73_cast")];
            tensor<fp16, []> var_500_to_fp16 = const()[name = tensor<string, []>("op_500_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_501_cast = mul(x = input_73_cast, y = var_500_to_fp16)[name = tensor<string, []>("op_501_cast")];
            tensor<fp16, [1, 257, 4096]> var_502_cast = sigmoid(x = var_501_cast)[name = tensor<string, []>("op_502_cast")];
            tensor<fp16, [1, 257, 4096]> input_75_cast = mul(x = input_73_cast, y = var_502_cast)[name = tensor<string, []>("input_75_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44813056))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47958848))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47959040)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_29_cast = linear(bias = vision_model_vision_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized, x = input_75_cast)[name = tensor<string, []>("hidden_states_29_cast")];
            tensor<fp16, [1, 257, 1024]> input_77_cast = add(x = input_69_cast, y = hidden_states_29_cast)[name = tensor<string, []>("input_77_cast")];
            tensor<int32, [1]> hidden_states_31_axes_0 = const()[name = tensor<string, []>("hidden_states_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47961152)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47963264)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_31_cast = layer_norm(axes = hidden_states_31_axes_0, beta = vision_model_vision_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_77_cast)[name = tensor<string, []>("hidden_states_31_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47965376))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48751872))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48752064)))];
            tensor<fp16, [1, 257, 1024]> var_526_cast = linear(bias = vision_model_vision_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor<string, []>("op_526_cast")];
            tensor<fp16, []> var_527_to_fp16 = const()[name = tensor<string, []>("op_527_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_35_cast = mul(x = var_526_cast, y = var_527_to_fp16)[name = tensor<string, []>("tensor_35_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48754176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49540672))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49540864)))];
            tensor<fp16, [1, 257, 1024]> tensor_31_cast = linear(bias = vision_model_vision_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_31_cast")];
            tensor<int32, [4]> var_532 = const()[name = tensor<string, []>("op_532"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_533_cast = reshape(shape = var_532, x = tensor_31_cast)[name = tensor<string, []>("op_533_cast")];
            tensor<int32, [4]> var_534_perm_0 = const()[name = tensor<string, []>("op_534_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49542976))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50329472))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50329664)))];
            tensor<fp16, [1, 257, 1024]> tensor_33_cast = linear(bias = vision_model_vision_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_33_cast")];
            tensor<int32, [4]> var_539 = const()[name = tensor<string, []>("op_539"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_540_cast = reshape(shape = var_539, x = tensor_33_cast)[name = tensor<string, []>("op_540_cast")];
            tensor<int32, [4]> var_541_perm_0 = const()[name = tensor<string, []>("op_541_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_548 = const()[name = tensor<string, []>("op_548"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_549_cast = reshape(shape = var_548, x = tensor_35_cast)[name = tensor<string, []>("op_549_cast")];
            tensor<int32, [4]> var_550_perm_0 = const()[name = tensor<string, []>("op_550_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_552 = const()[name = tensor<string, []>("op_552"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_94 = transpose(perm = var_550_perm_0, x = var_549_cast)[name = tensor<string, []>("transpose_94")];
            tensor<fp16, [16, 257, 64]> query_states_11_cast = reshape(shape = var_552, x = transpose_94)[name = tensor<string, []>("query_states_11_cast")];
            tensor<int32, [3]> var_554 = const()[name = tensor<string, []>("op_554"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_93 = transpose(perm = var_534_perm_0, x = var_533_cast)[name = tensor<string, []>("transpose_93")];
            tensor<fp16, [16, 257, 64]> key_states_23_cast = reshape(shape = var_554, x = transpose_93)[name = tensor<string, []>("key_states_23_cast")];
            tensor<int32, [3]> var_556 = const()[name = tensor<string, []>("op_556"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_92 = transpose(perm = var_541_perm_0, x = var_540_cast)[name = tensor<string, []>("transpose_92")];
            tensor<fp16, [16, 257, 64]> value_states_23_cast = reshape(shape = var_556, x = transpose_92)[name = tensor<string, []>("value_states_23_cast")];
            tensor<int32, [3]> var_558_perm_0 = const()[name = tensor<string, []>("op_558_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_21_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_21_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_21_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_21_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_91 = transpose(perm = var_558_perm_0, x = key_states_23_cast)[name = tensor<string, []>("transpose_91")];
            tensor<fp16, [16, 257, 257]> attn_weights_21_cast = matmul(transpose_x = attn_weights_21_transpose_x_0, transpose_y = attn_weights_21_transpose_y_0, x = query_states_11_cast, y = transpose_91)[name = tensor<string, []>("attn_weights_21_cast")];
            tensor<fp16, [16, 257, 257]> input_79_cast = softmax(axis = var_10, x = attn_weights_21_cast)[name = tensor<string, []>("input_79_cast")];
            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, [16, 257, 64]> attn_output_31_cast = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_79_cast, y = value_states_23_cast)[name = tensor<string, []>("attn_output_31_cast")];
            tensor<int32, [4]> var_563 = const()[name = tensor<string, []>("op_563"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_33_cast = reshape(shape = var_563, x = attn_output_31_cast)[name = tensor<string, []>("attn_output_33_cast")];
            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_566 = const()[name = tensor<string, []>("op_566"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_90 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor<string, []>("transpose_90")];
            tensor<fp16, [1, 257, 1024]> input_81_cast = reshape(shape = var_566, x = transpose_90)[name = tensor<string, []>("input_81_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50331776))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51118272))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51118464)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_33_cast = linear(bias = vision_model_vision_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_81_cast)[name = tensor<string, []>("hidden_states_33_cast")];
            tensor<fp16, [1, 257, 1024]> input_83_cast = add(x = input_77_cast, y = hidden_states_33_cast)[name = tensor<string, []>("input_83_cast")];
            tensor<int32, [1]> input_85_axes_0 = const()[name = tensor<string, []>("input_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51120576)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51122688)))];
            tensor<fp16, [1, 257, 1024]> input_85_cast = layer_norm(axes = input_85_axes_0, beta = vision_model_vision_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_83_cast)[name = tensor<string, []>("input_85_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51124800))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54270592))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54270784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54273920))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_87_cast = linear(bias = vision_model_vision_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_85_cast)[name = tensor<string, []>("input_87_cast")];
            tensor<fp16, []> var_581_to_fp16 = const()[name = tensor<string, []>("op_581_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_582_cast = mul(x = input_87_cast, y = var_581_to_fp16)[name = tensor<string, []>("op_582_cast")];
            tensor<fp16, [1, 257, 4096]> var_583_cast = sigmoid(x = var_582_cast)[name = tensor<string, []>("op_583_cast")];
            tensor<fp16, [1, 257, 4096]> input_89_cast = mul(x = input_87_cast, y = var_583_cast)[name = tensor<string, []>("input_89_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(54274112))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57419904))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57420096)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_35_cast = linear(bias = vision_model_vision_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized, x = input_89_cast)[name = tensor<string, []>("hidden_states_35_cast")];
            tensor<fp16, [1, 257, 1024]> input_91_cast = add(x = input_83_cast, y = hidden_states_35_cast)[name = tensor<string, []>("input_91_cast")];
            tensor<int32, [1]> hidden_states_37_axes_0 = const()[name = tensor<string, []>("hidden_states_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57422208)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57424320)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_37_cast = layer_norm(axes = hidden_states_37_axes_0, beta = vision_model_vision_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_91_cast)[name = tensor<string, []>("hidden_states_37_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57426432))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58212928))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58213120)))];
            tensor<fp16, [1, 257, 1024]> var_607_cast = linear(bias = vision_model_vision_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor<string, []>("op_607_cast")];
            tensor<fp16, []> var_608_to_fp16 = const()[name = tensor<string, []>("op_608_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_41_cast = mul(x = var_607_cast, y = var_608_to_fp16)[name = tensor<string, []>("tensor_41_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58215232))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59001728))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59001920)))];
            tensor<fp16, [1, 257, 1024]> tensor_37_cast = linear(bias = vision_model_vision_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_37_cast")];
            tensor<int32, [4]> var_613 = const()[name = tensor<string, []>("op_613"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_614_cast = reshape(shape = var_613, x = tensor_37_cast)[name = tensor<string, []>("op_614_cast")];
            tensor<int32, [4]> var_615_perm_0 = const()[name = tensor<string, []>("op_615_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59004032))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59790528))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59790720)))];
            tensor<fp16, [1, 257, 1024]> tensor_39_cast = linear(bias = vision_model_vision_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_39_cast")];
            tensor<int32, [4]> var_620 = const()[name = tensor<string, []>("op_620"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_621_cast = reshape(shape = var_620, x = tensor_39_cast)[name = tensor<string, []>("op_621_cast")];
            tensor<int32, [4]> var_622_perm_0 = const()[name = tensor<string, []>("op_622_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_629 = const()[name = tensor<string, []>("op_629"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_630_cast = reshape(shape = var_629, x = tensor_41_cast)[name = tensor<string, []>("op_630_cast")];
            tensor<int32, [4]> var_631_perm_0 = const()[name = tensor<string, []>("op_631_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_633 = const()[name = tensor<string, []>("op_633"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_89 = transpose(perm = var_631_perm_0, x = var_630_cast)[name = tensor<string, []>("transpose_89")];
            tensor<fp16, [16, 257, 64]> query_states_13_cast = reshape(shape = var_633, x = transpose_89)[name = tensor<string, []>("query_states_13_cast")];
            tensor<int32, [3]> var_635 = const()[name = tensor<string, []>("op_635"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_88 = transpose(perm = var_615_perm_0, x = var_614_cast)[name = tensor<string, []>("transpose_88")];
            tensor<fp16, [16, 257, 64]> key_states_27_cast = reshape(shape = var_635, x = transpose_88)[name = tensor<string, []>("key_states_27_cast")];
            tensor<int32, [3]> var_637 = const()[name = tensor<string, []>("op_637"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_87 = transpose(perm = var_622_perm_0, x = var_621_cast)[name = tensor<string, []>("transpose_87")];
            tensor<fp16, [16, 257, 64]> value_states_27_cast = reshape(shape = var_637, x = transpose_87)[name = tensor<string, []>("value_states_27_cast")];
            tensor<int32, [3]> var_639_perm_0 = const()[name = tensor<string, []>("op_639_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_25_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_25_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_86 = transpose(perm = var_639_perm_0, x = key_states_27_cast)[name = tensor<string, []>("transpose_86")];
            tensor<fp16, [16, 257, 257]> attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_13_cast, y = transpose_86)[name = tensor<string, []>("attn_weights_25_cast")];
            tensor<fp16, [16, 257, 257]> input_93_cast = softmax(axis = var_10, x = attn_weights_25_cast)[name = tensor<string, []>("input_93_cast")];
            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, [16, 257, 64]> attn_output_37_cast = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_93_cast, y = value_states_27_cast)[name = tensor<string, []>("attn_output_37_cast")];
            tensor<int32, [4]> var_644 = const()[name = tensor<string, []>("op_644"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_39_cast = reshape(shape = var_644, x = attn_output_37_cast)[name = tensor<string, []>("attn_output_39_cast")];
            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_647 = const()[name = tensor<string, []>("op_647"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_85 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor<string, []>("transpose_85")];
            tensor<fp16, [1, 257, 1024]> input_95_cast = reshape(shape = var_647, x = transpose_85)[name = tensor<string, []>("input_95_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59792832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60579328))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60579520)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_39_cast = linear(bias = vision_model_vision_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_95_cast)[name = tensor<string, []>("hidden_states_39_cast")];
            tensor<fp16, [1, 257, 1024]> input_97_cast = add(x = input_91_cast, y = hidden_states_39_cast)[name = tensor<string, []>("input_97_cast")];
            tensor<int32, [1]> input_99_axes_0 = const()[name = tensor<string, []>("input_99_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60581632)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60583744)))];
            tensor<fp16, [1, 257, 1024]> input_99_cast = layer_norm(axes = input_99_axes_0, beta = vision_model_vision_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_97_cast)[name = tensor<string, []>("input_99_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60585856))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63731648))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63731840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63734976))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_101_cast = linear(bias = vision_model_vision_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_99_cast)[name = tensor<string, []>("input_101_cast")];
            tensor<fp16, []> var_662_to_fp16 = const()[name = tensor<string, []>("op_662_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_663_cast = mul(x = input_101_cast, y = var_662_to_fp16)[name = tensor<string, []>("op_663_cast")];
            tensor<fp16, [1, 257, 4096]> var_664_cast = sigmoid(x = var_663_cast)[name = tensor<string, []>("op_664_cast")];
            tensor<fp16, [1, 257, 4096]> input_103_cast = mul(x = input_101_cast, y = var_664_cast)[name = tensor<string, []>("input_103_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63735168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66880960))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66881152)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_41_cast = linear(bias = vision_model_vision_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized, x = input_103_cast)[name = tensor<string, []>("hidden_states_41_cast")];
            tensor<fp16, [1, 257, 1024]> input_105_cast = add(x = input_97_cast, y = hidden_states_41_cast)[name = tensor<string, []>("input_105_cast")];
            tensor<int32, [1]> hidden_states_43_axes_0 = const()[name = tensor<string, []>("hidden_states_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66883264)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66885376)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_43_cast = layer_norm(axes = hidden_states_43_axes_0, beta = vision_model_vision_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_105_cast)[name = tensor<string, []>("hidden_states_43_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66887488))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67673984))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67674176)))];
            tensor<fp16, [1, 257, 1024]> var_688_cast = linear(bias = vision_model_vision_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor<string, []>("op_688_cast")];
            tensor<fp16, []> var_689_to_fp16 = const()[name = tensor<string, []>("op_689_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_47_cast = mul(x = var_688_cast, y = var_689_to_fp16)[name = tensor<string, []>("tensor_47_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67676288))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68462784))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68462976)))];
            tensor<fp16, [1, 257, 1024]> tensor_43_cast = linear(bias = vision_model_vision_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_43_cast")];
            tensor<int32, [4]> var_694 = const()[name = tensor<string, []>("op_694"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_695_cast = reshape(shape = var_694, x = tensor_43_cast)[name = tensor<string, []>("op_695_cast")];
            tensor<int32, [4]> var_696_perm_0 = const()[name = tensor<string, []>("op_696_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68465088))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69251584))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69251776)))];
            tensor<fp16, [1, 257, 1024]> tensor_45_cast = linear(bias = vision_model_vision_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_45_cast")];
            tensor<int32, [4]> var_701 = const()[name = tensor<string, []>("op_701"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_702_cast = reshape(shape = var_701, x = tensor_45_cast)[name = tensor<string, []>("op_702_cast")];
            tensor<int32, [4]> var_703_perm_0 = const()[name = tensor<string, []>("op_703_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_710 = const()[name = tensor<string, []>("op_710"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_711_cast = reshape(shape = var_710, x = tensor_47_cast)[name = tensor<string, []>("op_711_cast")];
            tensor<int32, [4]> var_712_perm_0 = const()[name = tensor<string, []>("op_712_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_714 = const()[name = tensor<string, []>("op_714"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_84 = transpose(perm = var_712_perm_0, x = var_711_cast)[name = tensor<string, []>("transpose_84")];
            tensor<fp16, [16, 257, 64]> query_states_15_cast = reshape(shape = var_714, x = transpose_84)[name = tensor<string, []>("query_states_15_cast")];
            tensor<int32, [3]> var_716 = const()[name = tensor<string, []>("op_716"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_83 = transpose(perm = var_696_perm_0, x = var_695_cast)[name = tensor<string, []>("transpose_83")];
            tensor<fp16, [16, 257, 64]> key_states_31_cast = reshape(shape = var_716, x = transpose_83)[name = tensor<string, []>("key_states_31_cast")];
            tensor<int32, [3]> var_718 = const()[name = tensor<string, []>("op_718"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_82 = transpose(perm = var_703_perm_0, x = var_702_cast)[name = tensor<string, []>("transpose_82")];
            tensor<fp16, [16, 257, 64]> value_states_31_cast = reshape(shape = var_718, x = transpose_82)[name = tensor<string, []>("value_states_31_cast")];
            tensor<int32, [3]> var_720_perm_0 = const()[name = tensor<string, []>("op_720_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_29_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_29_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_29_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_29_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_81 = transpose(perm = var_720_perm_0, x = key_states_31_cast)[name = tensor<string, []>("transpose_81")];
            tensor<fp16, [16, 257, 257]> attn_weights_29_cast = matmul(transpose_x = attn_weights_29_transpose_x_0, transpose_y = attn_weights_29_transpose_y_0, x = query_states_15_cast, y = transpose_81)[name = tensor<string, []>("attn_weights_29_cast")];
