7767517 1163 1275 pnnx.Input pnnx_input_0 0 1 0 pnnx.Input pnnx_input_10 0 1 1 pnnx.Input pnnx_input_11 0 1 2 pnnx.Input pnnx_input_12 0 1 3 pnnx.Input pnnx_input_13 0 1 4 pnnx.Input pnnx_input_14 0 1 5 pnnx.Input pnnx_input_15 0 1 6 pnnx.Input pnnx_input_16 0 1 7 pnnx.Input pnnx_input_17 0 1 8 pnnx.Input pnnx_input_18 0 1 9 pnnx.Input pnnx_input_19 0 1 10 pnnx.Input pnnx_input_110 0 1 11 pnnx.Input pnnx_input_111 0 1 12 pnnx.Input pnnx_input_112 0 1 13 pnnx.Input pnnx_input_113 0 1 14 pnnx.Input pnnx_input_114 0 1 15 pnnx.Input pnnx_input_115 0 1 16 pnnx.Input pnnx_input_116 0 1 17 pnnx.Input pnnx_input_117 0 1 18 pnnx.Input pnnx_input_118 0 1 19 pnnx.Input pnnx_input_119 0 1 20 pnnx.Input pnnx_input_120 0 1 21 pnnx.Input pnnx_input_121 0 1 22 pnnx.Input pnnx_input_122 0 1 23 pnnx.Input pnnx_input_123 0 1 24 pnnx.Input pnnx_input_124 0 1 25 pnnx.Input pnnx_input_125 0 1 26 pnnx.Input pnnx_input_126 0 1 27 pnnx.Input pnnx_input_127 0 1 28 pnnx.Input pnnx_input_128 0 1 29 pnnx.Input pnnx_input_129 0 1 30 pnnx.Input pnnx_input_130 0 1 31 pnnx.Input pnnx_input_131 0 1 32 pnnx.Input pnnx_input_132 0 1 33 pnnx.Input pnnx_input_133 0 1 34 pnnx.Input pnnx_input_134 0 1 35 pnnx.Input pnnx_input_135 0 1 36 pnnx.Input pnnx_input_136 0 1 37 pnnx.Input pnnx_input_137 0 1 38 pnnx.Input pnnx_input_138 0 1 39 pnnx.Input pnnx_input_139 0 1 40 pnnx.Input pnnx_input_140 0 1 41 pnnx.Input pnnx_input_141 0 1 42 pnnx.Input pnnx_input_142 0 1 43 pnnx.Input pnnx_input_143 0 1 44 pnnx.Input pnnx_input_144 0 1 45 pnnx.Input pnnx_input_145 0 1 46 pnnx.Input pnnx_input_146 0 1 47 pnnx.Input pnnx_input_147 0 1 48 pnnx.Input pnnx_input_148 0 1 49 pnnx.Input pnnx_input_149 0 1 50 pnnx.Input pnnx_input_150 0 1 51 pnnx.Input pnnx_input_151 0 1 52 pnnx.Input pnnx_input_152 0 1 53 pnnx.Input pnnx_input_153 0 1 54 pnnx.Input pnnx_input_154 0 1 55 pnnx.Input pnnx_input_155 0 1 56 pnnx.Input pnnx_input_156 0 1 57 pnnx.Input pnnx_input_157 0 1 58 pnnx.Input pnnx_input_158 0 1 59 pnnx.Input pnnx_input_159 0 1 60 pnnx.Input pnnx_input_160 0 1 61 pnnx.Input pnnx_input_161 0 1 62 pnnx.Input pnnx_input_162 0 1 63 pnnx.Input pnnx_input_163 0 1 64 torch.unsqueeze torch.unsqueeze_892 1 1 0 65 dim=1 $input=0 nn.Conv2d encoder_embed.conv.0 1 1 65 66 bias=True dilation=(1,1) groups=1 in_channels=1 kernel_size=(3,3) out_channels=8 padding=(1,1) padding_mode=zeros stride=(1,1) @bias=(8)f32 @weight=(8,1,3,3)f32 pnnx.Expression pnnx_expr_3071 1 1 66 67 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_16 1 1 67 68 $input=67 pnnx.Expression pnnx_expr_3070 2 1 66 68 69 expr=mul(@0,@1) nn.Conv2d encoder_embed.conv.3 1 1 69 70 bias=True dilation=(1,1) groups=1 in_channels=8 kernel_size=(3,3) out_channels=32 padding=(0,0) padding_mode=zeros stride=(2,2) @bias=(32)f32 @weight=(32,8,3,3)f32 pnnx.Expression pnnx_expr_3067 1 1 70 71 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_17 1 1 71 72 $input=71 pnnx.Expression pnnx_expr_3066 2 1 70 72 73 expr=mul(@0,@1) nn.Conv2d encoder_embed.conv.6 1 1 73 74 bias=True dilation=(1,1) groups=1 in_channels=32 kernel_size=(3,3) out_channels=128 padding=(0,0) padding_mode=zeros stride=(2,2) @bias=(128)f32 @weight=(128,32,3,3)f32 pnnx.Expression pnnx_expr_3063 1 1 74 75 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_18 1 1 75 76 $input=75 pnnx.Expression pnnx_expr_3062 2 1 74 76 77 expr=mul(@0,@1) torch.permute torch.permute_761 1 1 77 78 dims=(0,2,1,3) $input=77 Tensor.reshape Tensor.reshape_83 1 1 78 79 shape=(1,-1,2432) $input=78 nn.Linear encoder_embed.out 1 1 79 80 bias=True in_features=2432 out_features=144 @bias=(144)f32 @weight=(144,2432)f32 pnnx.Expression pnnx_expr_3053 1 1 80 81 expr=mul(@0,@0) torch.mean torch.mean_728 1 1 81 82 dim=(-1) keepdim=True $input=81 pnnx.Expression pnnx_expr_3049 2 1 80 82 83 expr=mul(@0,pow(add(@1,2.500004e-01),-5.000000e-01)) Tensor.slice slice_0 1 1 83 84 dims=(1) ends=(-1) starts=(1) steps=(1) $input=83 torch.permute torch.permute_762 1 1 84 85 dims=(1,0,2) $input=84 torch.tensor_split slice_2 1 2 85 86 87 dim=0 indices=(8) torch.cat torch.cat_568 2 1 87 86 88 dim=0 nn.Linear encoder.emformer_layers.0.feed_forward_macaron.0 1 1 88 89 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_3027 1 1 89 90 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_19 1 1 90 91 $input=90 pnnx.Expression pnnx_expr_3026 2 1 89 91 92 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.0.feed_forward_macaron.4 1 1 92 93 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_3024 2 1 88 93 94 expr=add(@0,@1) torch.tensor_split slice_4 1 2 94 95 96 dim=0 indices=(2) torch.cat torch.cat_569 2 1 95 96 97 dim=0 nn.Linear encoder.emformer_layers.0.attention.emb_to_query 1 1 97 98 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_570 3 1 1 95 96 99 dim=0 nn.Linear encoder.emformer_layers.0.attention.emb_to_key_value 1 1 99 100 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_712 1 2 100 101 102 chunks=2 dim=2 $input=100 Tensor.view Tensor.view_488 1 1 98 103 shape=(10,4,36) $input=98 torch.tensor_split slice_6 1 2 101 104 105 dim=0 indices=(34) torch.cat torch.cat_571 3 1 104 2 105 106 dim=0 Tensor.view Tensor.view_489 1 1 106 107 shape=(50,4,36) $input=106 torch.tensor_split slice_8 1 2 102 108 109 dim=0 indices=(34) torch.cat torch.cat_572 3 1 108 3 109 110 dim=0 Tensor.view Tensor.view_490 1 1 110 111 shape=(50,4,36) $input=110 torch.permute torch.permute_763 1 1 103 112 dims=(1,0,2) $input=103 pnnx.Expression pnnx_expr_2972 1 1 112 113 expr=mul(@0,1.666667e-01) torch.permute torch.permute_764 1 1 107 114 dims=(1,0,2) $input=107 torch.permute torch.permute_766 1 1 114 115 dims=(0,2,1) $input=114 torch.bmm torch.bmm_536 2 1 113 115 116 $input=113 $mat2=115 F.softmax F.softmax_67 1 1 116 117 dim=-1 $input=116 torch.permute torch.permute_765 1 1 111 118 dims=(1,0,2) $input=111 torch.bmm torch.bmm_537 2 1 117 118 119 $input=117 $mat2=118 torch.permute torch.permute_767 1 1 119 120 dims=(1,0,2) $input=119 Tensor.reshape Tensor.reshape_84 1 1 120 121 shape=(-1,144) $input=120 torch.unsqueeze torch.unsqueeze_893 1 1 121 122 dim=1 $input=121 nn.Linear encoder.emformer_layers.0.attention.out_proj 1 1 122 123 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_729 1 1 96 124 dim=(0) keepdim=True $input=96 pnnx.Expression pnnx_expr_2938 2 1 94 123 125 expr=add(@0,@1) torch.tensor_split slice_9 1 2 125 126 127 dim=0 indices=(2) torch.cat torch.cat_574 2 1 127 126 128 dim=0 torch.permute torch.permute_768 1 1 128 129 dims=(1,2,0) $input=128 nn.Conv1d encoder.emformer_layers.0.conv_module.pointwise_conv1 1 1 129 130 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_0 1 1 130 131 dim=1 $input=130 torch.cat torch.cat_575 2 1 4 131 132 dim=2 nn.Conv1d encoder.emformer_layers.0.conv_module.depthwise_conv 1 1 132 133 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_2910 1 1 133 134 