            tensor<fp16, [16, 257, 257]> input_107_cast = softmax(axis = var_10, x = attn_weights_29_cast)[name = tensor<string, []>("input_107_cast")];
            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, [16, 257, 64]> attn_output_43_cast = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_107_cast, y = value_states_31_cast)[name = tensor<string, []>("attn_output_43_cast")];
            tensor<int32, [4]> var_725 = const()[name = tensor<string, []>("op_725"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_45_cast = reshape(shape = var_725, x = attn_output_43_cast)[name = tensor<string, []>("attn_output_45_cast")];
            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_728 = const()[name = tensor<string, []>("op_728"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_80 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor<string, []>("transpose_80")];
            tensor<fp16, [1, 257, 1024]> input_109_cast = reshape(shape = var_728, x = transpose_80)[name = tensor<string, []>("input_109_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69253888))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70040384))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70040576)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_45_cast = linear(bias = vision_model_vision_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_109_cast)[name = tensor<string, []>("hidden_states_45_cast")];
            tensor<fp16, [1, 257, 1024]> input_111_cast = add(x = input_105_cast, y = hidden_states_45_cast)[name = tensor<string, []>("input_111_cast")];
            tensor<int32, [1]> input_113_axes_0 = const()[name = tensor<string, []>("input_113_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70042688)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70044800)))];
            tensor<fp16, [1, 257, 1024]> input_113_cast = layer_norm(axes = input_113_axes_0, beta = vision_model_vision_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_111_cast)[name = tensor<string, []>("input_113_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70046912))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73192704))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73192896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73196032))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_115_cast = linear(bias = vision_model_vision_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_113_cast)[name = tensor<string, []>("input_115_cast")];
            tensor<fp16, []> var_743_to_fp16 = const()[name = tensor<string, []>("op_743_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_744_cast = mul(x = input_115_cast, y = var_743_to_fp16)[name = tensor<string, []>("op_744_cast")];
            tensor<fp16, [1, 257, 4096]> var_745_cast = sigmoid(x = var_744_cast)[name = tensor<string, []>("op_745_cast")];
            tensor<fp16, [1, 257, 4096]> input_117_cast = mul(x = input_115_cast, y = var_745_cast)[name = tensor<string, []>("input_117_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73196224))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76342016))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76342208)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_47_cast = linear(bias = vision_model_vision_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized, x = input_117_cast)[name = tensor<string, []>("hidden_states_47_cast")];
            tensor<fp16, [1, 257, 1024]> input_119_cast = add(x = input_111_cast, y = hidden_states_47_cast)[name = tensor<string, []>("input_119_cast")];
            tensor<int32, [1]> hidden_states_49_axes_0 = const()[name = tensor<string, []>("hidden_states_49_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76344320)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76346432)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_49_cast = layer_norm(axes = hidden_states_49_axes_0, beta = vision_model_vision_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_119_cast)[name = tensor<string, []>("hidden_states_49_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76348544))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77135040))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77135232)))];
            tensor<fp16, [1, 257, 1024]> var_769_cast = linear(bias = vision_model_vision_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor<string, []>("op_769_cast")];
            tensor<fp16, []> var_770_to_fp16 = const()[name = tensor<string, []>("op_770_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_53_cast = mul(x = var_769_cast, y = var_770_to_fp16)[name = tensor<string, []>("tensor_53_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77137344))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77923840))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77924032)))];
            tensor<fp16, [1, 257, 1024]> tensor_49_cast = linear(bias = vision_model_vision_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_49_cast")];
            tensor<int32, [4]> var_775 = const()[name = tensor<string, []>("op_775"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_776_cast = reshape(shape = var_775, x = tensor_49_cast)[name = tensor<string, []>("op_776_cast")];
            tensor<int32, [4]> var_777_perm_0 = const()[name = tensor<string, []>("op_777_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77926144))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78712640))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78712832)))];
            tensor<fp16, [1, 257, 1024]> tensor_51_cast = linear(bias = vision_model_vision_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_51_cast")];
            tensor<int32, [4]> var_782 = const()[name = tensor<string, []>("op_782"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_783_cast = reshape(shape = var_782, x = tensor_51_cast)[name = tensor<string, []>("op_783_cast")];
            tensor<int32, [4]> var_784_perm_0 = const()[name = tensor<string, []>("op_784_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_791 = const()[name = tensor<string, []>("op_791"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_792_cast = reshape(shape = var_791, x = tensor_53_cast)[name = tensor<string, []>("op_792_cast")];
            tensor<int32, [4]> var_793_perm_0 = const()[name = tensor<string, []>("op_793_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_795 = const()[name = tensor<string, []>("op_795"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_79 = transpose(perm = var_793_perm_0, x = var_792_cast)[name = tensor<string, []>("transpose_79")];
            tensor<fp16, [16, 257, 64]> query_states_17_cast = reshape(shape = var_795, x = transpose_79)[name = tensor<string, []>("query_states_17_cast")];
            tensor<int32, [3]> var_797 = const()[name = tensor<string, []>("op_797"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_78 = transpose(perm = var_777_perm_0, x = var_776_cast)[name = tensor<string, []>("transpose_78")];
            tensor<fp16, [16, 257, 64]> key_states_35_cast = reshape(shape = var_797, x = transpose_78)[name = tensor<string, []>("key_states_35_cast")];
            tensor<int32, [3]> var_799 = const()[name = tensor<string, []>("op_799"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_77 = transpose(perm = var_784_perm_0, x = var_783_cast)[name = tensor<string, []>("transpose_77")];
            tensor<fp16, [16, 257, 64]> value_states_35_cast = reshape(shape = var_799, x = transpose_77)[name = tensor<string, []>("value_states_35_cast")];
            tensor<int32, [3]> var_801_perm_0 = const()[name = tensor<string, []>("op_801_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_33_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_33_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_33_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_33_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_76 = transpose(perm = var_801_perm_0, x = key_states_35_cast)[name = tensor<string, []>("transpose_76")];
            tensor<fp16, [16, 257, 257]> attn_weights_33_cast = matmul(transpose_x = attn_weights_33_transpose_x_0, transpose_y = attn_weights_33_transpose_y_0, x = query_states_17_cast, y = transpose_76)[name = tensor<string, []>("attn_weights_33_cast")];
            tensor<fp16, [16, 257, 257]> input_121_cast = softmax(axis = var_10, x = attn_weights_33_cast)[name = tensor<string, []>("input_121_cast")];
            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, [16, 257, 64]> attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_121_cast, y = value_states_35_cast)[name = tensor<string, []>("attn_output_49_cast")];
            tensor<int32, [4]> var_806 = const()[name = tensor<string, []>("op_806"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_51_cast = reshape(shape = var_806, x = attn_output_49_cast)[name = tensor<string, []>("attn_output_51_cast")];
            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_809 = const()[name = tensor<string, []>("op_809"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_75 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor<string, []>("transpose_75")];
            tensor<fp16, [1, 257, 1024]> input_123_cast = reshape(shape = var_809, x = transpose_75)[name = tensor<string, []>("input_123_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78714944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79501440))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79501632)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_51_cast = linear(bias = vision_model_vision_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_123_cast)[name = tensor<string, []>("hidden_states_51_cast")];
            tensor<fp16, [1, 257, 1024]> input_125_cast = add(x = input_119_cast, y = hidden_states_51_cast)[name = tensor<string, []>("input_125_cast")];
            tensor<int32, [1]> input_127_axes_0 = const()[name = tensor<string, []>("input_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79503744)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79505856)))];
            tensor<fp16, [1, 257, 1024]> input_127_cast = layer_norm(axes = input_127_axes_0, beta = vision_model_vision_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_125_cast)[name = tensor<string, []>("input_127_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79507968))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82653760))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82653952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82657088))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_129_cast = linear(bias = vision_model_vision_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_127_cast)[name = tensor<string, []>("input_129_cast")];
            tensor<fp16, []> var_824_to_fp16 = const()[name = tensor<string, []>("op_824_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_825_cast = mul(x = input_129_cast, y = var_824_to_fp16)[name = tensor<string, []>("op_825_cast")];
            tensor<fp16, [1, 257, 4096]> var_826_cast = sigmoid(x = var_825_cast)[name = tensor<string, []>("op_826_cast")];
            tensor<fp16, [1, 257, 4096]> input_131_cast = mul(x = input_129_cast, y = var_826_cast)[name = tensor<string, []>("input_131_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82657280))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85803072))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85803264)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_53_cast = linear(bias = vision_model_vision_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized, x = input_131_cast)[name = tensor<string, []>("hidden_states_53_cast")];
            tensor<fp16, [1, 257, 1024]> input_133_cast = add(x = input_125_cast, y = hidden_states_53_cast)[name = tensor<string, []>("input_133_cast")];
            tensor<int32, [1]> hidden_states_55_axes_0 = const()[name = tensor<string, []>("hidden_states_55_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85805376)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85807488)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_55_cast = layer_norm(axes = hidden_states_55_axes_0, beta = vision_model_vision_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_133_cast)[name = tensor<string, []>("hidden_states_55_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85809600))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86596096))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86596288)))];
            tensor<fp16, [1, 257, 1024]> var_850_cast = linear(bias = vision_model_vision_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor<string, []>("op_850_cast")];
            tensor<fp16, []> var_851_to_fp16 = const()[name = tensor<string, []>("op_851_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_59_cast = mul(x = var_850_cast, y = var_851_to_fp16)[name = tensor<string, []>("tensor_59_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86598400))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87384896))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87385088)))];
            tensor<fp16, [1, 257, 1024]> tensor_55_cast = linear(bias = vision_model_vision_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_55_cast")];
            tensor<int32, [4]> var_856 = const()[name = tensor<string, []>("op_856"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_857_cast = reshape(shape = var_856, x = tensor_55_cast)[name = tensor<string, []>("op_857_cast")];
            tensor<int32, [4]> var_858_perm_0 = const()[name = tensor<string, []>("op_858_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87387200))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88173696))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88173888)))];
            tensor<fp16, [1, 257, 1024]> tensor_57_cast = linear(bias = vision_model_vision_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_57_cast")];
            tensor<int32, [4]> var_863 = const()[name = tensor<string, []>("op_863"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_864_cast = reshape(shape = var_863, x = tensor_57_cast)[name = tensor<string, []>("op_864_cast")];
            tensor<int32, [4]> var_865_perm_0 = const()[name = tensor<string, []>("op_865_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_872 = const()[name = tensor<string, []>("op_872"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_873_cast = reshape(shape = var_872, x = tensor_59_cast)[name = tensor<string, []>("op_873_cast")];
            tensor<int32, [4]> var_874_perm_0 = const()[name = tensor<string, []>("op_874_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_876 = const()[name = tensor<string, []>("op_876"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_74 = transpose(perm = var_874_perm_0, x = var_873_cast)[name = tensor<string, []>("transpose_74")];
            tensor<fp16, [16, 257, 64]> query_states_19_cast = reshape(shape = var_876, x = transpose_74)[name = tensor<string, []>("query_states_19_cast")];
            tensor<int32, [3]> var_878 = const()[name = tensor<string, []>("op_878"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_73 = transpose(perm = var_858_perm_0, x = var_857_cast)[name = tensor<string, []>("transpose_73")];
            tensor<fp16, [16, 257, 64]> key_states_39_cast = reshape(shape = var_878, x = transpose_73)[name = tensor<string, []>("key_states_39_cast")];
            tensor<int32, [3]> var_880 = const()[name = tensor<string, []>("op_880"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_72 = transpose(perm = var_865_perm_0, x = var_864_cast)[name = tensor<string, []>("transpose_72")];
            tensor<fp16, [16, 257, 64]> value_states_39_cast = reshape(shape = var_880, x = transpose_72)[name = tensor<string, []>("value_states_39_cast")];
            tensor<int32, [3]> var_882_perm_0 = const()[name = tensor<string, []>("op_882_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_37_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_37_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_71 = transpose(perm = var_882_perm_0, x = key_states_39_cast)[name = tensor<string, []>("transpose_71")];
            tensor<fp16, [16, 257, 257]> attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_19_cast, y = transpose_71)[name = tensor<string, []>("attn_weights_37_cast")];
            tensor<fp16, [16, 257, 257]> input_135_cast = softmax(axis = var_10, x = attn_weights_37_cast)[name = tensor<string, []>("input_135_cast")];
            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, [16, 257, 64]> attn_output_55_cast = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_135_cast, y = value_states_39_cast)[name = tensor<string, []>("attn_output_55_cast")];
            tensor<int32, [4]> var_887 = const()[name = tensor<string, []>("op_887"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_57_cast = reshape(shape = var_887, x = attn_output_55_cast)[name = tensor<string, []>("attn_output_57_cast")];
            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_890 = const()[name = tensor<string, []>("op_890"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_70 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor<string, []>("transpose_70")];
            tensor<fp16, [1, 257, 1024]> input_137_cast = reshape(shape = var_890, x = transpose_70)[name = tensor<string, []>("input_137_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88176000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88962496))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88962688)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_57_cast = linear(bias = vision_model_vision_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_137_cast)[name = tensor<string, []>("hidden_states_57_cast")];
            tensor<fp16, [1, 257, 1024]> input_139_cast = add(x = input_133_cast, y = hidden_states_57_cast)[name = tensor<string, []>("input_139_cast")];
            tensor<int32, [1]> input_141_axes_0 = const()[name = tensor<string, []>("input_141_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88964800)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88966912)))];
            tensor<fp16, [1, 257, 1024]> input_141_cast = layer_norm(axes = input_141_axes_0, beta = vision_model_vision_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_139_cast)[name = tensor<string, []>("input_141_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88969024))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92114816))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92115008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92118144))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_143_cast = linear(bias = vision_model_vision_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast)[name = tensor<string, []>("input_143_cast")];
            tensor<fp16, []> var_905_to_fp16 = const()[name = tensor<string, []>("op_905_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_906_cast = mul(x = input_143_cast, y = var_905_to_fp16)[name = tensor<string, []>("op_906_cast")];
            tensor<fp16, [1, 257, 4096]> var_907_cast = sigmoid(x = var_906_cast)[name = tensor<string, []>("op_907_cast")];
            tensor<fp16, [1, 257, 4096]> input_145_cast = mul(x = input_143_cast, y = var_907_cast)[name = tensor<string, []>("input_145_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92118336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95264128))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95264320)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_59_cast = linear(bias = vision_model_vision_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized, x = input_145_cast)[name = tensor<string, []>("hidden_states_59_cast")];
            tensor<fp16, [1, 257, 1024]> input_147_cast = add(x = input_139_cast, y = hidden_states_59_cast)[name = tensor<string, []>("input_147_cast")];
            tensor<int32, [1]> hidden_states_61_axes_0 = const()[name = tensor<string, []>("hidden_states_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95266432)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95268544)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_61_cast = layer_norm(axes = hidden_states_61_axes_0, beta = vision_model_vision_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_147_cast)[name = tensor<string, []>("hidden_states_61_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95270656))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96057152))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96057344)))];
            tensor<fp16, [1, 257, 1024]> var_931_cast = linear(bias = vision_model_vision_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor<string, []>("op_931_cast")];
            tensor<fp16, []> var_932_to_fp16 = const()[name = tensor<string, []>("op_932_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_65_cast = mul(x = var_931_cast, y = var_932_to_fp16)[name = tensor<string, []>("tensor_65_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96059456))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96845952))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96846144)))];
            tensor<fp16, [1, 257, 1024]> tensor_61_cast = linear(bias = vision_model_vision_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_61_cast")];
            tensor<int32, [4]> var_937 = const()[name = tensor<string, []>("op_937"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_938_cast = reshape(shape = var_937, x = tensor_61_cast)[name = tensor<string, []>("op_938_cast")];
            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, [1024, 1024]> vision_model_vision_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96848256))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97634752))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97634944)))];
            tensor<fp16, [1, 257, 1024]> tensor_63_cast = linear(bias = vision_model_vision_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_63_cast")];