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_20 1 1 134 135 $input=134 pnnx.Expression pnnx_expr_2909 2 1 133 135 136 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.0.conv_module.pointwise_conv2 1 1 136 137 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_11 1 2 137 138 139 dim=2 indices=(8) torch.permute torch.permute_770 1 1 139 140 dims=(2,0,1) $input=139 torch.permute torch.permute_769 1 1 138 141 dims=(2,0,1) $input=138 torch.cat torch.cat_576 2 1 140 141 142 dim=0 pnnx.Expression pnnx_expr_2874 2 1 125 142 143 expr=add(@0,@1) nn.Linear encoder.emformer_layers.0.feed_forward.0 1 1 143 144 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2871 1 1 144 145 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_21 1 1 145 146 $input=145 pnnx.Expression pnnx_expr_2870 2 1 144 146 147 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.0.feed_forward.4 1 1 147 148 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2868 2 1 143 148 149 expr=add(@0,@1) pnnx.Expression pnnx_expr_2863 1 1 149 150 expr=mul(@0,@0) torch.mean torch.mean_730 1 1 150 151 dim=(-1) keepdim=True $input=150 pnnx.Expression pnnx_expr_2859 2 1 149 151 152 expr=mul(@0,pow(add(@1,9.635315e-01),-5.000000e-01)) torch.tensor_split slice_13 1 2 152 153 154 dim=0 indices=(2) torch.cat torch.cat_577 2 1 153 154 155 dim=0 nn.Linear encoder.emformer_layers.1.feed_forward_macaron.0 1 1 155 156 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2847 1 1 156 157 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_22 1 1 157 158 $input=157 pnnx.Expression pnnx_expr_2846 2 1 156 158 159 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.1.feed_forward_macaron.4 1 1 159 160 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2844 2 1 155 160 161 expr=add(@0,@1) torch.tensor_split slice_16 1 2 161 162 163 dim=0 indices=(2) torch.cat torch.cat_578 2 1 162 163 164 dim=0 nn.Linear encoder.emformer_layers.1.attention.emb_to_query 1 1 164 165 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_579 3 1 5 162 163 166 dim=0 nn.Linear encoder.emformer_layers.1.attention.emb_to_key_value 1 1 166 167 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_713 1 2 167 168 169 chunks=2 dim=2 $input=167 Tensor.view Tensor.view_491 1 1 165 170 shape=(10,4,36) $input=165 torch.tensor_split slice_18 1 2 168 171 172 dim=0 indices=(34) torch.cat torch.cat_580 3 1 171 6 172 173 dim=0 Tensor.view Tensor.view_492 1 1 173 174 shape=(50,4,36) $input=173 torch.tensor_split slice_20 1 2 169 175 176 dim=0 indices=(34) torch.cat torch.cat_581 3 1 175 7 176 177 dim=0 Tensor.view Tensor.view_493 1 1 177 178 shape=(50,4,36) $input=177 torch.permute torch.permute_771 1 1 170 179 dims=(1,0,2) $input=170 pnnx.Expression pnnx_expr_2786 1 1 179 180 expr=mul(@0,1.666667e-01) torch.permute torch.permute_772 1 1 174 181 dims=(1,0,2) $input=174 torch.permute torch.permute_774 1 1 181 182 dims=(0,2,1) $input=181 torch.bmm torch.bmm_538 2 1 180 182 183 $input=180 $mat2=182 F.softmax F.softmax_68 1 1 183 184 dim=-1 $input=183 torch.permute torch.permute_773 1 1 178 185 dims=(1,0,2) $input=178 torch.bmm torch.bmm_539 2 1 184 185 186 $input=184 $mat2=185 torch.permute torch.permute_775 1 1 186 187 dims=(1,0,2) $input=186 Tensor.reshape Tensor.reshape_85 1 1 187 188 shape=(-1,144) $input=187 torch.unsqueeze torch.unsqueeze_894 1 1 188 189 dim=1 $input=188 nn.Linear encoder.emformer_layers.1.attention.out_proj 1 1 189 190 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_731 1 1 163 191 dim=(0) keepdim=True $input=163 pnnx.Expression pnnx_expr_2750 2 1 161 190 192 expr=add(@0,@1) torch.tensor_split slice_21 1 2 192 193 194 dim=0 indices=(2) torch.cat torch.cat_583 2 1 194 193 195 dim=0 torch.permute torch.permute_776 1 1 195 196 dims=(1,2,0) $input=195 nn.Conv1d encoder.emformer_layers.1.conv_module.pointwise_conv1 1 1 196 197 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_1 1 1 197 198 dim=1 $input=197 torch.cat torch.cat_584 2 1 8 198 199 dim=2 nn.Conv1d encoder.emformer_layers.1.conv_module.depthwise_conv 1 1 199 200 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_2720 1 1 200 201 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_23 1 1 201 202 $input=201 pnnx.Expression pnnx_expr_2719 2 1 200 202 203 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.1.conv_module.pointwise_conv2 1 1 203 204 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_23 1 2 204 205 206 dim=2 indices=(8) torch.permute torch.permute_778 1 1 206 207 dims=(2,0,1) $input=206 torch.permute torch.permute_777 1 1 205 208 dims=(2,0,1) $input=205 torch.cat torch.cat_585 2 1 207 208 209 dim=0 pnnx.Expression pnnx_expr_2684 2 1 192 209 210 expr=add(@0,@1) nn.Linear encoder.emformer_layers.1.feed_forward.0 1 1 210 211 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2681 1 1 211 212 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_24 1 1 212 213 $input=212 pnnx.Expression pnnx_expr_2680 2 1 211 213 214 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.1.feed_forward.4 1 1 214 215 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2678 2 1 210 215 216 expr=add(@0,@1) pnnx.Expression pnnx_expr_2673 1 1 216 217 expr=mul(@0,@0) torch.mean torch.mean_732 1 1 217 218 dim=(-1) keepdim=True $input=217 pnnx.Expression pnnx_expr_2669 2 1 216 218 219 expr=mul(@0,pow(add(@1,1.013315e+00),-5.000000e-01)) torch.tensor_split slice_25 1 2 219 220 221 dim=0 indices=(2) torch.cat torch.cat_586 2 1 220 221 222 dim=0 nn.Linear encoder.emformer_layers.2.feed_forward_macaron.0 1 1 222 223 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2657 1 1 223 224 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_25 1 1 224 225 $input=224 pnnx.Expression pnnx_expr_2656 2 1 223 225 226 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.2.feed_forward_macaron.4 1 1 226 227 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2654 2 1 222 227 228 expr=add(@0,@1) torch.tensor_split slice_28 1 2 228 229 230 dim=0 indices=(2) torch.cat torch.cat_587 2 1 229 230 231 dim=0 nn.Linear encoder.emformer_layers.2.attention.emb_to_query 1 1 231 232 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_588 3 1 9 229 230 233 dim=0 nn.Linear encoder.emformer_layers.2.attention.emb_to_key_value 1 1 233 234 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_714 1 2 234 235 236 chunks=2 dim=2 $input=234 Tensor.view Tensor.view_494 1 1 232 237 shape=(10,4,36) $input=232 torch.tensor_split slice_30 1 2 235 238 239 dim=0 indices=(34) torch.cat torch.cat_589 3 1 238 10 239 240 dim=0 Tensor.view Tensor.view_495 1 1 240 241 shape=(50,4,36) $input=240 torch.tensor_split slice_32 1 2 236 242 243 dim=0 indices=(34) torch.cat torch.cat_590 3 1 242 11 243 244 dim=0 Tensor.view Tensor.view_496 1 1 244 245 shape=(50,4,36) $input=244 torch.permute torch.permute_779 1 1 237 246 dims=(1,0,2) $input=237 pnnx.Expression pnnx_expr_2596 1 1 246 247 expr=mul(@0,1.666667e-01) torch.permute torch.permute_780 1 1 241 248 dims=(1,0,2) $input=241 torch.permute torch.permute_782 1 1 248 249 dims=(0,2,1) $input=248 torch.bmm torch.bmm_540 2 1 247 249 250 $input=247 $mat2=249 F.softmax F.softmax_69 1 1 250 251 dim=-1 $input=250 torch.permute torch.permute_781 1 1 245 252 dims=(1,0,2) $input=245 torch.bmm torch.bmm_541 2 1 251 252 253 $input=251 $mat2=252 torch.permute torch.permute_783 1 1 253 254 dims=(1,0,2) $input=253 Tensor.reshape Tensor.reshape_86 1 1 254 255 shape=(-1,144) $input=254 torch.unsqueeze torch.unsqueeze_895 1 1 255 256 dim=1 $input=255 nn.Linear encoder.emformer_layers.2.attention.out_proj 1 1 256 257 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_733 1 1 230 258 dim=(0) keepdim=True $input=230 pnnx.Expression pnnx_expr_2560 2 1 228 257 259 expr=add(@0,@1) torch.tensor_split slice_33 1 2 259 260 261 dim=0 indices=(2) torch.cat torch.cat_592 2 1 261 260 262 dim=0 torch.permute torch.permute_784 1 1 262 263 dims=(1,2,0) $input=262 nn.Conv1d encoder.emformer_layers.2.conv_module.pointwise_conv1 1 1 263 264 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_2 1 1 264 265 dim=1 $input=264 torch.cat torch.cat_593 2 1 12 265 266 dim=2 nn.Conv1d encoder.emformer_layers.2.conv_module.depthwise_conv 1 1 266 267 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_2530 1 1 267 268 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_26 1 1 268 269 $input=268 pnnx.Expression pnnx_expr_2529 2 1 267 269 270 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.2.conv_module.pointwise_conv2 1 1 270 271 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_35 1 2 271 272 273 dim=2 indices=(8) torch.permute torch.permute_786 1 1 273 274 dims=(2,0,1) $input=273 torch.permute torch.permute_785 1 1 272 275 dims=(2,0,1) $input=272 torch.cat torch.cat_594 2 1 274 275 276 dim=0 pnnx.Expression pnnx_expr_2494 2 1 259 276 277 expr=add(@0,@1) nn.Linear encoder.emformer_layers.2.feed_forward.0 1 1 277 278 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2491 1 1 278 279 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_27 1 1 279 280 $input=279 pnnx.Expression pnnx_expr_2490 2 1 278 280 281 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.2.feed_forward.4 1 1 281 282 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2488 2 1 277 282 283 expr=add(@0,@1) pnnx.Expression pnnx_expr_2483 1 1 283 284 expr=mul(@0,@0) torch.mean torch.mean_734 1 1 284 285 dim=(-1) keepdim=True $input=284 pnnx.Expression pnnx_expr_2479 2 1 283 285 286 expr=mul(@0,pow(add(@1,1.069920e+00),-5.000000e-01)) torch.tensor_split slice_37 1 2 286 287 288 dim=0 indices=(2) torch.cat torch.cat_595 2 1 287 288 289 dim=0 nn.Linear encoder.emformer_layers.3.feed_forward_macaron.0 1 1 289 290 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2467 1 1 290 291 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_28 1 1 291 292 $input=291 pnnx.Expression pnnx_expr_2466 2 1 290 292 293 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.3.feed_forward_macaron.4 1 1 293 294 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2464 2 1 289 294 295 expr=add(@0,@1) torch.tensor_split slice_40 1 2 295 296 297 dim=0 indices=(2) torch.cat torch.cat_596 2 1 296 297 298 dim=0 nn.Linear encoder.emformer_layers.3.attention.emb_to_query 1 1 298 299 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_597 3 1 13 296 297 300 dim=0 nn.Linear encoder.emformer_layers.3.attention.emb_to_key_value 1 1 300 301 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_715 1 2 301 302 303 chunks=2 dim=2 $input=301 Tensor.view Tensor.view_497 1 1 299 304 shape=(10,4,36) $input=299 torch.tensor_split slice_42 1 2 302 305 306 dim=0 indices=(34) torch.cat torch.cat_598 3 1 305 14 306 307 dim=0 Tensor.view Tensor.view_498 1 1 307 308 shape=(50,4,36) $input=307 torch.tensor_split slice_44 1 2 303 309 310 dim=0 indices=(34) torch.cat torch.cat_599 3 1 309 15 310 311 dim=0 Tensor.view Tensor.view_499 1 1 311 312 shape=(50,4,36) $input=311 torch.permute torch.permute_787 1 1 304 313 dims=(1,0,2) $input=304 pnnx.Expression pnnx_expr_2406 1 1 313 314 expr=mul(@0,1.666667e-01) torch.permute torch.permute_788 1 1 308 315 dims=(1,0,2) $input=308 torch.permute torch.permute_790 1 1 315 316 dims=(0,2,1) $input=315 torch.bmm torch.bmm_542 2 1 314 316 317 $input=314 $mat2=316 F.softmax F.softmax_70 1 1 317 318 dim=-1 $input=317 torch.permute torch.permute_789 1 1 312 319 dims=(1,0,2) $input=312 torch.bmm torch.bmm_543 2 1 318 319 320 $input=318 $mat2=319 torch.permute torch.permute_791 1 1 320 321 dims=(1,0,2) $input=320 Tensor.reshape Tensor.reshape_87 1 1 321 322 shape=(-1,144) $input=321 torch.unsqueeze torch.unsqueeze_896 1 1 322 323 dim=1 $input=322 nn.Linear encoder.emformer_layers.3.attention.out_proj 1 1 323 324 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_735 1 1 297 325 dim=(0) keepdim=True $input=297 pnnx.Expression pnnx_expr_2370 2 1 295 324 326 expr=add(@0,@1) torch.tensor_split slice_45 1 2 326 327 328 dim=0 indices=(2) torch.cat torch.cat_601 2 1 328 327 329 dim=0 torch.permute torch.permute_792 1 1 329 330 dims=(1,2,0) $input=329 nn.Conv1d encoder.emformer_layers.3.conv_module.pointwise_conv1 1 1 330 331 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_3 1 1 331 332 dim=1 $input=331 torch.cat torch.cat_602 2 1 16 332 333 dim=2 nn.Conv1d encoder.emformer_layers.3.conv_module.depthwise_conv 1 1 333 334 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_2340 1 1 334 335 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_29 1 1 335 336 $input=335 pnnx.Expression pnnx_expr_2339 2 1 334 336 337 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.3.conv_module.pointwise_conv2 1 1 337 338 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_47 1 2 338 339 340 dim=2 indices=(8) torch.permute torch.permute_794 1 1 340 341 dims=(2,0,1) $input=340 torch.permute torch.permute_793 1 1 339 342 dims=(2,0,1) $input=339 torch.cat torch.cat_603 2 1 341 342 343 dim=0 pnnx.Expression pnnx_expr_2304 2 1 326 343 344 expr=add(@0,@1) nn.Linear encoder.emformer_layers.3.feed_forward.0 1 1 344 345 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2301 1 1 345 346 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_30 1 1 346 347 $input=346 pnnx.Expression pnnx_expr_2300 2 1 345 347 348 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.3.feed_forward.4 1 1 348 349 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2298 2 1 344 349 350 expr=add(@0,@1) pnnx.Expression pnnx_expr_2293 1 1 350 351 expr=mul(@0,@0) torch.mean torch.mean_736 1 1 351 352 dim=(-1) keepdim=True $input=351 pnnx.Expression pnnx_expr_2289 2 1 350 352 353 expr=mul(@0,pow(add(@1,1.152986e+00),-5.000000e-01)) torch.tensor_split slice_49 1 2 353 354 355 dim=0 indices=(2) torch.cat torch.cat_604 2 1 354 355 356 dim=0 nn.Linear