            tensor<int32, [4]> var_944 = const()[name = tensor<string, []>("op_944"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_945_cast = reshape(shape = var_944, x = tensor_63_cast)[name = tensor<string, []>("op_945_cast")];
            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, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_954_cast = reshape(shape = var_953, x = tensor_65_cast)[name = tensor<string, []>("op_954_cast")];
            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]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_69 = transpose(perm = var_955_perm_0, x = var_954_cast)[name = tensor<string, []>("transpose_69")];
            tensor<fp16, [16, 257, 64]> query_states_21_cast = reshape(shape = var_957, x = transpose_69)[name = tensor<string, []>("query_states_21_cast")];
            tensor<int32, [3]> var_959 = const()[name = tensor<string, []>("op_959"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_68 = transpose(perm = var_939_perm_0, x = var_938_cast)[name = tensor<string, []>("transpose_68")];
            tensor<fp16, [16, 257, 64]> key_states_43_cast = reshape(shape = var_959, x = transpose_68)[name = tensor<string, []>("key_states_43_cast")];
            tensor<int32, [3]> var_961 = const()[name = tensor<string, []>("op_961"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_67 = transpose(perm = var_946_perm_0, x = var_945_cast)[name = tensor<string, []>("transpose_67")];
            tensor<fp16, [16, 257, 64]> value_states_43_cast = reshape(shape = var_961, x = transpose_67)[name = tensor<string, []>("value_states_43_cast")];
            tensor<int32, [3]> var_963_perm_0 = const()[name = tensor<string, []>("op_963_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_41_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_41_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_41_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_41_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_66 = transpose(perm = var_963_perm_0, x = key_states_43_cast)[name = tensor<string, []>("transpose_66")];
            tensor<fp16, [16, 257, 257]> attn_weights_41_cast = matmul(transpose_x = attn_weights_41_transpose_x_0, transpose_y = attn_weights_41_transpose_y_0, x = query_states_21_cast, y = transpose_66)[name = tensor<string, []>("attn_weights_41_cast")];
            tensor<fp16, [16, 257, 257]> input_149_cast = softmax(axis = var_10, x = attn_weights_41_cast)[name = tensor<string, []>("input_149_cast")];
            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, [16, 257, 64]> attn_output_61_cast = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_149_cast, y = value_states_43_cast)[name = tensor<string, []>("attn_output_61_cast")];
            tensor<int32, [4]> var_968 = const()[name = tensor<string, []>("op_968"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_63_cast = reshape(shape = var_968, x = attn_output_61_cast)[name = tensor<string, []>("attn_output_63_cast")];
            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_971 = const()[name = tensor<string, []>("op_971"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_65 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor<string, []>("transpose_65")];
            tensor<fp16, [1, 257, 1024]> input_151_cast = reshape(shape = var_971, x = transpose_65)[name = tensor<string, []>("input_151_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97637056))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98423552))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98423744)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_63_cast = linear(bias = vision_model_vision_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_151_cast)[name = tensor<string, []>("hidden_states_63_cast")];
            tensor<fp16, [1, 257, 1024]> input_153_cast = add(x = input_147_cast, y = hidden_states_63_cast)[name = tensor<string, []>("input_153_cast")];
            tensor<int32, [1]> input_155_axes_0 = const()[name = tensor<string, []>("input_155_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98425856)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98427968)))];
            tensor<fp16, [1, 257, 1024]> input_155_cast = layer_norm(axes = input_155_axes_0, beta = vision_model_vision_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_153_cast)[name = tensor<string, []>("input_155_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98430080))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101575872))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101576064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101579200))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_157_cast = linear(bias = vision_model_vision_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_155_cast)[name = tensor<string, []>("input_157_cast")];
            tensor<fp16, []> var_986_to_fp16 = const()[name = tensor<string, []>("op_986_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_987_cast = mul(x = input_157_cast, y = var_986_to_fp16)[name = tensor<string, []>("op_987_cast")];
            tensor<fp16, [1, 257, 4096]> var_988_cast = sigmoid(x = var_987_cast)[name = tensor<string, []>("op_988_cast")];
            tensor<fp16, [1, 257, 4096]> input_159_cast = mul(x = input_157_cast, y = var_988_cast)[name = tensor<string, []>("input_159_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101579392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104725184))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104725376)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_65_cast = linear(bias = vision_model_vision_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized, x = input_159_cast)[name = tensor<string, []>("hidden_states_65_cast")];
            tensor<fp16, [1, 257, 1024]> input_161_cast = add(x = input_153_cast, y = hidden_states_65_cast)[name = tensor<string, []>("input_161_cast")];
            tensor<int32, [1]> hidden_states_67_axes_0 = const()[name = tensor<string, []>("hidden_states_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104727488)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104729600)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_67_cast = layer_norm(axes = hidden_states_67_axes_0, beta = vision_model_vision_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_161_cast)[name = tensor<string, []>("hidden_states_67_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(104731712))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105518208))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105518400)))];
            tensor<fp16, [1, 257, 1024]> var_1012_cast = linear(bias = vision_model_vision_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor<string, []>("op_1012_cast")];
            tensor<fp16, []> var_1013_to_fp16 = const()[name = tensor<string, []>("op_1013_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_71_cast = mul(x = var_1012_cast, y = var_1013_to_fp16)[name = tensor<string, []>("tensor_71_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105520512))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106307008))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106307200)))];
            tensor<fp16, [1, 257, 1024]> tensor_67_cast = linear(bias = vision_model_vision_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_67_cast")];
            tensor<int32, [4]> var_1018 = const()[name = tensor<string, []>("op_1018"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1019_cast = reshape(shape = var_1018, x = tensor_67_cast)[name = tensor<string, []>("op_1019_cast")];
            tensor<int32, [4]> var_1020_perm_0 = const()[name = tensor<string, []>("op_1020_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106309312))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107095808))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107096000)))];
            tensor<fp16, [1, 257, 1024]> tensor_69_cast = linear(bias = vision_model_vision_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_69_cast")];
            tensor<int32, [4]> var_1025 = const()[name = tensor<string, []>("op_1025"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1026_cast = reshape(shape = var_1025, x = tensor_69_cast)[name = tensor<string, []>("op_1026_cast")];
            tensor<int32, [4]> var_1027_perm_0 = const()[name = tensor<string, []>("op_1027_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1034 = const()[name = tensor<string, []>("op_1034"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1035_cast = reshape(shape = var_1034, x = tensor_71_cast)[name = tensor<string, []>("op_1035_cast")];
            tensor<int32, [4]> var_1036_perm_0 = const()[name = tensor<string, []>("op_1036_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1038 = const()[name = tensor<string, []>("op_1038"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_64 = transpose(perm = var_1036_perm_0, x = var_1035_cast)[name = tensor<string, []>("transpose_64")];
            tensor<fp16, [16, 257, 64]> query_states_23_cast = reshape(shape = var_1038, x = transpose_64)[name = tensor<string, []>("query_states_23_cast")];
            tensor<int32, [3]> var_1040 = const()[name = tensor<string, []>("op_1040"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_63 = transpose(perm = var_1020_perm_0, x = var_1019_cast)[name = tensor<string, []>("transpose_63")];
            tensor<fp16, [16, 257, 64]> key_states_47_cast = reshape(shape = var_1040, x = transpose_63)[name = tensor<string, []>("key_states_47_cast")];
            tensor<int32, [3]> var_1042 = const()[name = tensor<string, []>("op_1042"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_62 = transpose(perm = var_1027_perm_0, x = var_1026_cast)[name = tensor<string, []>("transpose_62")];
            tensor<fp16, [16, 257, 64]> value_states_47_cast = reshape(shape = var_1042, x = transpose_62)[name = tensor<string, []>("value_states_47_cast")];
            tensor<int32, [3]> var_1044_perm_0 = const()[name = tensor<string, []>("op_1044_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_45_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_45_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_45_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_45_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_61 = transpose(perm = var_1044_perm_0, x = key_states_47_cast)[name = tensor<string, []>("transpose_61")];
            tensor<fp16, [16, 257, 257]> attn_weights_45_cast = matmul(transpose_x = attn_weights_45_transpose_x_0, transpose_y = attn_weights_45_transpose_y_0, x = query_states_23_cast, y = transpose_61)[name = tensor<string, []>("attn_weights_45_cast")];
            tensor<fp16, [16, 257, 257]> input_163_cast = softmax(axis = var_10, x = attn_weights_45_cast)[name = tensor<string, []>("input_163_cast")];
            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, [16, 257, 64]> attn_output_67_cast = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_163_cast, y = value_states_47_cast)[name = tensor<string, []>("attn_output_67_cast")];
            tensor<int32, [4]> var_1049 = const()[name = tensor<string, []>("op_1049"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_69_cast = reshape(shape = var_1049, x = attn_output_67_cast)[name = tensor<string, []>("attn_output_69_cast")];
            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_1052 = const()[name = tensor<string, []>("op_1052"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_60 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast)[name = tensor<string, []>("transpose_60")];
            tensor<fp16, [1, 257, 1024]> input_165_cast = reshape(shape = var_1052, x = transpose_60)[name = tensor<string, []>("input_165_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107098112))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107884608))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107884800)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_69_cast = linear(bias = vision_model_vision_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_165_cast)[name = tensor<string, []>("hidden_states_69_cast")];
            tensor<fp16, [1, 257, 1024]> input_167_cast = add(x = input_161_cast, y = hidden_states_69_cast)[name = tensor<string, []>("input_167_cast")];
            tensor<int32, [1]> input_169_axes_0 = const()[name = tensor<string, []>("input_169_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107886912)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107889024)))];
            tensor<fp16, [1, 257, 1024]> input_169_cast = layer_norm(axes = input_169_axes_0, beta = vision_model_vision_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_167_cast)[name = tensor<string, []>("input_169_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107891136))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111036928))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111037120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111040256))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_171_cast = linear(bias = vision_model_vision_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_169_cast)[name = tensor<string, []>("input_171_cast")];
            tensor<fp16, []> var_1067_to_fp16 = const()[name = tensor<string, []>("op_1067_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1068_cast = mul(x = input_171_cast, y = var_1067_to_fp16)[name = tensor<string, []>("op_1068_cast")];
            tensor<fp16, [1, 257, 4096]> var_1069_cast = sigmoid(x = var_1068_cast)[name = tensor<string, []>("op_1069_cast")];
            tensor<fp16, [1, 257, 4096]> input_173_cast = mul(x = input_171_cast, y = var_1069_cast)[name = tensor<string, []>("input_173_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111040448))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114186240))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114186432)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_71_cast = linear(bias = vision_model_vision_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_173_cast)[name = tensor<string, []>("hidden_states_71_cast")];
            tensor<fp16, [1, 257, 1024]> input_175_cast = add(x = input_167_cast, y = hidden_states_71_cast)[name = tensor<string, []>("input_175_cast")];
            tensor<int32, [1]> hidden_states_73_axes_0 = const()[name = tensor<string, []>("hidden_states_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114188544)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114190656)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_73_cast = layer_norm(axes = hidden_states_73_axes_0, beta = vision_model_vision_model_encoder_layers_12_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_12_layer_norm1_weight_to_fp16, x = input_175_cast)[name = tensor<string, []>("hidden_states_73_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114192768))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114979264))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114979456)))];
            tensor<fp16, [1, 257, 1024]> var_1093_cast = linear(bias = vision_model_vision_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_73_cast)[name = tensor<string, []>("op_1093_cast")];
            tensor<fp16, []> var_1094_to_fp16 = const()[name = tensor<string, []>("op_1094_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_77_cast = mul(x = var_1093_cast, y = var_1094_to_fp16)[name = tensor<string, []>("tensor_77_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114981568))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(115768064))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(115768256)))];
            tensor<fp16, [1, 257, 1024]> tensor_73_cast = linear(bias = vision_model_vision_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_73_cast")];
            tensor<int32, [4]> var_1099 = const()[name = tensor<string, []>("op_1099"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1100_cast = reshape(shape = var_1099, x = tensor_73_cast)[name = tensor<string, []>("op_1100_cast")];
            tensor<int32, [4]> var_1101_perm_0 = const()[name = tensor<string, []>("op_1101_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(115770368))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116556864))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116557056)))];
            tensor<fp16, [1, 257, 1024]> tensor_75_cast = linear(bias = vision_model_vision_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_75_cast")];
            tensor<int32, [4]> var_1106 = const()[name = tensor<string, []>("op_1106"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1107_cast = reshape(shape = var_1106, x = tensor_75_cast)[name = tensor<string, []>("op_1107_cast")];
            tensor<int32, [4]> var_1108_perm_0 = const()[name = tensor<string, []>("op_1108_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1115 = const()[name = tensor<string, []>("op_1115"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1116_cast = reshape(shape = var_1115, x = tensor_77_cast)[name = tensor<string, []>("op_1116_cast")];
            tensor<int32, [4]> var_1117_perm_0 = const()[name = tensor<string, []>("op_1117_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1119 = const()[name = tensor<string, []>("op_1119"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_59 = transpose(perm = var_1117_perm_0, x = var_1116_cast)[name = tensor<string, []>("transpose_59")];
            tensor<fp16, [16, 257, 64]> query_states_25_cast = reshape(shape = var_1119, x = transpose_59)[name = tensor<string, []>("query_states_25_cast")];
            tensor<int32, [3]> var_1121 = const()[name = tensor<string, []>("op_1121"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_58 = transpose(perm = var_1101_perm_0, x = var_1100_cast)[name = tensor<string, []>("transpose_58")];
            tensor<fp16, [16, 257, 64]> key_states_51_cast = reshape(shape = var_1121, x = transpose_58)[name = tensor<string, []>("key_states_51_cast")];
            tensor<int32, [3]> var_1123 = const()[name = tensor<string, []>("op_1123"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_57 = transpose(perm = var_1108_perm_0, x = var_1107_cast)[name = tensor<string, []>("transpose_57")];
            tensor<fp16, [16, 257, 64]> value_states_51_cast = reshape(shape = var_1123, x = transpose_57)[name = tensor<string, []>("value_states_51_cast")];
            tensor<int32, [3]> var_1125_perm_0 = const()[name = tensor<string, []>("op_1125_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_49_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_49_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_56 = transpose(perm = var_1125_perm_0, x = key_states_51_cast)[name = tensor<string, []>("transpose_56")];
            tensor<fp16, [16, 257, 257]> attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_25_cast, y = transpose_56)[name = tensor<string, []>("attn_weights_49_cast")];
            tensor<fp16, [16, 257, 257]> input_177_cast = softmax(axis = var_10, x = attn_weights_49_cast)[name = tensor<string, []>("input_177_cast")];
            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, [16, 257, 64]> attn_output_73_cast = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_177_cast, y = value_states_51_cast)[name = tensor<string, []>("attn_output_73_cast")];
            tensor<int32, [4]> var_1130 = const()[name = tensor<string, []>("op_1130"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_75_cast = reshape(shape = var_1130, x = attn_output_73_cast)[name = tensor<string, []>("attn_output_75_cast")];
            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_1133 = const()[name = tensor<string, []>("op_1133"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_55 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast)[name = tensor<string, []>("transpose_55")];
            tensor<fp16, [1, 257, 1024]> input_179_cast = reshape(shape = var_1133, x = transpose_55)[name = tensor<string, []>("input_179_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116559168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117345664))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117345856)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_75_cast = linear(bias = vision_model_vision_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized, x = input_179_cast)[name = tensor<string, []>("hidden_states_75_cast")];
            tensor<fp16, [1, 257, 1024]> input_181_cast = add(x = input_175_cast, y = hidden_states_75_cast)[name = tensor<string, []>("input_181_cast")];
            tensor<int32, [1]> input_183_axes_0 = const()[name = tensor<string, []>("input_183_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117347968)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117350080)))];
            tensor<fp16, [1, 257, 1024]> input_183_cast = layer_norm(axes = input_183_axes_0, beta = vision_model_vision_model_encoder_layers_12_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_12_layer_norm2_weight_to_fp16, x = input_181_cast)[name = tensor<string, []>("input_183_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117352192))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120497984))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120498176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120501312))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_185_cast = linear(bias = vision_model_vision_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized, x = input_183_cast)[name = tensor<string, []>("input_185_cast")];
            tensor<fp16, []> var_1148_to_fp16 = const()[name = tensor<string, []>("op_1148_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1149_cast = mul(x = input_185_cast, y = var_1148_to_fp16)[name = tensor<string, []>("op_1149_cast")];
            tensor<fp16, [1, 257, 4096]> var_1150_cast = sigmoid(x = var_1149_cast)[name = tensor<string, []>("op_1150_cast")];