encoder.emformer_layers.4.feed_forward_macaron.0 1 1 356 357 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2277 1 1 357 358 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_31 1 1 358 359 $input=358 pnnx.Expression pnnx_expr_2276 2 1 357 359 360 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.4.feed_forward_macaron.4 1 1 360 361 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2274 2 1 356 361 362 expr=add(@0,@1) torch.tensor_split slice_52 1 2 362 363 364 dim=0 indices=(2) torch.cat torch.cat_605 2 1 363 364 365 dim=0 nn.Linear encoder.emformer_layers.4.attention.emb_to_query 1 1 365 366 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_606 3 1 17 363 364 367 dim=0 nn.Linear encoder.emformer_layers.4.attention.emb_to_key_value 1 1 367 368 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_716 1 2 368 369 370 chunks=2 dim=2 $input=368 Tensor.view Tensor.view_500 1 1 366 371 shape=(10,4,36) $input=366 torch.tensor_split slice_54 1 2 369 372 373 dim=0 indices=(34) torch.cat torch.cat_607 3 1 372 18 373 374 dim=0 Tensor.view Tensor.view_501 1 1 374 375 shape=(50,4,36) $input=374 torch.tensor_split slice_56 1 2 370 376 377 dim=0 indices=(34) torch.cat torch.cat_608 3 1 376 19 377 378 dim=0 Tensor.view Tensor.view_502 1 1 378 379 shape=(50,4,36) $input=378 torch.permute torch.permute_795 1 1 371 380 dims=(1,0,2) $input=371 pnnx.Expression pnnx_expr_2216 1 1 380 381 expr=mul(@0,1.666667e-01) torch.permute torch.permute_796 1 1 375 382 dims=(1,0,2) $input=375 torch.permute torch.permute_798 1 1 382 383 dims=(0,2,1) $input=382 torch.bmm torch.bmm_544 2 1 381 383 384 $input=381 $mat2=383 F.softmax F.softmax_71 1 1 384 385 dim=-1 $input=384 torch.permute torch.permute_797 1 1 379 386 dims=(1,0,2) $input=379 torch.bmm torch.bmm_545 2 1 385 386 387 $input=385 $mat2=386 torch.permute torch.permute_799 1 1 387 388 dims=(1,0,2) $input=387 Tensor.reshape Tensor.reshape_88 1 1 388 389 shape=(-1,144) $input=388 torch.unsqueeze torch.unsqueeze_897 1 1 389 390 dim=1 $input=389 nn.Linear encoder.emformer_layers.4.attention.out_proj 1 1 390 391 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_737 1 1 364 392 dim=(0) keepdim=True $input=364 pnnx.Expression pnnx_expr_2180 2 1 362 391 393 expr=add(@0,@1) torch.tensor_split slice_57 1 2 393 394 395 dim=0 indices=(2) torch.cat torch.cat_610 2 1 395 394 396 dim=0 torch.permute torch.permute_800 1 1 396 397 dims=(1,2,0) $input=396 nn.Conv1d encoder.emformer_layers.4.conv_module.pointwise_conv1 1 1 397 398 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_4 1 1 398 399 dim=1 $input=398 torch.cat torch.cat_611 2 1 20 399 400 dim=2 nn.Conv1d encoder.emformer_layers.4.conv_module.depthwise_conv 1 1 400 401 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_2150 1 1 401 402 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_32 1 1 402 403 $input=402 pnnx.Expression pnnx_expr_2149 2 1 401 403 404 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.4.conv_module.pointwise_conv2 1 1 404 405 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_59 1 2 405 406 407 dim=2 indices=(8) torch.permute torch.permute_802 1 1 407 408 dims=(2,0,1) $input=407 torch.permute torch.permute_801 1 1 406 409 dims=(2,0,1) $input=406 torch.cat torch.cat_612 2 1 408 409 410 dim=0 pnnx.Expression pnnx_expr_2114 2 1 393 410 411 expr=add(@0,@1) nn.Linear encoder.emformer_layers.4.feed_forward.0 1 1 411 412 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2111 1 1 412 413 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_33 1 1 413 414 $input=413 pnnx.Expression pnnx_expr_2110 2 1 412 414 415 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.4.feed_forward.4 1 1 415 416 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2108 2 1 411 416 417 expr=add(@0,@1) pnnx.Expression pnnx_expr_2103 1 1 417 418 expr=mul(@0,@0) torch.mean torch.mean_738 1 1 418 419 dim=(-1) keepdim=True $input=418 pnnx.Expression pnnx_expr_2099 2 1 417 419 420 expr=mul(@0,pow(add(@1,1.284874e+00),-5.000000e-01)) torch.tensor_split slice_61 1 2 420 421 422 dim=0 indices=(2) torch.cat torch.cat_613 2 1 421 422 423 dim=0 nn.Linear encoder.emformer_layers.5.feed_forward_macaron.0 1 1 423 424 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_2087 1 1 424 425 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_34 1 1 425 426 $input=425 pnnx.Expression pnnx_expr_2086 2 1 424 426 427 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.5.feed_forward_macaron.4 1 1 427 428 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_2084 2 1 423 428 429 expr=add(@0,@1) torch.tensor_split slice_64 1 2 429 430 431 dim=0 indices=(2) torch.cat torch.cat_614 2 1 430 431 432 dim=0 nn.Linear encoder.emformer_layers.5.attention.emb_to_query 1 1 432 433 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_615 3 1 21 430 431 434 dim=0 nn.Linear encoder.emformer_layers.5.attention.emb_to_key_value 1 1 434 435 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_717 1 2 435 436 437 chunks=2 dim=2 $input=435 Tensor.view Tensor.view_503 1 1 433 438 shape=(10,4,36) $input=433 torch.tensor_split slice_66 1 2 436 439 440 dim=0 indices=(34) torch.cat torch.cat_616 3 1 439 22 440 441 dim=0 Tensor.view Tensor.view_504 1 1 441 442 shape=(50,4,36) $input=441 torch.tensor_split slice_68 1 2 437 443 444 dim=0 indices=(34) torch.cat torch.cat_617 3 1 443 23 444 445 dim=0 Tensor.view Tensor.view_505 1 1 445 446 shape=(50,4,36) $input=445 torch.permute torch.permute_803 1 1 438 447 dims=(1,0,2) $input=438 pnnx.Expression pnnx_expr_2026 1 1 447 448 expr=mul(@0,1.666667e-01) torch.permute torch.permute_804 1 1 442 449 dims=(1,0,2) $input=442 torch.permute torch.permute_806 1 1 449 450 dims=(0,2,1) $input=449 torch.bmm torch.bmm_546 2 1 448 450 451 $input=448 $mat2=450 F.softmax F.softmax_72 1 1 451 452 dim=-1 $input=451 torch.permute torch.permute_805 1 1 446 453 dims=(1,0,2) $input=446 torch.bmm torch.bmm_547 2 1 452 453 454 $input=452 $mat2=453 torch.permute torch.permute_807 1 1 454 455 dims=(1,0,2) $input=454 Tensor.reshape Tensor.reshape_89 1 1 455 456 shape=(-1,144) $input=455 torch.unsqueeze torch.unsqueeze_898 1 1 456 457 dim=1 $input=456 nn.Linear encoder.emformer_layers.5.attention.out_proj 1 1 457 458 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_739 1 1 431 459 dim=(0) keepdim=True $input=431 pnnx.Expression pnnx_expr_1990 2 1 429 458 460 expr=add(@0,@1) torch.tensor_split slice_69 1 2 460 461 462 dim=0 indices=(2) torch.cat torch.cat_619 2 1 462 461 463 dim=0 torch.permute torch.permute_808 1 1 463 464 dims=(1,2,0) $input=463 nn.Conv1d encoder.emformer_layers.5.conv_module.pointwise_conv1 1 1 464 465 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_5 1 1 465 466 dim=1 $input=465 torch.cat torch.cat_620 2 1 24 466 467 dim=2 nn.Conv1d encoder.emformer_layers.5.conv_module.depthwise_conv 1 1 467 468 