            tensor<fp16, [1, 257, 4096]> input_187_cast = mul(x = input_185_cast, y = var_1150_cast)[name = tensor<string, []>("input_187_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120501504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123647296))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123647488)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_77_cast = linear(bias = vision_model_vision_model_encoder_layers_12_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized, x = input_187_cast)[name = tensor<string, []>("hidden_states_77_cast")];
            tensor<fp16, [1, 257, 1024]> input_189_cast = add(x = input_181_cast, y = hidden_states_77_cast)[name = tensor<string, []>("input_189_cast")];
            tensor<int32, [1]> hidden_states_79_axes_0 = const()[name = tensor<string, []>("hidden_states_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123649600)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123651712)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_79_cast = layer_norm(axes = hidden_states_79_axes_0, beta = vision_model_vision_model_encoder_layers_13_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_13_layer_norm1_weight_to_fp16, x = input_189_cast)[name = tensor<string, []>("hidden_states_79_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123653824))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124440320))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124440512)))];
            tensor<fp16, [1, 257, 1024]> var_1174_cast = linear(bias = vision_model_vision_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_79_cast)[name = tensor<string, []>("op_1174_cast")];
            tensor<fp16, []> var_1175_to_fp16 = const()[name = tensor<string, []>("op_1175_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_83_cast = mul(x = var_1174_cast, y = var_1175_to_fp16)[name = tensor<string, []>("tensor_83_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124442624))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125229120))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125229312)))];
            tensor<fp16, [1, 257, 1024]> tensor_79_cast = linear(bias = vision_model_vision_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_79_cast")];
            tensor<int32, [4]> var_1180 = const()[name = tensor<string, []>("op_1180"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1181_cast = reshape(shape = var_1180, x = tensor_79_cast)[name = tensor<string, []>("op_1181_cast")];
            tensor<int32, [4]> var_1182_perm_0 = const()[name = tensor<string, []>("op_1182_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125231424))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126017920))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126018112)))];
            tensor<fp16, [1, 257, 1024]> tensor_81_cast = linear(bias = vision_model_vision_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_81_cast")];
            tensor<int32, [4]> var_1187 = const()[name = tensor<string, []>("op_1187"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1188_cast = reshape(shape = var_1187, x = tensor_81_cast)[name = tensor<string, []>("op_1188_cast")];
            tensor<int32, [4]> var_1189_perm_0 = const()[name = tensor<string, []>("op_1189_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1196 = const()[name = tensor<string, []>("op_1196"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1197_cast = reshape(shape = var_1196, x = tensor_83_cast)[name = tensor<string, []>("op_1197_cast")];
            tensor<int32, [4]> var_1198_perm_0 = const()[name = tensor<string, []>("op_1198_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1200 = const()[name = tensor<string, []>("op_1200"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_54 = transpose(perm = var_1198_perm_0, x = var_1197_cast)[name = tensor<string, []>("transpose_54")];
            tensor<fp16, [16, 257, 64]> query_states_27_cast = reshape(shape = var_1200, x = transpose_54)[name = tensor<string, []>("query_states_27_cast")];
            tensor<int32, [3]> var_1202 = const()[name = tensor<string, []>("op_1202"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_53 = transpose(perm = var_1182_perm_0, x = var_1181_cast)[name = tensor<string, []>("transpose_53")];
            tensor<fp16, [16, 257, 64]> key_states_55_cast = reshape(shape = var_1202, x = transpose_53)[name = tensor<string, []>("key_states_55_cast")];
            tensor<int32, [3]> var_1204 = const()[name = tensor<string, []>("op_1204"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_52 = transpose(perm = var_1189_perm_0, x = var_1188_cast)[name = tensor<string, []>("transpose_52")];
            tensor<fp16, [16, 257, 64]> value_states_55_cast = reshape(shape = var_1204, x = transpose_52)[name = tensor<string, []>("value_states_55_cast")];
            tensor<int32, [3]> var_1206_perm_0 = const()[name = tensor<string, []>("op_1206_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_53_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_53_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_53_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_53_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_51 = transpose(perm = var_1206_perm_0, x = key_states_55_cast)[name = tensor<string, []>("transpose_51")];
            tensor<fp16, [16, 257, 257]> attn_weights_53_cast = matmul(transpose_x = attn_weights_53_transpose_x_0, transpose_y = attn_weights_53_transpose_y_0, x = query_states_27_cast, y = transpose_51)[name = tensor<string, []>("attn_weights_53_cast")];
            tensor<fp16, [16, 257, 257]> input_191_cast = softmax(axis = var_10, x = attn_weights_53_cast)[name = tensor<string, []>("input_191_cast")];
            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, [16, 257, 64]> attn_output_79_cast = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_191_cast, y = value_states_55_cast)[name = tensor<string, []>("attn_output_79_cast")];
            tensor<int32, [4]> var_1211 = const()[name = tensor<string, []>("op_1211"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_81_cast = reshape(shape = var_1211, x = attn_output_79_cast)[name = tensor<string, []>("attn_output_81_cast")];
            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_1214 = const()[name = tensor<string, []>("op_1214"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_50 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast)[name = tensor<string, []>("transpose_50")];
            tensor<fp16, [1, 257, 1024]> input_193_cast = reshape(shape = var_1214, x = transpose_50)[name = tensor<string, []>("input_193_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126020224))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126806720))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126806912)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_81_cast = linear(bias = vision_model_vision_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized, x = input_193_cast)[name = tensor<string, []>("hidden_states_81_cast")];
            tensor<fp16, [1, 257, 1024]> input_195_cast = add(x = input_189_cast, y = hidden_states_81_cast)[name = tensor<string, []>("input_195_cast")];
            tensor<int32, [1]> input_197_axes_0 = const()[name = tensor<string, []>("input_197_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126809024)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126811136)))];
            tensor<fp16, [1, 257, 1024]> input_197_cast = layer_norm(axes = input_197_axes_0, beta = vision_model_vision_model_encoder_layers_13_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_13_layer_norm2_weight_to_fp16, x = input_195_cast)[name = tensor<string, []>("input_197_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126813248))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129959040))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129959232))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129962368))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_199_cast = linear(bias = vision_model_vision_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized, x = input_197_cast)[name = tensor<string, []>("input_199_cast")];
            tensor<fp16, []> var_1229_to_fp16 = const()[name = tensor<string, []>("op_1229_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1230_cast = mul(x = input_199_cast, y = var_1229_to_fp16)[name = tensor<string, []>("op_1230_cast")];
            tensor<fp16, [1, 257, 4096]> var_1231_cast = sigmoid(x = var_1230_cast)[name = tensor<string, []>("op_1231_cast")];
            tensor<fp16, [1, 257, 4096]> input_201_cast = mul(x = input_199_cast, y = var_1231_cast)[name = tensor<string, []>("input_201_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129962560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133108352))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133108544)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_83_cast = linear(bias = vision_model_vision_model_encoder_layers_13_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized, x = input_201_cast)[name = tensor<string, []>("hidden_states_83_cast")];
            tensor<fp16, [1, 257, 1024]> input_203_cast = add(x = input_195_cast, y = hidden_states_83_cast)[name = tensor<string, []>("input_203_cast")];
            tensor<int32, [1]> hidden_states_85_axes_0 = const()[name = tensor<string, []>("hidden_states_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133110656)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133112768)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_85_cast = layer_norm(axes = hidden_states_85_axes_0, beta = vision_model_vision_model_encoder_layers_14_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_14_layer_norm1_weight_to_fp16, x = input_203_cast)[name = tensor<string, []>("hidden_states_85_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133114880))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133901376))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133901568)))];
            tensor<fp16, [1, 257, 1024]> var_1255_cast = linear(bias = vision_model_vision_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_85_cast)[name = tensor<string, []>("op_1255_cast")];
            tensor<fp16, []> var_1256_to_fp16 = const()[name = tensor<string, []>("op_1256_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_89_cast = mul(x = var_1255_cast, y = var_1256_to_fp16)[name = tensor<string, []>("tensor_89_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133903680))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134690176))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134690368)))];
            tensor<fp16, [1, 257, 1024]> tensor_85_cast = linear(bias = vision_model_vision_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_85_cast")];
            tensor<int32, [4]> var_1261 = const()[name = tensor<string, []>("op_1261"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1262_cast = reshape(shape = var_1261, x = tensor_85_cast)[name = tensor<string, []>("op_1262_cast")];
            tensor<int32, [4]> var_1263_perm_0 = const()[name = tensor<string, []>("op_1263_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134692480))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135478976))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135479168)))];
            tensor<fp16, [1, 257, 1024]> tensor_87_cast = linear(bias = vision_model_vision_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_87_cast")];
            tensor<int32, [4]> var_1268 = const()[name = tensor<string, []>("op_1268"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1269_cast = reshape(shape = var_1268, x = tensor_87_cast)[name = tensor<string, []>("op_1269_cast")];
            tensor<int32, [4]> var_1270_perm_0 = const()[name = tensor<string, []>("op_1270_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1277 = const()[name = tensor<string, []>("op_1277"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1278_cast = reshape(shape = var_1277, x = tensor_89_cast)[name = tensor<string, []>("op_1278_cast")];
            tensor<int32, [4]> var_1279_perm_0 = const()[name = tensor<string, []>("op_1279_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1281 = const()[name = tensor<string, []>("op_1281"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_49 = transpose(perm = var_1279_perm_0, x = var_1278_cast)[name = tensor<string, []>("transpose_49")];
            tensor<fp16, [16, 257, 64]> query_states_29_cast = reshape(shape = var_1281, x = transpose_49)[name = tensor<string, []>("query_states_29_cast")];
            tensor<int32, [3]> var_1283 = const()[name = tensor<string, []>("op_1283"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_48 = transpose(perm = var_1263_perm_0, x = var_1262_cast)[name = tensor<string, []>("transpose_48")];
            tensor<fp16, [16, 257, 64]> key_states_59_cast = reshape(shape = var_1283, x = transpose_48)[name = tensor<string, []>("key_states_59_cast")];
            tensor<int32, [3]> var_1285 = const()[name = tensor<string, []>("op_1285"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_47 = transpose(perm = var_1270_perm_0, x = var_1269_cast)[name = tensor<string, []>("transpose_47")];
            tensor<fp16, [16, 257, 64]> value_states_59_cast = reshape(shape = var_1285, x = transpose_47)[name = tensor<string, []>("value_states_59_cast")];
            tensor<int32, [3]> var_1287_perm_0 = const()[name = tensor<string, []>("op_1287_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_57_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_57_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_57_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_57_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_46 = transpose(perm = var_1287_perm_0, x = key_states_59_cast)[name = tensor<string, []>("transpose_46")];
            tensor<fp16, [16, 257, 257]> attn_weights_57_cast = matmul(transpose_x = attn_weights_57_transpose_x_0, transpose_y = attn_weights_57_transpose_y_0, x = query_states_29_cast, y = transpose_46)[name = tensor<string, []>("attn_weights_57_cast")];
            tensor<fp16, [16, 257, 257]> input_205_cast = softmax(axis = var_10, x = attn_weights_57_cast)[name = tensor<string, []>("input_205_cast")];
            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, [16, 257, 64]> attn_output_85_cast = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_205_cast, y = value_states_59_cast)[name = tensor<string, []>("attn_output_85_cast")];
            tensor<int32, [4]> var_1292 = const()[name = tensor<string, []>("op_1292"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_87_cast = reshape(shape = var_1292, x = attn_output_85_cast)[name = tensor<string, []>("attn_output_87_cast")];
            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_1295 = const()[name = tensor<string, []>("op_1295"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_45 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast)[name = tensor<string, []>("transpose_45")];
            tensor<fp16, [1, 257, 1024]> input_207_cast = reshape(shape = var_1295, x = transpose_45)[name = tensor<string, []>("input_207_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135481280))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136267776))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136267968)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_87_cast = linear(bias = vision_model_vision_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized, x = input_207_cast)[name = tensor<string, []>("hidden_states_87_cast")];
            tensor<fp16, [1, 257, 1024]> input_209_cast = add(x = input_203_cast, y = hidden_states_87_cast)[name = tensor<string, []>("input_209_cast")];
            tensor<int32, [1]> input_211_axes_0 = const()[name = tensor<string, []>("input_211_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136270080)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136272192)))];
            tensor<fp16, [1, 257, 1024]> input_211_cast = layer_norm(axes = input_211_axes_0, beta = vision_model_vision_model_encoder_layers_14_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_14_layer_norm2_weight_to_fp16, x = input_209_cast)[name = tensor<string, []>("input_211_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136274304))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139420096))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139420288))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139423424))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_213_cast = linear(bias = vision_model_vision_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized, x = input_211_cast)[name = tensor<string, []>("input_213_cast")];
            tensor<fp16, []> var_1310_to_fp16 = const()[name = tensor<string, []>("op_1310_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1311_cast = mul(x = input_213_cast, y = var_1310_to_fp16)[name = tensor<string, []>("op_1311_cast")];
            tensor<fp16, [1, 257, 4096]> var_1312_cast = sigmoid(x = var_1311_cast)[name = tensor<string, []>("op_1312_cast")];
            tensor<fp16, [1, 257, 4096]> input_215_cast = mul(x = input_213_cast, y = var_1312_cast)[name = tensor<string, []>("input_215_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139423616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142569408))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142569600)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_89_cast = linear(bias = vision_model_vision_model_encoder_layers_14_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized, x = input_215_cast)[name = tensor<string, []>("hidden_states_89_cast")];
            tensor<fp16, [1, 257, 1024]> input_217_cast = add(x = input_209_cast, y = hidden_states_89_cast)[name = tensor<string, []>("input_217_cast")];
            tensor<int32, [1]> hidden_states_91_axes_0 = const()[name = tensor<string, []>("hidden_states_91_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142571712)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142573824)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_91_cast = layer_norm(axes = hidden_states_91_axes_0, beta = vision_model_vision_model_encoder_layers_15_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_15_layer_norm1_weight_to_fp16, x = input_217_cast)[name = tensor<string, []>("hidden_states_91_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142575936))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143362432))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143362624)))];
            tensor<fp16, [1, 257, 1024]> var_1336_cast = linear(bias = vision_model_vision_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_91_cast)[name = tensor<string, []>("op_1336_cast")];
            tensor<fp16, []> var_1337_to_fp16 = const()[name = tensor<string, []>("op_1337_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_95_cast = mul(x = var_1336_cast, y = var_1337_to_fp16)[name = tensor<string, []>("tensor_95_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143364736))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144151232))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144151424)))];
            tensor<fp16, [1, 257, 1024]> tensor_91_cast = linear(bias = vision_model_vision_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_91_cast")];
            tensor<int32, [4]> var_1342 = const()[name = tensor<string, []>("op_1342"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1343_cast = reshape(shape = var_1342, x = tensor_91_cast)[name = tensor<string, []>("op_1343_cast")];
            tensor<int32, [4]> var_1344_perm_0 = const()[name = tensor<string, []>("op_1344_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144153536))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144940032))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144940224)))];
            tensor<fp16, [1, 257, 1024]> tensor_93_cast = linear(bias = vision_model_vision_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_93_cast")];
            tensor<int32, [4]> var_1349 = const()[name = tensor<string, []>("op_1349"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1350_cast = reshape(shape = var_1349, x = tensor_93_cast)[name = tensor<string, []>("op_1350_cast")];
            tensor<int32, [4]> var_1351_perm_0 = const()[name = tensor<string, []>("op_1351_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1358 = const()[name = tensor<string, []>("op_1358"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1359_cast = reshape(shape = var_1358, x = tensor_95_cast)[name = tensor<string, []>("op_1359_cast")];
            tensor<int32, [4]> var_1360_perm_0 = const()[name = tensor<string, []>("op_1360_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1362 = const()[name = tensor<string, []>("op_1362"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_44 = transpose(perm = var_1360_perm_0, x = var_1359_cast)[name = tensor<string, []>("transpose_44")];
            tensor<fp16, [16, 257, 64]> query_states_31_cast = reshape(shape = var_1362, x = transpose_44)[name = tensor<string, []>("query_states_31_cast")];
            tensor<int32, [3]> var_1364 = const()[name = tensor<string, []>("op_1364"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_43 = transpose(perm = var_1344_perm_0, x = var_1343_cast)[name = tensor<string, []>("transpose_43")];
            tensor<fp16, [16, 257, 64]> key_states_63_cast = reshape(shape = var_1364, x = transpose_43)[name = tensor<string, []>("key_states_63_cast")];
            tensor<int32, [3]> var_1366 = const()[name = tensor<string, []>("op_1366"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_42 = transpose(perm = var_1351_perm_0, x = var_1350_cast)[name = tensor<string, []>("transpose_42")];
            tensor<fp16, [16, 257, 64]> value_states_63_cast = reshape(shape = var_1366, x = transpose_42)[name = tensor<string, []>("value_states_63_cast")];