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_1960 1 1 468 469 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_35 1 1 469 470 $input=469 pnnx.Expression pnnx_expr_1959 2 1 468 470 471 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.5.conv_module.pointwise_conv2 1 1 471 472 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_71 1 2 472 473 474 dim=2 indices=(8) torch.permute torch.permute_810 1 1 474 475 dims=(2,0,1) $input=474 torch.permute torch.permute_809 1 1 473 476 dims=(2,0,1) $input=473 torch.cat torch.cat_621 2 1 475 476 477 dim=0 pnnx.Expression pnnx_expr_1924 2 1 460 477 478 expr=add(@0,@1) nn.Linear encoder.emformer_layers.5.feed_forward.0 1 1 478 479 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1921 1 1 479 480 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_36 1 1 480 481 $input=480 pnnx.Expression pnnx_expr_1920 2 1 479 481 482 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.5.feed_forward.4 1 1 482 483 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1918 2 1 478 483 484 expr=add(@0,@1) pnnx.Expression pnnx_expr_1913 1 1 484 485 expr=mul(@0,@0) torch.mean torch.mean_740 1 1 485 486 dim=(-1) keepdim=True $input=485 pnnx.Expression pnnx_expr_1909 2 1 484 486 487 expr=mul(@0,pow(add(@1,1.493289e+00),-5.000000e-01)) torch.tensor_split slice_73 1 2 487 488 489 dim=0 indices=(2) torch.cat torch.cat_622 2 1 488 489 490 dim=0 nn.Linear encoder.emformer_layers.6.feed_forward_macaron.0 1 1 490 491 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1897 1 1 491 492 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_37 1 1 492 493 $input=492 pnnx.Expression pnnx_expr_1896 2 1 491 493 494 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.6.feed_forward_macaron.4 1 1 494 495 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1894 2 1 490 495 496 expr=add(@0,@1) torch.tensor_split slice_76 1 2 496 497 498 dim=0 indices=(2) torch.cat torch.cat_623 2 1 497 498 499 dim=0 nn.Linear encoder.emformer_layers.6.attention.emb_to_query 1 1 499 500 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_624 3 1 25 497 498 501 dim=0 nn.Linear encoder.emformer_layers.6.attention.emb_to_key_value 1 1 501 502 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_718 1 2 502 503 504 chunks=2 dim=2 $input=502 Tensor.view Tensor.view_506 1 1 500 505 shape=(10,4,36) $input=500 torch.tensor_split slice_78 1 2 503 506 507 dim=0 indices=(34) torch.cat torch.cat_625 3 1 506 26 507 508 dim=0 Tensor.view Tensor.view_507 1 1 508 509 shape=(50,4,36) $input=508 torch.tensor_split slice_80 1 2 504 510 511 dim=0 indices=(34) torch.cat torch.cat_626 3 1 510 27 511 512 dim=0 Tensor.view Tensor.view_508 1 1 512 513 shape=(50,4,36) $input=512 torch.permute torch.permute_811 1 1 505 514 dims=(1,0,2) $input=505 pnnx.Expression pnnx_expr_1836 1 1 514 515 expr=mul(@0,1.666667e-01) torch.permute torch.permute_812 1 1 509 516 dims=(1,0,2) $input=509 torch.permute torch.permute_814 1 1 516 517 dims=(0,2,1) $input=516 torch.bmm torch.bmm_548 2 1 515 517 518 $input=515 $mat2=517 F.softmax F.softmax_73 1 1 518 519 dim=-1 $input=518 torch.permute torch.permute_813 1 1 513 520 dims=(1,0,2) $input=513 torch.bmm torch.bmm_549 2 1 519 520 521 $input=519 $mat2=520 torch.permute torch.permute_815 1 1 521 522 dims=(1,0,2) $input=521 Tensor.reshape Tensor.reshape_90 1 1 522 523 shape=(-1,144) $input=522 torch.unsqueeze torch.unsqueeze_899 1 1 523 524 dim=1 $input=523 nn.Linear encoder.emformer_layers.6.attention.out_proj 1 1 524 525 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_741 1 1 498 526 dim=(0) keepdim=True $input=498 pnnx.Expression pnnx_expr_1800 2 1 496 525 527 expr=add(@0,@1) torch.tensor_split slice_81 1 2 527 528 529 dim=0 indices=(2) torch.cat torch.cat_628 2 1 529 528 530 dim=0 torch.permute torch.permute_816 1 1 530 531 dims=(1,2,0) $input=530 nn.Conv1d encoder.emformer_layers.6.conv_module.pointwise_conv1 1 1 531 532 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_6 1 1 532 533 dim=1 $input=532 torch.cat torch.cat_629 2 1 28 533 534 dim=2 nn.Conv1d encoder.emformer_layers.6.conv_module.depthwise_conv 1 1 534 535 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_1770 1 1 535 536 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_38 1 1 536 537 $input=536 pnnx.Expression pnnx_expr_1769 2 1 535 537 538 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.6.conv_module.pointwise_conv2 1 1 538 539 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_83 1 2 539 540 541 dim=2 indices=(8) torch.permute torch.permute_818 1 1 541 542 dims=(2,0,1) $input=541 torch.permute torch.permute_817 1 1 540 543 dims=(2,0,1) $input=540 torch.cat torch.cat_630 2 1 542 543 544 dim=0 pnnx.Expression pnnx_expr_1734 2 1 527 544 545 expr=add(@0,@1) nn.Linear encoder.emformer_layers.6.feed_forward.0 1 1 545 546 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1731 1 1 546 547 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_39 1 1 547 548 $input=547 pnnx.Expression pnnx_expr_1730 2 1 546 548 549 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.6.feed_forward.4 1 1 549 550 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1728 2 1 545 550 551 expr=add(@0,@1) pnnx.Expression pnnx_expr_1723 1 1 551 552 expr=mul(@0,@0) torch.mean torch.mean_742 1 1 552 553 dim=(-1) keepdim=True $input=552 pnnx.Expression pnnx_expr_1719 2 1 551 553 554 expr=mul(@0,pow(add(@1,1.652225e+00),-5.000000e-01)) torch.tensor_split slice_85 1 2 554 555 556 dim=0 indices=(2) torch.cat torch.cat_631 2 1 555 556 557 dim=0 nn.Linear encoder.emformer_layers.7.feed_forward_macaron.0 1 1 557 558 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1707 1 1 558 559 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_40 1 1 559 560 $input=559 pnnx.Expression pnnx_expr_1706 2 1 558 560 561 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.7.feed_forward_macaron.4 1 1 561 562 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1704 2 1 557 562 563 expr=add(@0,@1) torch.tensor_split slice_88 1 2 563 564 565 dim=0 indices=(2) torch.cat torch.cat_632 2 1 564 565 566 dim=0 nn.Linear encoder.emformer_layers.7.attention.emb_to_query 1 1 566 567 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_633 3 1 29 564 565 568 dim=0 nn.Linear encoder.emformer_layers.7.attention.emb_to_key_value 1 1 568 569 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_719 1 2 569 570 571 chunks=2 dim=2 $input=569 Tensor.view Tensor.view_509 1 1 567 572 shape=(10,4,36) $input=567 torch.tensor_split slice_90 1 2 570 573 574 dim=0 indices=(34) torch.cat torch.cat_634 3 1 573 30 574 575 dim=0 Tensor.view Tensor.view_510 1 1 575 576 shape=(50,4,36) $input=575 torch.tensor_split slice_92 1 2 571 577 578 dim=0 indices=(34) torch.cat torch.cat_635 3 1 577 31 578 579 dim=0 Tensor.view Tensor.view_511 1 1 579 580 shape=(50,4,36) $input=579 torch.permute