            tensor<int32, [3]> var_1368_perm_0 = const()[name = tensor<string, []>("op_1368_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_61_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_61_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_41 = transpose(perm = var_1368_perm_0, x = key_states_63_cast)[name = tensor<string, []>("transpose_41")];
            tensor<fp16, [16, 257, 257]> attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_31_cast, y = transpose_41)[name = tensor<string, []>("attn_weights_61_cast")];
            tensor<fp16, [16, 257, 257]> input_219_cast = softmax(axis = var_10, x = attn_weights_61_cast)[name = tensor<string, []>("input_219_cast")];
            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, [16, 257, 64]> attn_output_91_cast = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_219_cast, y = value_states_63_cast)[name = tensor<string, []>("attn_output_91_cast")];
            tensor<int32, [4]> var_1373 = const()[name = tensor<string, []>("op_1373"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_93_cast = reshape(shape = var_1373, x = attn_output_91_cast)[name = tensor<string, []>("attn_output_93_cast")];
            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_1376 = const()[name = tensor<string, []>("op_1376"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_40 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast)[name = tensor<string, []>("transpose_40")];
            tensor<fp16, [1, 257, 1024]> input_221_cast = reshape(shape = var_1376, x = transpose_40)[name = tensor<string, []>("input_221_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(144942336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145728832))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145729024)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_93_cast = linear(bias = vision_model_vision_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized, x = input_221_cast)[name = tensor<string, []>("hidden_states_93_cast")];
            tensor<fp16, [1, 257, 1024]> input_223_cast = add(x = input_217_cast, y = hidden_states_93_cast)[name = tensor<string, []>("input_223_cast")];
            tensor<int32, [1]> input_225_axes_0 = const()[name = tensor<string, []>("input_225_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145731136)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145733248)))];
            tensor<fp16, [1, 257, 1024]> input_225_cast = layer_norm(axes = input_225_axes_0, beta = vision_model_vision_model_encoder_layers_15_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_15_layer_norm2_weight_to_fp16, x = input_223_cast)[name = tensor<string, []>("input_225_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145735360))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148881152))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148881344))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148884480))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_227_cast = linear(bias = vision_model_vision_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized, x = input_225_cast)[name = tensor<string, []>("input_227_cast")];
            tensor<fp16, []> var_1391_to_fp16 = const()[name = tensor<string, []>("op_1391_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1392_cast = mul(x = input_227_cast, y = var_1391_to_fp16)[name = tensor<string, []>("op_1392_cast")];
            tensor<fp16, [1, 257, 4096]> var_1393_cast = sigmoid(x = var_1392_cast)[name = tensor<string, []>("op_1393_cast")];
            tensor<fp16, [1, 257, 4096]> input_229_cast = mul(x = input_227_cast, y = var_1393_cast)[name = tensor<string, []>("input_229_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148884672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152030464))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152030656)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_95_cast = linear(bias = vision_model_vision_model_encoder_layers_15_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized, x = input_229_cast)[name = tensor<string, []>("hidden_states_95_cast")];
            tensor<fp16, [1, 257, 1024]> input_231_cast = add(x = input_223_cast, y = hidden_states_95_cast)[name = tensor<string, []>("input_231_cast")];
            tensor<int32, [1]> hidden_states_97_axes_0 = const()[name = tensor<string, []>("hidden_states_97_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152032768)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152034880)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_97_cast = layer_norm(axes = hidden_states_97_axes_0, beta = vision_model_vision_model_encoder_layers_16_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_16_layer_norm1_weight_to_fp16, x = input_231_cast)[name = tensor<string, []>("hidden_states_97_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152036992))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152823488))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152823680)))];
            tensor<fp16, [1, 257, 1024]> var_1417_cast = linear(bias = vision_model_vision_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_97_cast)[name = tensor<string, []>("op_1417_cast")];
            tensor<fp16, []> var_1418_to_fp16 = const()[name = tensor<string, []>("op_1418_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_101_cast = mul(x = var_1417_cast, y = var_1418_to_fp16)[name = tensor<string, []>("tensor_101_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152825792))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153612288))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153612480)))];
            tensor<fp16, [1, 257, 1024]> tensor_97_cast = linear(bias = vision_model_vision_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_97_cast")];
            tensor<int32, [4]> var_1423 = const()[name = tensor<string, []>("op_1423"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1424_cast = reshape(shape = var_1423, x = tensor_97_cast)[name = tensor<string, []>("op_1424_cast")];
            tensor<int32, [4]> var_1425_perm_0 = const()[name = tensor<string, []>("op_1425_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153614592))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154401088))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154401280)))];
            tensor<fp16, [1, 257, 1024]> tensor_99_cast = linear(bias = vision_model_vision_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_99_cast")];
            tensor<int32, [4]> var_1430 = const()[name = tensor<string, []>("op_1430"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1431_cast = reshape(shape = var_1430, x = tensor_99_cast)[name = tensor<string, []>("op_1431_cast")];
            tensor<int32, [4]> var_1432_perm_0 = const()[name = tensor<string, []>("op_1432_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1439 = const()[name = tensor<string, []>("op_1439"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1440_cast = reshape(shape = var_1439, x = tensor_101_cast)[name = tensor<string, []>("op_1440_cast")];
            tensor<int32, [4]> var_1441_perm_0 = const()[name = tensor<string, []>("op_1441_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1443 = const()[name = tensor<string, []>("op_1443"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_39 = transpose(perm = var_1441_perm_0, x = var_1440_cast)[name = tensor<string, []>("transpose_39")];
            tensor<fp16, [16, 257, 64]> query_states_33_cast = reshape(shape = var_1443, x = transpose_39)[name = tensor<string, []>("query_states_33_cast")];
            tensor<int32, [3]> var_1445 = const()[name = tensor<string, []>("op_1445"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_38 = transpose(perm = var_1425_perm_0, x = var_1424_cast)[name = tensor<string, []>("transpose_38")];
            tensor<fp16, [16, 257, 64]> key_states_67_cast = reshape(shape = var_1445, x = transpose_38)[name = tensor<string, []>("key_states_67_cast")];
            tensor<int32, [3]> var_1447 = const()[name = tensor<string, []>("op_1447"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_37 = transpose(perm = var_1432_perm_0, x = var_1431_cast)[name = tensor<string, []>("transpose_37")];
            tensor<fp16, [16, 257, 64]> value_states_67_cast = reshape(shape = var_1447, x = transpose_37)[name = tensor<string, []>("value_states_67_cast")];
            tensor<int32, [3]> var_1449_perm_0 = const()[name = tensor<string, []>("op_1449_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_65_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_65_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_65_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_65_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_36 = transpose(perm = var_1449_perm_0, x = key_states_67_cast)[name = tensor<string, []>("transpose_36")];
            tensor<fp16, [16, 257, 257]> attn_weights_65_cast = matmul(transpose_x = attn_weights_65_transpose_x_0, transpose_y = attn_weights_65_transpose_y_0, x = query_states_33_cast, y = transpose_36)[name = tensor<string, []>("attn_weights_65_cast")];
            tensor<fp16, [16, 257, 257]> input_233_cast = softmax(axis = var_10, x = attn_weights_65_cast)[name = tensor<string, []>("input_233_cast")];
            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, [16, 257, 64]> attn_output_97_cast = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_233_cast, y = value_states_67_cast)[name = tensor<string, []>("attn_output_97_cast")];
            tensor<int32, [4]> var_1454 = const()[name = tensor<string, []>("op_1454"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_99_cast = reshape(shape = var_1454, x = attn_output_97_cast)[name = tensor<string, []>("attn_output_99_cast")];
            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_1457 = const()[name = tensor<string, []>("op_1457"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_35 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast)[name = tensor<string, []>("transpose_35")];
            tensor<fp16, [1, 257, 1024]> input_235_cast = reshape(shape = var_1457, x = transpose_35)[name = tensor<string, []>("input_235_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154403392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155189888))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155190080)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_99_cast = linear(bias = vision_model_vision_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized, x = input_235_cast)[name = tensor<string, []>("hidden_states_99_cast")];
            tensor<fp16, [1, 257, 1024]> input_237_cast = add(x = input_231_cast, y = hidden_states_99_cast)[name = tensor<string, []>("input_237_cast")];
            tensor<int32, [1]> input_239_axes_0 = const()[name = tensor<string, []>("input_239_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155192192)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155194304)))];
            tensor<fp16, [1, 257, 1024]> input_239_cast = layer_norm(axes = input_239_axes_0, beta = vision_model_vision_model_encoder_layers_16_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_16_layer_norm2_weight_to_fp16, x = input_237_cast)[name = tensor<string, []>("input_239_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155196416))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158342208))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158342400))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158345536))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_241_cast = linear(bias = vision_model_vision_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized, x = input_239_cast)[name = tensor<string, []>("input_241_cast")];
            tensor<fp16, []> var_1472_to_fp16 = const()[name = tensor<string, []>("op_1472_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1473_cast = mul(x = input_241_cast, y = var_1472_to_fp16)[name = tensor<string, []>("op_1473_cast")];
            tensor<fp16, [1, 257, 4096]> var_1474_cast = sigmoid(x = var_1473_cast)[name = tensor<string, []>("op_1474_cast")];
            tensor<fp16, [1, 257, 4096]> input_243_cast = mul(x = input_241_cast, y = var_1474_cast)[name = tensor<string, []>("input_243_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158345728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161491520))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161491712)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_101_cast = linear(bias = vision_model_vision_model_encoder_layers_16_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized, x = input_243_cast)[name = tensor<string, []>("hidden_states_101_cast")];
            tensor<fp16, [1, 257, 1024]> input_245_cast = add(x = input_237_cast, y = hidden_states_101_cast)[name = tensor<string, []>("input_245_cast")];
            tensor<int32, [1]> hidden_states_103_axes_0 = const()[name = tensor<string, []>("hidden_states_103_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161493824)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161495936)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_103_cast = layer_norm(axes = hidden_states_103_axes_0, beta = vision_model_vision_model_encoder_layers_17_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_17_layer_norm1_weight_to_fp16, x = input_245_cast)[name = tensor<string, []>("hidden_states_103_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161498048))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162284544))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162284736)))];
            tensor<fp16, [1, 257, 1024]> var_1498_cast = linear(bias = vision_model_vision_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_103_cast)[name = tensor<string, []>("op_1498_cast")];
            tensor<fp16, []> var_1499_to_fp16 = const()[name = tensor<string, []>("op_1499_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_107_cast = mul(x = var_1498_cast, y = var_1499_to_fp16)[name = tensor<string, []>("tensor_107_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162286848))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163073344))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163073536)))];
            tensor<fp16, [1, 257, 1024]> tensor_103_cast = linear(bias = vision_model_vision_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_103_cast")];
            tensor<int32, [4]> var_1504 = const()[name = tensor<string, []>("op_1504"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1505_cast = reshape(shape = var_1504, x = tensor_103_cast)[name = tensor<string, []>("op_1505_cast")];
            tensor<int32, [4]> var_1506_perm_0 = const()[name = tensor<string, []>("op_1506_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163075648))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163862144))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163862336)))];
            tensor<fp16, [1, 257, 1024]> tensor_105_cast = linear(bias = vision_model_vision_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_105_cast")];
            tensor<int32, [4]> var_1511 = const()[name = tensor<string, []>("op_1511"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1512_cast = reshape(shape = var_1511, x = tensor_105_cast)[name = tensor<string, []>("op_1512_cast")];
            tensor<int32, [4]> var_1513_perm_0 = const()[name = tensor<string, []>("op_1513_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1520 = const()[name = tensor<string, []>("op_1520"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1521_cast = reshape(shape = var_1520, x = tensor_107_cast)[name = tensor<string, []>("op_1521_cast")];
            tensor<int32, [4]> var_1522_perm_0 = const()[name = tensor<string, []>("op_1522_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1524 = const()[name = tensor<string, []>("op_1524"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_34 = transpose(perm = var_1522_perm_0, x = var_1521_cast)[name = tensor<string, []>("transpose_34")];
            tensor<fp16, [16, 257, 64]> query_states_35_cast = reshape(shape = var_1524, x = transpose_34)[name = tensor<string, []>("query_states_35_cast")];
            tensor<int32, [3]> var_1526 = const()[name = tensor<string, []>("op_1526"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_33 = transpose(perm = var_1506_perm_0, x = var_1505_cast)[name = tensor<string, []>("transpose_33")];
            tensor<fp16, [16, 257, 64]> key_states_71_cast = reshape(shape = var_1526, x = transpose_33)[name = tensor<string, []>("key_states_71_cast")];
            tensor<int32, [3]> var_1528 = const()[name = tensor<string, []>("op_1528"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_32 = transpose(perm = var_1513_perm_0, x = var_1512_cast)[name = tensor<string, []>("transpose_32")];
            tensor<fp16, [16, 257, 64]> value_states_71_cast = reshape(shape = var_1528, x = transpose_32)[name = tensor<string, []>("value_states_71_cast")];
            tensor<int32, [3]> var_1530_perm_0 = const()[name = tensor<string, []>("op_1530_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_69_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_69_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_69_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_69_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_31 = transpose(perm = var_1530_perm_0, x = key_states_71_cast)[name = tensor<string, []>("transpose_31")];
            tensor<fp16, [16, 257, 257]> attn_weights_69_cast = matmul(transpose_x = attn_weights_69_transpose_x_0, transpose_y = attn_weights_69_transpose_y_0, x = query_states_35_cast, y = transpose_31)[name = tensor<string, []>("attn_weights_69_cast")];
            tensor<fp16, [16, 257, 257]> input_247_cast = softmax(axis = var_10, x = attn_weights_69_cast)[name = tensor<string, []>("input_247_cast")];
            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, [16, 257, 64]> attn_output_103_cast = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_247_cast, y = value_states_71_cast)[name = tensor<string, []>("attn_output_103_cast")];
            tensor<int32, [4]> var_1535 = const()[name = tensor<string, []>("op_1535"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_105_cast = reshape(shape = var_1535, x = attn_output_103_cast)[name = tensor<string, []>("attn_output_105_cast")];
            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_1538 = const()[name = tensor<string, []>("op_1538"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_30 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast)[name = tensor<string, []>("transpose_30")];
            tensor<fp16, [1, 257, 1024]> input_249_cast = reshape(shape = var_1538, x = transpose_30)[name = tensor<string, []>("input_249_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163864448))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164650944))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164651136)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_105_cast = linear(bias = vision_model_vision_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized, x = input_249_cast)[name = tensor<string, []>("hidden_states_105_cast")];
            tensor<fp16, [1, 257, 1024]> input_251_cast = add(x = input_245_cast, y = hidden_states_105_cast)[name = tensor<string, []>("input_251_cast")];
            tensor<int32, [1]> input_253_axes_0 = const()[name = tensor<string, []>("input_253_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164653248)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164655360)))];
            tensor<fp16, [1, 257, 1024]> input_253_cast = layer_norm(axes = input_253_axes_0, beta = vision_model_vision_model_encoder_layers_17_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_17_layer_norm2_weight_to_fp16, x = input_251_cast)[name = tensor<string, []>("input_253_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164657472))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167803264))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167803456))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167806592))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_255_cast = linear(bias = vision_model_vision_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized, x = input_253_cast)[name = tensor<string, []>("input_255_cast")];
            tensor<fp16, []> var_1553_to_fp16 = const()[name = tensor<string, []>("op_1553_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1554_cast = mul(x = input_255_cast, y = var_1553_to_fp16)[name = tensor<string, []>("op_1554_cast")];
            tensor<fp16, [1, 257, 4096]> var_1555_cast = sigmoid(x = var_1554_cast)[name = tensor<string, []>("op_1555_cast")];
            tensor<fp16, [1, 257, 4096]> input_257_cast = mul(x = input_255_cast, y = var_1555_cast)[name = tensor<string, []>("input_257_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(167806784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170952576))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170952768)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_107_cast = linear(bias = vision_model_vision_model_encoder_layers_17_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized, x = input_257_cast)[name = tensor<string, []>("hidden_states_107_cast")];
            tensor<fp16, [1, 257, 1024]> input_259_cast = add(x = input_251_cast, y = hidden_states_107_cast)[name = tensor<string, []>("input_259_cast")];
            tensor<int32, [1]> hidden_states_109_axes_0 = const()[name = tensor<string, []>("hidden_states_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170954880)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170956992)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_109_cast = layer_norm(axes = hidden_states_109_axes_0, beta = vision_model_vision_model_encoder_layers_18_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_18_layer_norm1_weight_to_fp16, x = input_259_cast)[name = tensor<string, []>("hidden_states_109_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170959104))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171745600))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171745792)))];
            tensor<fp16, [1, 257, 1024]> var_1579_cast = linear(bias = vision_model_vision_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_109_cast)[name = tensor<string, []>("op_1579_cast")];
            tensor<fp16, []> var_1580_to_fp16 = const()[name = tensor<string, []>("op_1580_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_113_cast = mul(x = var_1579_cast, y = var_1580_to_fp16)[name = tensor<string, []>("tensor_113_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171747904))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172534400))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172534592)))];
            tensor<fp16, [1, 257, 1024]> tensor_109_cast = linear(bias = vision_model_vision_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_109_cast")];
            tensor<int32, [4]> var_1585 = const()[name = tensor<string, []>("op_1585"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1586_cast = reshape(shape = var_1585, x = tensor_109_cast)[name = tensor<string, []>("op_1586_cast")];
            tensor<int32, [4]> var_1587_perm_0 = const()[name = tensor<string, []>("op_1587_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172536704))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173323200))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173323392)))];
            tensor<fp16, [1, 257, 1024]> tensor_111_cast = linear(bias = vision_model_vision_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_111_cast")];
            tensor<int32, [4]> var_1592 = const()[name = tensor<string, []>("op_1592"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1593_cast = reshape(shape = var_1592, x = tensor_111_cast)[name = tensor<string, []>("op_1593_cast")];
            tensor<int32, [4]> var_1594_perm_0 = const()[name = tensor<string, []>("op_1594_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1601 = const()[name = tensor<string, []>("op_1601"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1602_cast = reshape(shape = var_1601, x = tensor_113_cast)[name = tensor<string, []>("op_1602_cast")];
            tensor<int32, [4]> var_1603_perm_0 = const()[name = tensor<string, []>("op_1603_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1605 = const()[name = tensor<string, []>("op_1605"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_29 = transpose(perm = var_1603_perm_0, x = var_1602_cast)[name = tensor<string, []>("transpose_29")];
            tensor<fp16, [16, 257, 64]> query_states_37_cast = reshape(shape = var_1605, x = transpose_29)[name = tensor<string, []>("query_states_37_cast")];
            tensor<int32, [3]> var_1607 = const()[name = tensor<string, []>("op_1607"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_28 = transpose(perm = var_1587_perm_0, x = var_1586_cast)[name = tensor<string, []>("transpose_28")];
            tensor<fp16, [16, 257, 64]> key_states_75_cast = reshape(shape = var_1607, x = transpose_28)[name = tensor<string, []>("key_states_75_cast")];
            tensor<int32, [3]> var_1609 = const()[name = tensor<string, []>("op_1609"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_27 = transpose(perm = var_1594_perm_0, x = var_1593_cast)[name = tensor<string, []>("transpose_27")];
            tensor<fp16, [16, 257, 64]> value_states_75_cast = reshape(shape = var_1609, x = transpose_27)[name = tensor<string, []>("value_states_75_cast")];
            tensor<int32, [3]> var_1611_perm_0 = const()[name = tensor<string, []>("op_1611_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_73_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_73_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_26 = transpose(perm = var_1611_perm_0, x = key_states_75_cast)[name = tensor<string, []>("transpose_26")];
            tensor<fp16, [16, 257, 257]> attn_weights_73_cast = matmul(transpose_x = attn_weights_73_transpose_x_0, transpose_y = attn_weights_73_transpose_y_0, x = query_states_37_cast, y = transpose_26)[name = tensor<string, []>("attn_weights_73_cast")];
            tensor<fp16, [16, 257, 257]> input_261_cast = softmax(axis = var_10, x = attn_weights_73_cast)[name = tensor<string, []>("input_261_cast")];
            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, [16, 257, 64]> attn_output_109_cast = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_261_cast, y = value_states_75_cast)[name = tensor<string, []>("attn_output_109_cast")];
            tensor<int32, [4]> var_1616 = const()[name = tensor<string, []>("op_1616"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_111_cast = reshape(shape = var_1616, x = attn_output_109_cast)[name = tensor<string, []>("attn_output_111_cast")];
            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_1619 = const()[name = tensor<string, []>("op_1619"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_25 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast)[name = tensor<string, []>("transpose_25")];
            tensor<fp16, [1, 257, 1024]> input_263_cast = reshape(shape = var_1619, x = transpose_25)[name = tensor<string, []>("input_263_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173325504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174112000))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174112192)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_111_cast = linear(bias = vision_model_vision_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized, x = input_263_cast)[name = tensor<string, []>("hidden_states_111_cast")];
            tensor<fp16, [1, 257, 1024]> input_265_cast = add(x = input_259_cast, y = hidden_states_111_cast)[name = tensor<string, []>("input_265_cast")];
            tensor<int32, [1]> input_267_axes_0 = const()[name = tensor<string, []>("input_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174114304)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174116416)))];
            tensor<fp16, [1, 257, 1024]> input_267_cast = layer_norm(axes = input_267_axes_0, beta = vision_model_vision_model_encoder_layers_18_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_18_layer_norm2_weight_to_fp16, x = input_265_cast)[name = tensor<string, []>("input_267_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174118528))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177264320))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177264512))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177267648))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_269_cast = linear(bias = vision_model_vision_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized, x = input_267_cast)[name = tensor<string, []>("input_269_cast")];
            tensor<fp16, []> var_1634_to_fp16 = const()[name = tensor<string, []>("op_1634_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1635_cast = mul(x = input_269_cast, y = var_1634_to_fp16)[name = tensor<string, []>("op_1635_cast")];
            tensor<fp16, [1, 257, 4096]> var_1636_cast = sigmoid(x = var_1635_cast)[name = tensor<string, []>("op_1636_cast")];
            tensor<fp16, [1, 257, 4096]> input_271_cast = mul(x = input_269_cast, y = var_1636_cast)[name = tensor<string, []>("input_271_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(177267840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180413632))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180413824)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_113_cast = linear(bias = vision_model_vision_model_encoder_layers_18_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized, x = input_271_cast)[name = tensor<string, []>("hidden_states_113_cast")];
            tensor<fp16, [1, 257, 1024]> input_273_cast = add(x = input_265_cast, y = hidden_states_113_cast)[name = tensor<string, []>("input_273_cast")];
            tensor<int32, [1]> hidden_states_115_axes_0 = const()[name = tensor<string, []>("hidden_states_115_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180415936)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180418048)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_115_cast = layer_norm(axes = hidden_states_115_axes_0, beta = vision_model_vision_model_encoder_layers_19_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_19_layer_norm1_weight_to_fp16, x = input_273_cast)[name = tensor<string, []>("hidden_states_115_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180420160))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181206656))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181206848)))];
            tensor<fp16, [1, 257, 1024]> var_1660_cast = linear(bias = vision_model_vision_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_115_cast)[name = tensor<string, []>("op_1660_cast")];
            tensor<fp16, []> var_1661_to_fp16 = const()[name = tensor<string, []>("op_1661_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_119_cast = mul(x = var_1660_cast, y = var_1661_to_fp16)[name = tensor<string, []>("tensor_119_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181208960))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181995456))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181995648)))];
            tensor<fp16, [1, 257, 1024]> tensor_115_cast = linear(bias = vision_model_vision_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_115_cast")];
            tensor<int32, [4]> var_1666 = const()[name = tensor<string, []>("op_1666"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1667_cast = reshape(shape = var_1666, x = tensor_115_cast)[name = tensor<string, []>("op_1667_cast")];
            tensor<int32, [4]> var_1668_perm_0 = const()[name = tensor<string, []>("op_1668_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181997760))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182784256))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182784448)))];
            tensor<fp16, [1, 257, 1024]> tensor_117_cast = linear(bias = vision_model_vision_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_117_cast")];
            tensor<int32, [4]> var_1673 = const()[name = tensor<string, []>("op_1673"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1674_cast = reshape(shape = var_1673, x = tensor_117_cast)[name = tensor<string, []>("op_1674_cast")];
            tensor<int32, [4]> var_1675_perm_0 = const()[name = tensor<string, []>("op_1675_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1682 = const()[name = tensor<string, []>("op_1682"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1683_cast = reshape(shape = var_1682, x = tensor_119_cast)[name = tensor<string, []>("op_1683_cast")];
            tensor<int32, [4]> var_1684_perm_0 = const()[name = tensor<string, []>("op_1684_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1686 = const()[name = tensor<string, []>("op_1686"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_24 = transpose(perm = var_1684_perm_0, x = var_1683_cast)[name = tensor<string, []>("transpose_24")];
            tensor<fp16, [16, 257, 64]> query_states_39_cast = reshape(shape = var_1686, x = transpose_24)[name = tensor<string, []>("query_states_39_cast")];
            tensor<int32, [3]> var_1688 = const()[name = tensor<string, []>("op_1688"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_23 = transpose(perm = var_1668_perm_0, x = var_1667_cast)[name = tensor<string, []>("transpose_23")];
            tensor<fp16, [16, 257, 64]> key_states_79_cast = reshape(shape = var_1688, x = transpose_23)[name = tensor<string, []>("key_states_79_cast")];
            tensor<int32, [3]> var_1690 = const()[name = tensor<string, []>("op_1690"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_22 = transpose(perm = var_1675_perm_0, x = var_1674_cast)[name = tensor<string, []>("transpose_22")];
            tensor<fp16, [16, 257, 64]> value_states_79_cast = reshape(shape = var_1690, x = transpose_22)[name = tensor<string, []>("value_states_79_cast")];
            tensor<int32, [3]> var_1692_perm_0 = const()[name = tensor<string, []>("op_1692_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_77_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_77_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_77_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_77_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_21 = transpose(perm = var_1692_perm_0, x = key_states_79_cast)[name = tensor<string, []>("transpose_21")];
            tensor<fp16, [16, 257, 257]> attn_weights_77_cast = matmul(transpose_x = attn_weights_77_transpose_x_0, transpose_y = attn_weights_77_transpose_y_0, x = query_states_39_cast, y = transpose_21)[name = tensor<string, []>("attn_weights_77_cast")];
            tensor<fp16, [16, 257, 257]> input_275_cast = softmax(axis = var_10, x = attn_weights_77_cast)[name = tensor<string, []>("input_275_cast")];
            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, [16, 257, 64]> attn_output_115_cast = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_275_cast, y = value_states_79_cast)[name = tensor<string, []>("attn_output_115_cast")];
            tensor<int32, [4]> var_1697 = const()[name = tensor<string, []>("op_1697"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_117_cast = reshape(shape = var_1697, x = attn_output_115_cast)[name = tensor<string, []>("attn_output_117_cast")];
            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_1700 = const()[name = tensor<string, []>("op_1700"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_20 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast)[name = tensor<string, []>("transpose_20")];
            tensor<fp16, [1, 257, 1024]> input_277_cast = reshape(shape = var_1700, x = transpose_20)[name = tensor<string, []>("input_277_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182786560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183573056))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183573248)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_117_cast = linear(bias = vision_model_vision_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized, x = input_277_cast)[name = tensor<string, []>("hidden_states_117_cast")];
            tensor<fp16, [1, 257, 1024]> input_279_cast = add(x = input_273_cast, y = hidden_states_117_cast)[name = tensor<string, []>("input_279_cast")];
            tensor<int32, [1]> input_281_axes_0 = const()[name = tensor<string, []>("input_281_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183575360)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183577472)))];
            tensor<fp16, [1, 257, 1024]> input_281_cast = layer_norm(axes = input_281_axes_0, beta = vision_model_vision_model_encoder_layers_19_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_19_layer_norm2_weight_to_fp16, x = input_279_cast)[name = tensor<string, []>("input_281_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183579584))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186725376))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186725568))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186728704))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_283_cast = linear(bias = vision_model_vision_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized, x = input_281_cast)[name = tensor<string, []>("input_283_cast")];
            tensor<fp16, []> var_1715_to_fp16 = const()[name = tensor<string, []>("op_1715_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1716_cast = mul(x = input_283_cast, y = var_1715_to_fp16)[name = tensor<string, []>("op_1716_cast")];
            tensor<fp16, [1, 257, 4096]> var_1717_cast = sigmoid(x = var_1716_cast)[name = tensor<string, []>("op_1717_cast")];
            tensor<fp16, [1, 257, 4096]> input_285_cast = mul(x = input_283_cast, y = var_1717_cast)[name = tensor<string, []>("input_285_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186728896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189874688))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189874880)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_119_cast = linear(bias = vision_model_vision_model_encoder_layers_19_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized, x = input_285_cast)[name = tensor<string, []>("hidden_states_119_cast")];
            tensor<fp16, [1, 257, 1024]> input_287_cast = add(x = input_279_cast, y = hidden_states_119_cast)[name = tensor<string, []>("input_287_cast")];
            tensor<int32, [1]> hidden_states_121_axes_0 = const()[name = tensor<string, []>("hidden_states_121_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189876992)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189879104)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_121_cast = layer_norm(axes = hidden_states_121_axes_0, beta = vision_model_vision_model_encoder_layers_20_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_20_layer_norm1_weight_to_fp16, x = input_287_cast)[name = tensor<string, []>("hidden_states_121_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(189881216))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190667712))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190667904)))];
            tensor<fp16, [1, 257, 1024]> var_1741_cast = linear(bias = vision_model_vision_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_121_cast)[name = tensor<string, []>("op_1741_cast")];
            tensor<fp16, []> var_1742_to_fp16 = const()[name = tensor<string, []>("op_1742_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_125_cast = mul(x = var_1741_cast, y = var_1742_to_fp16)[name = tensor<string, []>("tensor_125_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190670016))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(191456512))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(191456704)))];
            tensor<fp16, [1, 257, 1024]> tensor_121_cast = linear(bias = vision_model_vision_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_121_cast")];
            tensor<int32, [4]> var_1747 = const()[name = tensor<string, []>("op_1747"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1748_cast = reshape(shape = var_1747, x = tensor_121_cast)[name = tensor<string, []>("op_1748_cast")];
            tensor<int32, [4]> var_1749_perm_0 = const()[name = tensor<string, []>("op_1749_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(191458816))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192245312))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192245504)))];
            tensor<fp16, [1, 257, 1024]> tensor_123_cast = linear(bias = vision_model_vision_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_123_cast")];
            tensor<int32, [4]> var_1754 = const()[name = tensor<string, []>("op_1754"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1755_cast = reshape(shape = var_1754, x = tensor_123_cast)[name = tensor<string, []>("op_1755_cast")];
            tensor<int32, [4]> var_1756_perm_0 = const()[name = tensor<string, []>("op_1756_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1763 = const()[name = tensor<string, []>("op_1763"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1764_cast = reshape(shape = var_1763, x = tensor_125_cast)[name = tensor<string, []>("op_1764_cast")];
            tensor<int32, [4]> var_1765_perm_0 = const()[name = tensor<string, []>("op_1765_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1767 = const()[name = tensor<string, []>("op_1767"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_19 = transpose(perm = var_1765_perm_0, x = var_1764_cast)[name = tensor<string, []>("transpose_19")];
            tensor<fp16, [16, 257, 64]> query_states_41_cast = reshape(shape = var_1767, x = transpose_19)[name = tensor<string, []>("query_states_41_cast")];
            tensor<int32, [3]> var_1769 = const()[name = tensor<string, []>("op_1769"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_18 = transpose(perm = var_1749_perm_0, x = var_1748_cast)[name = tensor<string, []>("transpose_18")];
            tensor<fp16, [16, 257, 64]> key_states_83_cast = reshape(shape = var_1769, x = transpose_18)[name = tensor<string, []>("key_states_83_cast")];
            tensor<int32, [3]> var_1771 = const()[name = tensor<string, []>("op_1771"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_17 = transpose(perm = var_1756_perm_0, x = var_1755_cast)[name = tensor<string, []>("transpose_17")];
            tensor<fp16, [16, 257, 64]> value_states_83_cast = reshape(shape = var_1771, x = transpose_17)[name = tensor<string, []>("value_states_83_cast")];
            tensor<int32, [3]> var_1773_perm_0 = const()[name = tensor<string, []>("op_1773_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_81_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_81_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_81_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_81_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_16 = transpose(perm = var_1773_perm_0, x = key_states_83_cast)[name = tensor<string, []>("transpose_16")];
            tensor<fp16, [16, 257, 257]> attn_weights_81_cast = matmul(transpose_x = attn_weights_81_transpose_x_0, transpose_y = attn_weights_81_transpose_y_0, x = query_states_41_cast, y = transpose_16)[name = tensor<string, []>("attn_weights_81_cast")];
            tensor<fp16, [16, 257, 257]> input_289_cast = softmax(axis = var_10, x = attn_weights_81_cast)[name = tensor<string, []>("input_289_cast")];
            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, [16, 257, 64]> attn_output_121_cast = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_289_cast, y = value_states_83_cast)[name = tensor<string, []>("attn_output_121_cast")];
            tensor<int32, [4]> var_1778 = const()[name = tensor<string, []>("op_1778"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_123_cast = reshape(shape = var_1778, x = attn_output_121_cast)[name = tensor<string, []>("attn_output_123_cast")];