torch.permute_819 1 1 572 581 dims=(1,0,2) $input=572 pnnx.Expression pnnx_expr_1646 1 1 581 582 expr=mul(@0,1.666667e-01) torch.permute torch.permute_820 1 1 576 583 dims=(1,0,2) $input=576 torch.permute torch.permute_822 1 1 583 584 dims=(0,2,1) $input=583 torch.bmm torch.bmm_550 2 1 582 584 585 $input=582 $mat2=584 F.softmax F.softmax_74 1 1 585 586 dim=-1 $input=585 torch.permute torch.permute_821 1 1 580 587 dims=(1,0,2) $input=580 torch.bmm torch.bmm_551 2 1 586 587 588 $input=586 $mat2=587 torch.permute torch.permute_823 1 1 588 589 dims=(1,0,2) $input=588 Tensor.reshape Tensor.reshape_91 1 1 589 590 shape=(-1,144) $input=589 torch.unsqueeze torch.unsqueeze_900 1 1 590 591 dim=1 $input=590 nn.Linear encoder.emformer_layers.7.attention.out_proj 1 1 591 592 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_743 1 1 565 593 dim=(0) keepdim=True $input=565 pnnx.Expression pnnx_expr_1610 2 1 563 592 594 expr=add(@0,@1) torch.tensor_split slice_93 1 2 594 595 596 dim=0 indices=(2) torch.cat torch.cat_637 2 1 596 595 597 dim=0 torch.permute torch.permute_824 1 1 597 598 dims=(1,2,0) $input=597 nn.Conv1d encoder.emformer_layers.7.conv_module.pointwise_conv1 1 1 598 599 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_7 1 1 599 600 dim=1 $input=599 torch.cat torch.cat_638 2 1 32 600 601 dim=2 nn.Conv1d encoder.emformer_layers.7.conv_module.depthwise_conv 1 1 601 602 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_1580 1 1 602 603 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_41 1 1 603 604 $input=603 pnnx.Expression pnnx_expr_1579 2 1 602 604 605 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.7.conv_module.pointwise_conv2 1 1 605 606 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_95 1 2 606 607 608 dim=2 indices=(8) torch.permute torch.permute_826 1 1 608 609 dims=(2,0,1) $input=608 torch.permute torch.permute_825 1 1 607 610 dims=(2,0,1) $input=607 torch.cat torch.cat_639 2 1 609 610 611 dim=0 pnnx.Expression pnnx_expr_1544 2 1 594 611 612 expr=add(@0,@1) nn.Linear encoder.emformer_layers.7.feed_forward.0 1 1 612 613 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1541 1 1 613 614 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_42 1 1 614 615 $input=614 pnnx.Expression pnnx_expr_1540 2 1 613 615 616 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.7.feed_forward.4 1 1 616 617 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1538 2 1 612 617 618 expr=add(@0,@1) pnnx.Expression pnnx_expr_1533 1 1 618 619 expr=mul(@0,@0) torch.mean torch.mean_744 1 1 619 620 dim=(-1) keepdim=True $input=619 pnnx.Expression pnnx_expr_1529 2 1 618 620 621 expr=mul(@0,pow(add(@1,1.899739e+00),-5.000000e-01)) torch.tensor_split slice_97 1 2 621 622 623 dim=0 indices=(2) torch.cat torch.cat_640 2 1 622 623 624 dim=0 nn.Linear encoder.emformer_layers.8.feed_forward_macaron.0 1 1 624 625 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1517 1 1 625 626 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_43 1 1 626 627 $input=626 pnnx.Expression pnnx_expr_1516 2 1 625 627 628 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.8.feed_forward_macaron.4 1 1 628 629 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1514 2 1 624 629 630 expr=add(@0,@1) torch.tensor_split slice_100 1 2 630 631 632 dim=0 indices=(2) torch.cat torch.cat_641 2 1 631 632 633 dim=0 nn.Linear encoder.emformer_layers.8.attention.emb_to_query 1 1 633 634 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_642 3 1 33 631 632 635 dim=0 nn.Linear encoder.emformer_layers.8.attention.emb_to_key_value 1 1 635 636 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_720 1 2 636 637 638 chunks=2 dim=2 $input=636 Tensor.view Tensor.view_512 1 1 634 639 shape=(10,4,36) $input=634 torch.tensor_split slice_102 1 2 637 640 641 dim=0 indices=(34) torch.cat torch.cat_643 3 1 640 34 641 642 dim=0 Tensor.view Tensor.view_513 1 1 642 643 shape=(50,4,36) $input=642 torch.tensor_split slice_104 1 2 638 644 645 dim=0 indices=(34) torch.cat torch.cat_644 3 1 644 35 645 646 dim=0 Tensor.view Tensor.view_514 1 1 646 647 shape=(50,4,36) $input=646 torch.permute torch.permute_827 1 1 639 648 dims=(1,0,2) $input=639 pnnx.Expression pnnx_expr_1456 1 1 648 649 expr=mul(@0,1.666667e-01) torch.permute torch.permute_828 1 1 643 650 dims=(1,0,2) $input=643 torch.permute torch.permute_830 1 1 650 651 dims=(0,2,1) $input=650 torch.bmm torch.bmm_552 2 1 649 651 652 $input=649 $mat2=651 F.softmax F.softmax_75 1 1 652 653 dim=-1 $input=652 torch.permute torch.permute_829 1 1 647 654 dims=(1,0,2) $input=647 torch.bmm torch.bmm_553 2 1 653 654 655 $input=653 $mat2=654 torch.permute torch.permute_831 1 1 655 656 dims=(1,0,2) $input=655 Tensor.reshape Tensor.reshape_92 1 1 656 657 shape=(-1,144) $input=656 torch.unsqueeze torch.unsqueeze_901 1 1 657 658 dim=1 $input=657 nn.Linear encoder.emformer_layers.8.attention.out_proj 1 1 658 659 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_745 1 1 632 660 dim=(0) keepdim=True $input=632 pnnx.Expression pnnx_expr_1420 2 1 630 659 661 expr=add(@0,@1) torch.tensor_split slice_105 1 2 661 662 663 dim=0 indices=(2) torch.cat torch.cat_646 2 1 663 662 664 dim=0 torch.permute torch.permute_832 1 1 664 665 dims=(1,2,0) $input=664 nn.Conv1d encoder.emformer_layers.8.conv_module.pointwise_conv1 1 1 665 666 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_8 1 1 666 667 dim=1 $input=666 torch.cat torch.cat_647 2 1 36 667 668 dim=2 nn.Conv1d encoder.emformer_layers.8.conv_module.depthwise_conv 1 1 668 669 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_1390 1 1 669 670 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_44 1 1 670 671 $input=670 pnnx.Expression pnnx_expr_1389 2 1 669 671 672 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.8.conv_module.pointwise_conv2 1 1 672 673 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_107 1 2 673 674 675 dim=2 indices=(8) torch.permute torch.permute_834 1 1 675 676 dims=(2,0,1) $input=675 torch.permute torch.permute_833 1 1 674 677 dims=(2,0,1) $input=674 torch.cat torch.cat_648 2 1 676 677 678 dim=0 pnnx.Expression pnnx_expr_1354 2 1 661 678 679 expr=add(@0,@1) nn.Linear encoder.emformer_layers.8.feed_forward.0 1 1 679 680 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1351 1 1 680 681 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_45 1 1 681 682 $input=681 pnnx.Expression pnnx_expr_1350 2 1 680 682 683 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.8.feed_forward.4 1 1 683 684 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1348 2 1 679 684 685 expr=add(@0,@1) pnnx.Expression pnnx_expr_1343 1 1 685 686 expr=mul(@0,@0) torch.mean torch.mean_746 1 1 686 687 dim=(-1) keepdim=True $input=686 pnnx.Expression pnnx_expr_1339 2 1 685 687 688 expr=mul(@0,pow(add(@1,1.969823e+00),-5.000000e-01)) torch.tensor_split slice_109 1 