            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_1781 = const()[name = tensor<string, []>("op_1781"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_15 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast)[name = tensor<string, []>("transpose_15")];
            tensor<fp16, [1, 257, 1024]> input_291_cast = reshape(shape = var_1781, x = transpose_15)[name = tensor<string, []>("input_291_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192247616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193034112))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193034304)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_123_cast = linear(bias = vision_model_vision_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized, x = input_291_cast)[name = tensor<string, []>("hidden_states_123_cast")];
            tensor<fp16, [1, 257, 1024]> input_293_cast = add(x = input_287_cast, y = hidden_states_123_cast)[name = tensor<string, []>("input_293_cast")];
            tensor<int32, [1]> input_295_axes_0 = const()[name = tensor<string, []>("input_295_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193036416)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193038528)))];
            tensor<fp16, [1, 257, 1024]> input_295_cast = layer_norm(axes = input_295_axes_0, beta = vision_model_vision_model_encoder_layers_20_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_20_layer_norm2_weight_to_fp16, x = input_293_cast)[name = tensor<string, []>("input_295_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193040640))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196186432))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196186624))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196189760))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_297_cast = linear(bias = vision_model_vision_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized, x = input_295_cast)[name = tensor<string, []>("input_297_cast")];
            tensor<fp16, []> var_1796_to_fp16 = const()[name = tensor<string, []>("op_1796_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1797_cast = mul(x = input_297_cast, y = var_1796_to_fp16)[name = tensor<string, []>("op_1797_cast")];
            tensor<fp16, [1, 257, 4096]> var_1798_cast = sigmoid(x = var_1797_cast)[name = tensor<string, []>("op_1798_cast")];
            tensor<fp16, [1, 257, 4096]> input_299_cast = mul(x = input_297_cast, y = var_1798_cast)[name = tensor<string, []>("input_299_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196189952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199335744))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199335936)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_125_cast = linear(bias = vision_model_vision_model_encoder_layers_20_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized, x = input_299_cast)[name = tensor<string, []>("hidden_states_125_cast")];
            tensor<fp16, [1, 257, 1024]> input_301_cast = add(x = input_293_cast, y = hidden_states_125_cast)[name = tensor<string, []>("input_301_cast")];
            tensor<int32, [1]> hidden_states_127_axes_0 = const()[name = tensor<string, []>("hidden_states_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199338048)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199340160)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_127_cast = layer_norm(axes = hidden_states_127_axes_0, beta = vision_model_vision_model_encoder_layers_21_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_21_layer_norm1_weight_to_fp16, x = input_301_cast)[name = tensor<string, []>("hidden_states_127_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199342272))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200128768))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200128960)))];
            tensor<fp16, [1, 257, 1024]> var_1822_cast = linear(bias = vision_model_vision_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_127_cast)[name = tensor<string, []>("op_1822_cast")];
            tensor<fp16, []> var_1823_to_fp16 = const()[name = tensor<string, []>("op_1823_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_131_cast = mul(x = var_1822_cast, y = var_1823_to_fp16)[name = tensor<string, []>("tensor_131_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200131072))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200917568))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200917760)))];
            tensor<fp16, [1, 257, 1024]> tensor_127_cast = linear(bias = vision_model_vision_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_127_cast")];
            tensor<int32, [4]> var_1828 = const()[name = tensor<string, []>("op_1828"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1829_cast = reshape(shape = var_1828, x = tensor_127_cast)[name = tensor<string, []>("op_1829_cast")];
            tensor<int32, [4]> var_1830_perm_0 = const()[name = tensor<string, []>("op_1830_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200919872))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201706368))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201706560)))];
            tensor<fp16, [1, 257, 1024]> tensor_129_cast = linear(bias = vision_model_vision_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_129_cast")];
            tensor<int32, [4]> var_1835 = const()[name = tensor<string, []>("op_1835"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1836_cast = reshape(shape = var_1835, x = tensor_129_cast)[name = tensor<string, []>("op_1836_cast")];
            tensor<int32, [4]> var_1837_perm_0 = const()[name = tensor<string, []>("op_1837_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1844 = const()[name = tensor<string, []>("op_1844"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1845_cast = reshape(shape = var_1844, x = tensor_131_cast)[name = tensor<string, []>("op_1845_cast")];
            tensor<int32, [4]> var_1846_perm_0 = const()[name = tensor<string, []>("op_1846_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1848 = const()[name = tensor<string, []>("op_1848"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_14 = transpose(perm = var_1846_perm_0, x = var_1845_cast)[name = tensor<string, []>("transpose_14")];
            tensor<fp16, [16, 257, 64]> query_states_43_cast = reshape(shape = var_1848, x = transpose_14)[name = tensor<string, []>("query_states_43_cast")];
            tensor<int32, [3]> var_1850 = const()[name = tensor<string, []>("op_1850"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_13 = transpose(perm = var_1830_perm_0, x = var_1829_cast)[name = tensor<string, []>("transpose_13")];
            tensor<fp16, [16, 257, 64]> key_states_87_cast = reshape(shape = var_1850, x = transpose_13)[name = tensor<string, []>("key_states_87_cast")];
            tensor<int32, [3]> var_1852 = const()[name = tensor<string, []>("op_1852"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_12 = transpose(perm = var_1837_perm_0, x = var_1836_cast)[name = tensor<string, []>("transpose_12")];
            tensor<fp16, [16, 257, 64]> value_states_87_cast = reshape(shape = var_1852, x = transpose_12)[name = tensor<string, []>("value_states_87_cast")];
            tensor<int32, [3]> var_1854_perm_0 = const()[name = tensor<string, []>("op_1854_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_85_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_85_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_11 = transpose(perm = var_1854_perm_0, x = key_states_87_cast)[name = tensor<string, []>("transpose_11")];
            tensor<fp16, [16, 257, 257]> attn_weights_85_cast = matmul(transpose_x = attn_weights_85_transpose_x_0, transpose_y = attn_weights_85_transpose_y_0, x = query_states_43_cast, y = transpose_11)[name = tensor<string, []>("attn_weights_85_cast")];
            tensor<fp16, [16, 257, 257]> input_303_cast = softmax(axis = var_10, x = attn_weights_85_cast)[name = tensor<string, []>("input_303_cast")];
            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, [16, 257, 64]> attn_output_127_cast = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_303_cast, y = value_states_87_cast)[name = tensor<string, []>("attn_output_127_cast")];
            tensor<int32, [4]> var_1859 = const()[name = tensor<string, []>("op_1859"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_129_cast = reshape(shape = var_1859, x = attn_output_127_cast)[name = tensor<string, []>("attn_output_129_cast")];
            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_1862 = const()[name = tensor<string, []>("op_1862"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_10 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast)[name = tensor<string, []>("transpose_10")];
            tensor<fp16, [1, 257, 1024]> input_305_cast = reshape(shape = var_1862, x = transpose_10)[name = tensor<string, []>("input_305_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201708672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202495168))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202495360)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_129_cast = linear(bias = vision_model_vision_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized, x = input_305_cast)[name = tensor<string, []>("hidden_states_129_cast")];
            tensor<fp16, [1, 257, 1024]> input_307_cast = add(x = input_301_cast, y = hidden_states_129_cast)[name = tensor<string, []>("input_307_cast")];
            tensor<int32, [1]> input_309_axes_0 = const()[name = tensor<string, []>("input_309_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202497472)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202499584)))];
            tensor<fp16, [1, 257, 1024]> input_309_cast = layer_norm(axes = input_309_axes_0, beta = vision_model_vision_model_encoder_layers_21_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_21_layer_norm2_weight_to_fp16, x = input_307_cast)[name = tensor<string, []>("input_309_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(202501696))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205647488))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205647680))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205650816))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_311_cast = linear(bias = vision_model_vision_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized, x = input_309_cast)[name = tensor<string, []>("input_311_cast")];
            tensor<fp16, []> var_1877_to_fp16 = const()[name = tensor<string, []>("op_1877_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1878_cast = mul(x = input_311_cast, y = var_1877_to_fp16)[name = tensor<string, []>("op_1878_cast")];
            tensor<fp16, [1, 257, 4096]> var_1879_cast = sigmoid(x = var_1878_cast)[name = tensor<string, []>("op_1879_cast")];
            tensor<fp16, [1, 257, 4096]> input_313_cast = mul(x = input_311_cast, y = var_1879_cast)[name = tensor<string, []>("input_313_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205651008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208796800))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208796992)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_131_cast = linear(bias = vision_model_vision_model_encoder_layers_21_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized, x = input_313_cast)[name = tensor<string, []>("hidden_states_131_cast")];
            tensor<fp16, [1, 257, 1024]> input_315_cast = add(x = input_307_cast, y = hidden_states_131_cast)[name = tensor<string, []>("input_315_cast")];
            tensor<int32, [1]> hidden_states_133_axes_0 = const()[name = tensor<string, []>("hidden_states_133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208799104)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208801216)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_133_cast = layer_norm(axes = hidden_states_133_axes_0, beta = vision_model_vision_model_encoder_layers_22_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_22_layer_norm1_weight_to_fp16, x = input_315_cast)[name = tensor<string, []>("hidden_states_133_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208803328))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209589824))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209590016)))];
            tensor<fp16, [1, 257, 1024]> var_1903_cast = linear(bias = vision_model_vision_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_133_cast)[name = tensor<string, []>("op_1903_cast")];
            tensor<fp16, []> var_1904_to_fp16 = const()[name = tensor<string, []>("op_1904_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_137_cast = mul(x = var_1903_cast, y = var_1904_to_fp16)[name = tensor<string, []>("tensor_137_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209592128))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210378624))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210378816)))];
            tensor<fp16, [1, 257, 1024]> tensor_133_cast = linear(bias = vision_model_vision_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_133_cast")];
            tensor<int32, [4]> var_1909 = const()[name = tensor<string, []>("op_1909"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1910_cast = reshape(shape = var_1909, x = tensor_133_cast)[name = tensor<string, []>("op_1910_cast")];
            tensor<int32, [4]> var_1911_perm_0 = const()[name = tensor<string, []>("op_1911_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210380928))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211167424))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211167616)))];
            tensor<fp16, [1, 257, 1024]> tensor_135_cast = linear(bias = vision_model_vision_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_135_cast")];
            tensor<int32, [4]> var_1916 = const()[name = tensor<string, []>("op_1916"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1917_cast = reshape(shape = var_1916, x = tensor_135_cast)[name = tensor<string, []>("op_1917_cast")];
            tensor<int32, [4]> var_1918_perm_0 = const()[name = tensor<string, []>("op_1918_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1925 = const()[name = tensor<string, []>("op_1925"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1926_cast = reshape(shape = var_1925, x = tensor_137_cast)[name = tensor<string, []>("op_1926_cast")];
            tensor<int32, [4]> var_1927_perm_0 = const()[name = tensor<string, []>("op_1927_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1929 = const()[name = tensor<string, []>("op_1929"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_9 = transpose(perm = var_1927_perm_0, x = var_1926_cast)[name = tensor<string, []>("transpose_9")];
            tensor<fp16, [16, 257, 64]> query_states_45_cast = reshape(shape = var_1929, x = transpose_9)[name = tensor<string, []>("query_states_45_cast")];
            tensor<int32, [3]> var_1931 = const()[name = tensor<string, []>("op_1931"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_8 = transpose(perm = var_1911_perm_0, x = var_1910_cast)[name = tensor<string, []>("transpose_8")];
            tensor<fp16, [16, 257, 64]> key_states_91_cast = reshape(shape = var_1931, x = transpose_8)[name = tensor<string, []>("key_states_91_cast")];
            tensor<int32, [3]> var_1933 = const()[name = tensor<string, []>("op_1933"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_7 = transpose(perm = var_1918_perm_0, x = var_1917_cast)[name = tensor<string, []>("transpose_7")];
            tensor<fp16, [16, 257, 64]> value_states_91_cast = reshape(shape = var_1933, x = transpose_7)[name = tensor<string, []>("value_states_91_cast")];
            tensor<int32, [3]> var_1935_perm_0 = const()[name = tensor<string, []>("op_1935_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_89_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_89_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_89_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_89_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_6 = transpose(perm = var_1935_perm_0, x = key_states_91_cast)[name = tensor<string, []>("transpose_6")];
            tensor<fp16, [16, 257, 257]> attn_weights_89_cast = matmul(transpose_x = attn_weights_89_transpose_x_0, transpose_y = attn_weights_89_transpose_y_0, x = query_states_45_cast, y = transpose_6)[name = tensor<string, []>("attn_weights_89_cast")];
            tensor<fp16, [16, 257, 257]> input_317_cast = softmax(axis = var_10, x = attn_weights_89_cast)[name = tensor<string, []>("input_317_cast")];
            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, [16, 257, 64]> attn_output_133_cast = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_317_cast, y = value_states_91_cast)[name = tensor<string, []>("attn_output_133_cast")];
            tensor<int32, [4]> var_1940 = const()[name = tensor<string, []>("op_1940"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_135_cast = reshape(shape = var_1940, x = attn_output_133_cast)[name = tensor<string, []>("attn_output_135_cast")];
            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_1943 = const()[name = tensor<string, []>("op_1943"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_5 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast)[name = tensor<string, []>("transpose_5")];
            tensor<fp16, [1, 257, 1024]> input_319_cast = reshape(shape = var_1943, x = transpose_5)[name = tensor<string, []>("input_319_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211169728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211956224))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211956416)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_135_cast = linear(bias = vision_model_vision_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized, x = input_319_cast)[name = tensor<string, []>("hidden_states_135_cast")];
            tensor<fp16, [1, 257, 1024]> input_321_cast = add(x = input_315_cast, y = hidden_states_135_cast)[name = tensor<string, []>("input_321_cast")];
            tensor<int32, [1]> input_323_axes_0 = const()[name = tensor<string, []>("input_323_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211958528)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211960640)))];
            tensor<fp16, [1, 257, 1024]> input_323_cast = layer_norm(axes = input_323_axes_0, beta = vision_model_vision_model_encoder_layers_22_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_22_layer_norm2_weight_to_fp16, x = input_321_cast)[name = tensor<string, []>("input_323_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211962752))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215108544))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215108736))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215111872))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_325_cast = linear(bias = vision_model_vision_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized, x = input_323_cast)[name = tensor<string, []>("input_325_cast")];
            tensor<fp16, []> var_1958_to_fp16 = const()[name = tensor<string, []>("op_1958_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_1959_cast = mul(x = input_325_cast, y = var_1958_to_fp16)[name = tensor<string, []>("op_1959_cast")];
            tensor<fp16, [1, 257, 4096]> var_1960_cast = sigmoid(x = var_1959_cast)[name = tensor<string, []>("op_1960_cast")];
            tensor<fp16, [1, 257, 4096]> input_327_cast = mul(x = input_325_cast, y = var_1960_cast)[name = tensor<string, []>("input_327_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215112064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218257856))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218258048)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_137_cast = linear(bias = vision_model_vision_model_encoder_layers_22_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized, x = input_327_cast)[name = tensor<string, []>("hidden_states_137_cast")];
            tensor<fp16, [1, 257, 1024]> input_329_cast = add(x = input_321_cast, y = hidden_states_137_cast)[name = tensor<string, []>("input_329_cast")];
            tensor<int32, [1]> hidden_states_139_axes_0 = const()[name = tensor<string, []>("hidden_states_139_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218260160)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218262272)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_139_cast = layer_norm(axes = hidden_states_139_axes_0, beta = vision_model_vision_model_encoder_layers_23_layer_norm1_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_23_layer_norm1_weight_to_fp16, x = input_329_cast)[name = tensor<string, []>("hidden_states_139_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218264384))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219050880))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219051072)))];
            tensor<fp16, [1, 257, 1024]> var_1984_cast = linear(bias = vision_model_vision_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_139_cast)[name = tensor<string, []>("op_1984_cast")];
            tensor<fp16, []> var_1985_to_fp16 = const()[name = tensor<string, []>("op_1985_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 257, 1024]> tensor_cast = mul(x = var_1984_cast, y = var_1985_to_fp16)[name = tensor<string, []>("tensor_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219053184))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219839680))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219839872)))];
            tensor<fp16, [1, 257, 1024]> tensor_139_cast = linear(bias = vision_model_vision_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_139_cast")];
            tensor<int32, [4]> var_1990 = const()[name = tensor<string, []>("op_1990"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1991_cast = reshape(shape = var_1990, x = tensor_139_cast)[name = tensor<string, []>("op_1991_cast")];
            tensor<int32, [4]> var_1992_perm_0 = const()[name = tensor<string, []>("op_1992_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219841984))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220628480))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220628672)))];
            tensor<fp16, [1, 257, 1024]> tensor_141_cast = linear(bias = vision_model_vision_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_141_cast")];
            tensor<int32, [4]> var_1997 = const()[name = tensor<string, []>("op_1997"), val = tensor<int32, [4]>([1, -1, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_1998_cast = reshape(shape = var_1997, x = tensor_141_cast)[name = tensor<string, []>("op_1998_cast")];
            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, [4]> var_2006 = const()[name = tensor<string, []>("op_2006"), val = tensor<int32, [4]>([1, 257, 16, 64])];
            tensor<fp16, [1, 257, 16, 64]> var_2007_cast = reshape(shape = var_2006, x = tensor_cast)[name = tensor<string, []>("op_2007_cast")];
            tensor<int32, [4]> var_2008_perm_0 = const()[name = tensor<string, []>("op_2008_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2010 = const()[name = tensor<string, []>("op_2010"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_4 = transpose(perm = var_2008_perm_0, x = var_2007_cast)[name = tensor<string, []>("transpose_4")];
            tensor<fp16, [16, 257, 64]> query_states_cast = reshape(shape = var_2010, x = transpose_4)[name = tensor<string, []>("query_states_cast")];
            tensor<int32, [3]> var_2012 = const()[name = tensor<string, []>("op_2012"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_3 = transpose(perm = var_1992_perm_0, x = var_1991_cast)[name = tensor<string, []>("transpose_3")];
            tensor<fp16, [16, 257, 64]> key_states_cast = reshape(shape = var_2012, x = transpose_3)[name = tensor<string, []>("key_states_cast")];
            tensor<int32, [3]> var_2014 = const()[name = tensor<string, []>("op_2014"), val = tensor<int32, [3]>([16, -1, 64])];
            tensor<fp16, [1, 16, 257, 64]> transpose_2 = transpose(perm = var_1999_perm_0, x = var_1998_cast)[name = tensor<string, []>("transpose_2")];
            tensor<fp16, [16, 257, 64]> value_states_cast = reshape(shape = var_2014, x = transpose_2)[name = tensor<string, []>("value_states_cast")];
            tensor<int32, [3]> var_2016_perm_0 = const()[name = tensor<string, []>("op_2016_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_93_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_93_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_93_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_93_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [16, 64, 257]> transpose_1 = transpose(perm = var_2016_perm_0, x = key_states_cast)[name = tensor<string, []>("transpose_1")];
            tensor<fp16, [16, 257, 257]> attn_weights_93_cast = matmul(transpose_x = attn_weights_93_transpose_x_0, transpose_y = attn_weights_93_transpose_y_0, x = query_states_cast, y = transpose_1)[name = tensor<string, []>("attn_weights_93_cast")];
            tensor<fp16, [16, 257, 257]> input_331_cast = softmax(axis = var_10, x = attn_weights_93_cast)[name = tensor<string, []>("input_331_cast")];
            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, [16, 257, 64]> attn_output_139_cast = matmul(transpose_x = attn_output_139_transpose_x_0, transpose_y = attn_output_139_transpose_y_0, x = input_331_cast, y = value_states_cast)[name = tensor<string, []>("attn_output_139_cast")];
            tensor<int32, [4]> var_2021 = const()[name = tensor<string, []>("op_2021"), val = tensor<int32, [4]>([1, 16, 257, 64])];
            tensor<fp16, [1, 16, 257, 64]> attn_output_141_cast = reshape(shape = var_2021, x = attn_output_139_cast)[name = tensor<string, []>("attn_output_141_cast")];
            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_2024 = const()[name = tensor<string, []>("op_2024"), val = tensor<int32, [3]>([1, 257, 1024])];
            tensor<fp16, [1, 257, 16, 64]> transpose_0 = transpose(perm = attn_output_perm_0, x = attn_output_141_cast)[name = tensor<string, []>("transpose_0")];
            tensor<fp16, [1, 257, 1024]> input_333_cast = reshape(shape = var_2024, x = transpose_0)[name = tensor<string, []>("input_333_cast")];
            tensor<fp16, [1024, 1024]> vision_model_vision_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [786432]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(220630784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221417280))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 1024])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221417472)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_141_cast = linear(bias = vision_model_vision_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized, x = input_333_cast)[name = tensor<string, []>("hidden_states_141_cast")];
            tensor<fp16, [1, 257, 1024]> input_335_cast = add(x = input_329_cast, y = hidden_states_141_cast)[name = tensor<string, []>("input_335_cast")];
            tensor<int32, [1]> input_337_axes_0 = const()[name = tensor<string, []>("input_337_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221419584)))];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221421696)))];
            tensor<fp16, [1, 257, 1024]> input_337_cast = layer_norm(axes = input_337_axes_0, beta = vision_model_vision_model_encoder_layers_23_layer_norm2_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_encoder_layers_23_layer_norm2_weight_to_fp16, x = input_335_cast)[name = tensor<string, []>("input_337_cast")];
            tensor<fp16, [4096, 1024]> vision_model_vision_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221423808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224569600))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([4096, 1024])];
            tensor<fp16, [4096]> vision_model_vision_model_encoder_layers_23_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224569792))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224572928))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_mlp_fc1_bias_to_fp16_palettized"), shape = tensor<uint32, [1]>([4096])];
            tensor<fp16, [1, 257, 4096]> input_339_cast = linear(bias = vision_model_vision_model_encoder_layers_23_mlp_fc1_bias_to_fp16_palettized, weight = vision_model_vision_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized, x = input_337_cast)[name = tensor<string, []>("input_339_cast")];
            tensor<fp16, []> var_2039_to_fp16 = const()[name = tensor<string, []>("op_2039_to_fp16"), val = tensor<fp16, []>(0x1.b3cp+0)];
            tensor<fp16, [1, 257, 4096]> var_2040_cast = mul(x = input_339_cast, y = var_2039_to_fp16)[name = tensor<string, []>("op_2040_cast")];
            tensor<fp16, [1, 257, 4096]> var_2041_cast = sigmoid(x = var_2040_cast)[name = tensor<string, []>("op_2041_cast")];
            tensor<fp16, [1, 257, 4096]> input_341_cast = mul(x = input_339_cast, y = var_2041_cast)[name = tensor<string, []>("input_341_cast")];
            tensor<fp16, [1024, 4096]> vision_model_vision_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [3145728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224573120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227718912))), name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1024, 4096])];
            tensor<fp16, [1024]> vision_model_vision_model_encoder_layers_23_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_encoder_layers_23_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227719104)))];
            tensor<fp16, [1, 257, 1024]> hidden_states_cast = linear(bias = vision_model_vision_model_encoder_layers_23_mlp_fc2_bias_to_fp16, weight = vision_model_vision_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized, x = input_341_cast)[name = tensor<string, []>("hidden_states_cast")];
            tensor<fp16, [1, 257, 1024]> last_hidden_state_cast = add(x = input_335_cast, y = hidden_states_cast)[name = tensor<string, []>("last_hidden_state_cast")];
            tensor<int32, [3]> var_2048_begin_0 = const()[name = tensor<string, []>("op_2048_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> var_2048_end_0 = const()[name = tensor<string, []>("op_2048_end_0"), val = tensor<int32, [3]>([1, 1, 1024])];
            tensor<bool, [3]> var_2048_end_mask_0 = const()[name = tensor<string, []>("op_2048_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> var_2048_squeeze_mask_0 = const()[name = tensor<string, []>("op_2048_squeeze_mask_0"), val = tensor<bool, [3]>([false, true, false])];
            tensor<fp16, [1, 1024]> var_2048_cast = slice_by_index(begin = var_2048_begin_0, end = var_2048_end_0, end_mask = var_2048_end_mask_0, squeeze_mask = var_2048_squeeze_mask_0, x = last_hidden_state_cast)[name = tensor<string, []>("op_2048_cast")];
            tensor<int32, [1]> input_345_axes_0 = const()[name = tensor<string, []>("input_345_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> vision_model_vision_model_post_layernorm_weight_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_post_layernorm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227721216)))];
            tensor<fp16, [1024]> vision_model_vision_model_post_layernorm_bias_to_fp16 = const()[name = tensor<string, []>("vision_model_vision_model_post_layernorm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227723328)))];
            tensor<fp16, [1, 1024]> input_345_cast = layer_norm(axes = input_345_axes_0, beta = vision_model_vision_model_post_layernorm_bias_to_fp16, epsilon = var_19_to_fp16, gamma = vision_model_vision_model_post_layernorm_weight_to_fp16, x = var_2048_cast)[name = tensor<string, []>("input_345_cast")];
            tensor<fp16, [768, 1024]> visual_projection_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [589824]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227725440))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228315328))), name = tensor<string, []>("visual_projection_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([768, 1024])];
            tensor<fp16, [768]> input_347_bias_0_to_fp16 = const()[name = tensor<string, []>("input_347_bias_0_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228315520)))];
            tensor<fp16, [1, 768]> input_347_cast = linear(bias = input_347_bias_0_to_fp16, weight = visual_projection_weight_to_fp16_palettized, x = input_345_cast)[name = tensor<string, []>("input_347_cast")];
            tensor<int32, [1]> var_2059 = const()[name = tensor<string, []>("op_2059"), val = tensor<int32, [1]>([1])];
            tensor<bool, []> var_2060 = const()[name = tensor<string, []>("op_2060"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 768]> abs_0_cast = abs(x = input_347_cast)[name = tensor<string, []>("abs_0_cast")];
            tensor<fp16, []> const_73_to_fp16 = const()[name = tensor<string, []>("const_73_to_fp16"), val = tensor<fp16, []>(0x1p+1)];
            tensor<fp16, [1, 768]> pow_0_cast = pow(x = abs_0_cast, y = const_73_to_fp16)[name = tensor<string, []>("pow_0_cast")];
            tensor<fp16, [1, 1]> reduce_sum_0_cast = reduce_sum(axes = var_2059, keep_dims = var_2060, x = pow_0_cast)[name = tensor<string, []>("reduce_sum_0_cast")];
            tensor<fp16, []> var_2062_y_0_to_fp16 = const()[name = tensor<string, []>("op_2062_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 1]> var_2062_cast = pow(x = reduce_sum_0_cast, y = var_2062_y_0_to_fp16)[name = tensor<string, []>("op_2062_cast")];
            tensor<fp16, []> var_2063_to_fp16 = const()[name = tensor<string, []>("op_2063_to_fp16"), val = tensor<fp16, []>(0x1p-24)];
            tensor<fp16, []> var_2064_beta_0_to_fp16 = const()[name = tensor<string, []>("op_2064_beta_0_to_fp16"), val = tensor<fp16, []>(inf)];
            tensor<fp16, [1, 1]> var_2064_cast = clip(alpha = var_2063_to_fp16, beta = var_2064_beta_0_to_fp16, x = var_2062_cast)[name = tensor<string, []>("op_2064_cast")];
            tensor<int32, [2]> denom_1_reps_0 = const()[name = tensor<string, []>("denom_1_reps_0"), val = tensor<int32, [2]>([1, 768])];
            tensor<fp16, [1, 768]> denom_1_cast = tile(reps = denom_1_reps_0, x = var_2064_cast)[name = tensor<string, []>("denom_1_cast")];
            tensor<fp16, [1, 768]> var_2066_cast = real_div(x = input_347_cast, y = denom_1_cast)[name = tensor<string, []>("op_2066_cast")];
            tensor<fp16, [3, 768]> op_2106_weight_0_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1728]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228317120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228318912))), name = tensor<string, []>("op_2106_weight_0_to_fp16_palettized"), shape = tensor<uint32, [2]>([3, 768])];
            tensor<fp16, [3]> var_2106_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2106_bias_0_to_fp16"), val = tensor<fp16, [3]>([-0x1.8f4p-3, -0x1.998p-3, -0x1.c28p-3])];
            tensor<fp16, [1, 3]> var_2106_cast = linear(bias = var_2106_bias_0_to_fp16, weight = op_2106_weight_0_to_fp16_palettized, x = var_2066_cast)[name = tensor<string, []>("op_2106_cast")];
            tensor<fp16, [17, 768]> op_2141_weight_0_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [9792]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228319104))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228328960))), name = tensor<string, []>("op_2141_weight_0_to_fp16_palettized"), shape = tensor<uint32, [2]>([17, 768])];
            tensor<fp16, [17]> var_2141_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2141_bias_0_to_fp16"), val = tensor<fp16, [17]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228329152)))];
            tensor<fp16, [1, 17]> var_2141_cast = linear(bias = var_2141_bias_0_to_fp16, weight = op_2141_weight_0_to_fp16_palettized, x = var_2066_cast)[name = tensor<string, []>("op_2141_cast")];
            tensor<fp16, [1, 3]> special_scores_cast = add(x = var_2106_cast, y = adjustment)[name = tensor<string, []>("special_scores_cast")];
            tensor<fp16, []> var_2109_promoted_to_fp16 = const()[name = tensor<string, []>("op_2109_promoted_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<bool, [1, 3]> var_2110_cast = greater(x = special_scores_cast, y = var_2109_promoted_to_fp16)[name = tensor<string, []>("op_2110_cast")];
            tensor<int32, [1]> var_2117 = const()[name = tensor<string, []>("op_2117"), val = tensor<int32, [1]>([1])];
            tensor<bool, []> var_2118 = const()[name = tensor<string, []>("op_2118"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2115_to_fp16_dtype_0 = const()[name = tensor<string, []>("op_2115_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [1, 3]> cast_6 = cast(dtype = var_2115_to_fp16_dtype_0, x = var_2110_cast)[name = tensor<string, []>("cast_6")];
            tensor<fp16, [1]> var_2120_cast = reduce_sum(axes = var_2117, keep_dims = var_2118, x = cast_6)[name = tensor<string, []>("op_2120_cast")];
            tensor<fp16, []> var_2121_promoted_to_fp16 = const()[name = tensor<string, []>("op_2121_promoted_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<bool, [1]> var_2122_cast = greater(x = var_2120_cast, y = var_2121_promoted_to_fp16)[name = tensor<string, []>("op_2122_cast")];
            tensor<string, []> special_care_to_fp16_dtype_0 = const()[name = tensor<string, []>("special_care_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, []> var_2128_to_fp16 = const()[name = tensor<string, []>("op_2128_to_fp16"), val = tensor<fp16, []>(0x1.47cp-7)];
            tensor<fp16, [1]> cast_5 = cast(dtype = special_care_to_fp16_dtype_0, x = var_2122_cast)[name = tensor<string, []>("cast_5")];
            tensor<fp16, [1]> special_adjustment_1_cast = mul(x = cast_5, y = var_2128_to_fp16)[name = tensor<string, []>("special_adjustment_1_cast")];
            tensor<int32, [1]> var_2131_axes_0 = const()[name = tensor<string, []>("op_2131_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1]> var_2131_cast = expand_dims(axes = var_2131_axes_0, x = special_adjustment_1_cast)[name = tensor<string, []>("op_2131_cast")];
            tensor<int32, [2]> special_adjustment_reps_0 = const()[name = tensor<string, []>("special_adjustment_reps_0"), val = tensor<int32, [2]>([1, 17])];
            tensor<fp16, [1, 17]> special_adjustment_cast = tile(reps = special_adjustment_reps_0, x = var_2131_cast)[name = tensor<string, []>("special_adjustment_cast")];
            tensor<fp16, [1, 17]> concept_scores_cast = add(x = var_2141_cast, y = special_adjustment_cast)[name = tensor<string, []>("concept_scores_cast")];
            tensor<string, []> concept_scores_cast_to_fp32_dtype_0 = const()[name = tensor<string, []>("concept_scores_cast_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp16, []> var_2144_promoted_to_fp16 = const()[name = tensor<string, []>("op_2144_promoted_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<bool, [1, 17]> var_2145_cast = greater(x = concept_scores_cast, y = var_2144_promoted_to_fp16)[name = tensor<string, []>("op_2145_cast")];
            tensor<int32, [1]> var_2152 = const()[name = tensor<string, []>("op_2152"), val = tensor<int32, [1]>([1])];
            tensor<bool, []> var_2153 = const()[name = tensor<string, []>("op_2153"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2150_to_fp16_dtype_0 = const()[name = tensor<string, []>("op_2150_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [1, 17]> cast_4 = cast(dtype = var_2150_to_fp16_dtype_0, x = var_2145_cast)[name = tensor<string, []>("cast_4")];
            tensor<fp16, [1]> var_2155_cast = reduce_sum(axes = var_2152, keep_dims = var_2153, x = cast_4)[name = tensor<string, []>("op_2155_cast")];
            tensor<fp16, []> var_2156_promoted_to_fp16 = const()[name = tensor<string, []>("op_2156_promoted_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<bool, [1]> var_2157_cast = greater(x = var_2155_cast, y = var_2156_promoted_to_fp16)[name = tensor<string, []>("op_2157_cast")];
            tensor<int32, [1]> var_2164_axes_0 = const()[name = tensor<string, []>("op_2164_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1]> var_2164 = expand_dims(axes = var_2164_axes_0, x = var_2157_cast)[name = tensor<string, []>("op_2164")];
            tensor<int32, [1]> var_2166_axes_0 = const()[name = tensor<string, []>("op_2166_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<bool, [1, 1, 1]> var_2166 = expand_dims(axes = var_2166_axes_0, x = var_2164)[name = tensor<string, []>("op_2166")];
            tensor<int32, [1]> has_nsfw_concepts_axes_0 = const()[name = tensor<string, []>("has_nsfw_concepts_axes_0"), val = tensor<int32, [1]>([3])];
            tensor<bool, [1, 1, 1, 1]> has_nsfw_concepts_1 = expand_dims(axes = has_nsfw_concepts_axes_0, x = var_2166)[name = tensor<string, []>("has_nsfw_concepts")];
            tensor<int32, [4]> has_nsfw_concepts_after_broadcast_reps_0 = const()[name = tensor<string, []>("has_nsfw_concepts_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 512, 512, 3])];
            tensor<bool, [1, 512, 512, 3]> has_nsfw_concepts_after_broadcast = tile(reps = has_nsfw_concepts_after_broadcast_reps_0, x = has_nsfw_concepts_1)[name = tensor<string, []>("has_nsfw_concepts_after_broadcast")];
            tensor<string, []> cast_205_dtype_0 = const()[name = tensor<string, []>("cast_205_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1, 512, 512, 3]> cast_3 = cast(dtype = cast_205_dtype_0, x = has_nsfw_concepts_after_broadcast)[name = tensor<string, []>("cast_3")];
            tensor<int32, [?, 4]> non_zero_0 = non_zero(x = cast_3)[name = tensor<string, []>("non_zero_0")];
            tensor<int32, [2]> shape_1 = shape(x = non_zero_0)[name = tensor<string, []>("shape_1")];
            tensor<int32, [1]> slice_by_index_2_begin_0 = const()[name = tensor<string, []>("slice_by_index_2_begin_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> slice_by_index_2_end_0 = const()[name = tensor<string, []>("slice_by_index_2_end_0"), val = tensor<int32, [1]>([0])];
            tensor<bool, [1]> slice_by_index_2_squeeze_mask_0 = const()[name = tensor<string, []>("slice_by_index_2_squeeze_mask_0"), val = tensor<bool, [1]>([true])];
            tensor<int32, []> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, squeeze_mask = slice_by_index_2_squeeze_mask_0, x = shape_1)[name = tensor<string, []>("slice_by_index_2")];
            tensor<int32, [1]> expand_dims_2_axes_0 = const()[name = tensor<string, []>("expand_dims_2_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_2 = expand_dims(axes = expand_dims_2_axes_0, x = slice_by_index_2)[name = tensor<string, []>("expand_dims_2")];
            tensor<fp16, [1]> expand_dims_1_to_fp16 = const()[name = tensor<string, []>("expand_dims_1_to_fp16"), val = tensor<fp16, [1]>([0x0p+0])];
            tensor<fp16, [?]> tile_0_cast = tile(reps = expand_dims_2, x = expand_dims_1_to_fp16)[name = tensor<string, []>("tile_0_cast")];
            tensor<string, []> var_2176_mode_0 = const()[name = tensor<string, []>("op_2176_mode_0"), val = tensor<string, []>("update")];
            tensor<fp16, [1, 512, 512, 3]> var_2176_cast = scatter_nd(data = images, indices = non_zero_0, mode = var_2176_mode_0, updates = tile_0_cast)[name = tensor<string, []>("op_2176_cast")];
            tensor<string, []> var_2176_cast_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_2176_cast_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<string, []> var_2181_dtype_0 = const()[name = tensor<string, []>("op_2181_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 17]> concept_scores = cast(dtype = concept_scores_cast_to_fp32_dtype_0, x = concept_scores_cast)[name = tensor<string, []>("cast_0")];
            tensor<fp32, [1, 512, 512, 3]> filtered_images = cast(dtype = var_2176_cast_to_fp32_dtype_0, x = var_2176_cast)[name = tensor<string, []>("cast_1")];
            tensor<fp32, [1, 1, 1, 1]> has_nsfw_concepts = cast(dtype = var_2181_dtype_0, x = has_nsfw_concepts_1)[name = tensor<string, []>("cast_2")];
        } -> (filtered_images, has_nsfw_concepts, concept_scores);
}