2 688 689 690 dim=0 indices=(2) torch.cat torch.cat_649 2 1 689 690 691 dim=0 nn.Linear encoder.emformer_layers.9.feed_forward_macaron.0 1 1 691 692 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1327 1 1 692 693 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_46 1 1 693 694 $input=693 pnnx.Expression pnnx_expr_1326 2 1 692 694 695 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.9.feed_forward_macaron.4 1 1 695 696 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1324 2 1 691 696 697 expr=add(@0,@1) torch.tensor_split slice_112 1 2 697 698 699 dim=0 indices=(2) torch.cat torch.cat_650 2 1 698 699 700 dim=0 nn.Linear encoder.emformer_layers.9.attention.emb_to_query 1 1 700 701 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_651 3 1 37 698 699 702 dim=0 nn.Linear encoder.emformer_layers.9.attention.emb_to_key_value 1 1 702 703 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_721 1 2 703 704 705 chunks=2 dim=2 $input=703 Tensor.view Tensor.view_515 1 1 701 706 shape=(10,4,36) $input=701 torch.tensor_split slice_114 1 2 704 707 708 dim=0 indices=(34) torch.cat torch.cat_652 3 1 707 38 708 709 dim=0 Tensor.view Tensor.view_516 1 1 709 710 shape=(50,4,36) $input=709 torch.tensor_split slice_116 1 2 705 711 712 dim=0 indices=(34) torch.cat torch.cat_653 3 1 711 39 712 713 dim=0 Tensor.view Tensor.view_517 1 1 713 714 shape=(50,4,36) $input=713 torch.permute torch.permute_835 1 1 706 715 dims=(1,0,2) $input=706 pnnx.Expression pnnx_expr_1266 1 1 715 716 expr=mul(@0,1.666667e-01) torch.permute torch.permute_836 1 1 710 717 dims=(1,0,2) $input=710 torch.permute torch.permute_838 1 1 717 718 dims=(0,2,1) $input=717 torch.bmm torch.bmm_554 2 1 716 718 719 $input=716 $mat2=718 F.softmax F.softmax_76 1 1 719 720 dim=-1 $input=719 torch.permute torch.permute_837 1 1 714 721 dims=(1,0,2) $input=714 torch.bmm torch.bmm_555 2 1 720 721 722 $input=720 $mat2=721 torch.permute torch.permute_839 1 1 722 723 dims=(1,0,2) $input=722 Tensor.reshape Tensor.reshape_93 1 1 723 724 shape=(-1,144) $input=723 torch.unsqueeze torch.unsqueeze_902 1 1 724 725 dim=1 $input=724 nn.Linear encoder.emformer_layers.9.attention.out_proj 1 1 725 726 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_747 1 1 699 727 dim=(0) keepdim=True $input=699 pnnx.Expression pnnx_expr_1230 2 1 697 726 728 expr=add(@0,@1) torch.tensor_split slice_117 1 2 728 729 730 dim=0 indices=(2) torch.cat torch.cat_655 2 1 730 729 731 dim=0 torch.permute torch.permute_840 1 1 731 732 dims=(1,2,0) $input=731 nn.Conv1d encoder.emformer_layers.9.conv_module.pointwise_conv1 1 1 732 733 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_9 1 1 733 734 dim=1 $input=733 torch.cat torch.cat_656 2 1 40 734 735 dim=2 nn.Conv1d encoder.emformer_layers.9.conv_module.depthwise_conv 1 1 735 736 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_1200 1 1 736 737 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_47 1 1 737 738 $input=737 pnnx.Expression pnnx_expr_1199 2 1 736 738 739 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.9.conv_module.pointwise_conv2 1 1 739 740 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_119 1 2 740 741 742 dim=2 indices=(8) torch.permute torch.permute_842 1 1 742 743 dims=(2,0,1) $input=742 torch.permute torch.permute_841 1 1 741 744 dims=(2,0,1) $input=741 torch.cat torch.cat_657 2 1 743 744 745 dim=0 pnnx.Expression pnnx_expr_1164 2 1 728 745 746 expr=add(@0,@1) nn.Linear encoder.emformer_layers.9.feed_forward.0 1 1 746 747 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1161 1 1 747 748 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_48 1 1 748 749 $input=748 pnnx.Expression pnnx_expr_1160 2 1 747 749 750 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.9.feed_forward.4 1 1 750 751 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1158 2 1 746 751 752 expr=add(@0,@1) pnnx.Expression pnnx_expr_1153 1 1 752 753 expr=mul(@0,@0) torch.mean torch.mean_748 1 1 753 754 dim=(-1) keepdim=True $input=753 pnnx.Expression pnnx_expr_1149 2 1 752 754 755 expr=mul(@0,pow(add(@1,2.125452e+00),-5.000000e-01)) torch.tensor_split slice_121 1 2 755 756 757 dim=0 indices=(2) torch.cat torch.cat_658 2 1 756 757 758 dim=0 nn.Linear encoder.emformer_layers.10.feed_forward_macaron.0 1 1 758 759 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_1137 1 1 759 760 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_49 1 1 760 761 $input=760 pnnx.Expression pnnx_expr_1136 2 1 759 761 762 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.10.feed_forward_macaron.4 1 1 762 763 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_1134 2 1 758 763 764 expr=add(@0,@1) torch.tensor_split slice_124 1 2 764 765 766 dim=0 indices=(2) torch.cat torch.cat_659 2 1 765 766 767 dim=0 nn.Linear encoder.emformer_layers.10.attention.emb_to_query 1 1 767 768 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_660 3 1 41 765 766 769 dim=0 nn.Linear encoder.emformer_layers.10.attention.emb_to_key_value 1 1 769 770 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_722 1 2 770 771 772 chunks=2 dim=2 $input=770 Tensor.view Tensor.view_518 1 1 768 773 shape=(10,4,36) $input=768 torch.tensor_split slice_126 1 2 771 774 775 dim=0 indices=(34) torch.cat torch.cat_661 3 1 774 42 775 776 dim=0 Tensor.view Tensor.view_519 1 1 776 777 shape=(50,4,36) $input=776 torch.tensor_split slice_128 1 2 772 778 779 dim=0 indices=(34) torch.cat torch.cat_662 3 1 778 43 779 780 dim=0 Tensor.view Tensor.view_520 1 1 780 781 shape=(50,4,36) $input=780 torch.permute torch.permute_843 1 1 773 782 dims=(1,0,2) $input=773 pnnx.Expression pnnx_expr_1076 1 1 782 783 expr=mul(@0,1.666667e-01) torch.permute torch.permute_844 1 1 777 784 dims=(1,0,2) $input=777 torch.permute torch.permute_846 1 1 784 785 dims=(0,2,1) $input=784 torch.bmm torch.bmm_556 2 1 783 785 786 $input=783 $mat2=785 F.softmax F.softmax_77 1 1 786 787 dim=-1 $input=786 torch.permute torch.permute_845 1 1 781 788 dims=(1,0,2) $input=781 torch.bmm torch.bmm_557 2 1 787 788 789 $input=787 $mat2=788 torch.permute torch.permute_847 1 1 789 790 dims=(1,0,2) $input=789 Tensor.reshape Tensor.reshape_94 1 1 790 791 shape=(-1,144) $input=790 torch.unsqueeze torch.unsqueeze_903 1 1 791 792 dim=1 $input=791 nn.Linear encoder.emformer_layers.10.attention.out_proj 1 1 792 793 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_749 1 1 766 794 dim=(0) keepdim=True $input=766 pnnx.Expression pnnx_expr_1040 2 1 764 793 795 expr=add(@0,@1) torch.tensor_split slice_129 1 2 795 796 797 dim=0 indices=(2) torch.cat torch.cat_664 2 1 797 796 798 dim=0 torch.permute torch.permute_848 1 1 798 799 dims=(1,2,0) $input=798 nn.Conv1d encoder.emformer_layers.10.conv_module.pointwise_conv1 1 1 799 800 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_10 1 1 800 801 dim=1 $input=800 torch.cat torch.cat_665 2 1 44 801 802 dim=2 nn.Conv1d encoder.emformer_layers.10.conv_module.depthwise_conv 1 1 802 803 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_1010 1 1 803 804 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_50 1 1 804 805 $input=804 pnnx.Expression pnnx_expr_1009 2 1 803 805 806 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.10.conv_module.pointwise_conv2 1 1 806 807 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_131 1 2 807 808 809 dim=2 indices=(8) torch.permute torch.permute_850 1 1 809 810 dims=(2,0,1) $input=809 torch.permute torch.permute_849 1 1 808 811 dims=(2,0,1) $input=808 torch.cat torch.cat_666 2 1 810 811 812 dim=0 pnnx.Expression pnnx_expr_974 2 1 795 812 813 expr=add(@0,@1) nn.Linear encoder.emformer_layers.10.feed_forward.0 1 1 813 814 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_971 1 1 814 815 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_51 1 1 815 816 $input=815 pnnx.Expression pnnx_expr_970 2 1 814 816 817 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.10.feed_forward.4 1 1 817 818 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_968 2 1 813 818 819 expr=add(@0,@1) pnnx.Expression pnnx_expr_963 1 1 819 820 expr=mul(@0,@0) torch.mean torch.mean_750 1 1 820 821 dim=(-1) keepdim=True $input=820 pnnx.Expression pnnx_expr_959 2 1 819 821 822 expr=mul(@0,pow(add(@1,2.230928e+00),-5.000000e-01)) torch.tensor_split slice_133 1 2 822 823 824 dim=0 indices=(2) torch.cat torch.cat_667 2 1 823 824 825 dim=0 nn.Linear encoder.emformer_layers.11.feed_forward_macaron.0 1 1 825 826 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_947 1 1 826 827 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_52 1 1 827 828 $input=827 pnnx.Expression pnnx_expr_946 2 1 826 828 829 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.11.feed_forward_macaron.4 1 1 829 830 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_944 2 1 825 830 831 expr=add(@0,@1) torch.tensor_split slice_136 1 2 831 832 833 dim=0 indices=(2) torch.cat torch.cat_668 2 1 832 833 834 dim=0 nn.Linear encoder.emformer_layers.11.attention.emb_to_query 1 1 834 835 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_669 3 1 45 832 833 836 dim=0 nn.Linear encoder.emformer_layers.11.attention.emb_to_key_value 1 1 836 837 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_723 1 2 837 838 839 chunks=2 dim=2 $input=837 Tensor.view Tensor.view_521 1 1 835 840 shape=(10,4,36) $input=835 torch.tensor_split slice_138 1 2 838 841 842 dim=0 indices=(34) torch.cat torch.cat_670 3 1 841 46 842 843 dim=0 Tensor.view Tensor.view_522 1 1 843 844 shape=(50,4,36) $input=843 torch.tensor_split slice_140 1 2 839 845 846 dim=0 indices=(34) torch.cat torch.cat_671 3 1 845 47 846 847 dim=0 Tensor.view Tensor.view_523 1 1 847 848 shape=(50,4,36) $input=847 torch.permute torch.permute_851 1 1 840 849 dims=(1,0,2) $input=840 pnnx.Expression pnnx_expr_886 1 1 849 850 expr=mul(@0,1.666667e-01) torch.permute torch.permute_852 1 1 844 851 dims=(1,0,2) $input=844 torch.permute torch.permute_854 1 1 851 852 dims=(0,2,1) $input=851 torch.bmm torch.bmm_558 2 1 850 852 853 $input=850 $mat2=852 F.softmax F.softmax_78 1 1 853 854 dim=-1 $input=853 torch.permute torch.permute_853 1 1 848 855 dims=(1,0,2) $input=848 torch.bmm torch.bmm_559 2 1 854 855 856 $input=854 $mat2=855 torch.permute torch.permute_855 1 1 856 857 dims=(1,0,2) $input=856 Tensor.reshape Tensor.reshape_95 1 1 857 858 shape=(-1,144) $input=857 torch.unsqueeze torch.unsqueeze_904 1 1 858 859 dim=1 $input=858 nn.Linear encoder.emformer_layers.11.attention.out_proj 1 1 859 860 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_751 1 1 833 861 dim=(0) keepdim=True $input=833 pnnx.Expression pnnx_expr_850 2 1 831 860 862 expr=add(@0,@1) torch.tensor_split slice_141 1 2 862 863 864 dim=0 indices=(2) torch.cat torch.cat_673 2 1 864 863 865 dim=0 torch.permute torch.permute_856 1 1 865 866 dims=(1,2,0) $input=865 nn.Conv1d encoder.emformer_layers.11.conv_module.pointwise_conv1 1 1 866 867 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_11 1 1 867 868 dim=1 $input=867 torch.cat torch.cat_674 2 1 48 868 869 dim=2 nn.Conv1d encoder.emformer_layers.11.conv_module.depthwise_conv 1 1 869 870 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_820 1 1 870 871 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_53 1 1 871 872 $input=871 pnnx.Expression pnnx_expr_819 2 1 870 872 873 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.11.conv_module.pointwise_conv2 1 1 873 874 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_143 1 2 874 875 876 dim=2 indices=(8) torch.permute torch.permute_858 1 1 876 877 dims=(2,0,1) $input=876 torch.permute torch.permute_857 1 1 875 878 dims=(2,0,1) $input=875 torch.cat torch.cat_675 2 1 877 878 879 dim=0 pnnx.Expression pnnx_expr_784 2 1 862 879 880 expr=add(@0,@1) nn.Linear encoder.emformer_layers.11.feed_forward.0 1 1 880 881 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_781 1 1 881 882 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_54 1 1 882 883 $input=882 pnnx.Expression pnnx_expr_780 2 1 881 883 884 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.11.feed_forward.4 1 1 884 885 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_778 2 1 880 885 886 expr=add(@0,@1) pnnx.Expression pnnx_expr_773 1 1 886 887 expr=mul(@0,@0) torch.mean torch.mean_752 1 1 887 888 dim=(-1) keepdim=True $input=887 pnnx.Expression pnnx_expr_769 2 1 886 888 889 expr=mul(@0,pow(add(@1,2.460389e+00),-5.000000e-01)) torch.tensor_split slice_145 1 2 889 890 891 dim=0 indices=(2) torch.cat torch.cat_676 2 1 890 891 892 dim=0 nn.Linear encoder.emformer_layers.12.feed_forward_macaron.0 1 1 892 893 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_757 1 1 893 894 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_55 1 1 894 895 $input=894 pnnx.Expression pnnx_expr_756 2 1 893 895 896 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.12.feed_forward_macaron.4 1 1 896 897 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_754 2 1 892 897 898 expr=add(@0,@1) torch.tensor_split slice_148 1 2 898 899 900 dim=0 indices=(2) torch.cat torch.cat_677 2 1 899 900 901 dim=0 nn.Linear encoder.emformer_layers.12.attention.emb_to_query 1 1 901 902 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_678 3 1 49 899 900 903 dim=0 nn.Linear encoder.emformer_layers.12.attention.emb_to_key_value 1 1 903 904 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_724 1 2 904 905 906 chunks=2 dim=2 $input=904 Tensor.view Tensor.view_524 1 1 902 907 shape=(10,4,36) $input=902 torch.tensor_split slice_150 1 2 905 908 909 dim=0 indices=(34) torch.cat torch.cat_679 3 1 908 50 909 910 dim=0 Tensor.view Tensor.view_525 1 1 910 911 shape=(50,4,36) $input=910 torch.tensor_split slice_152 1 2 906 912 913 dim=0 indices=(34) torch.cat torch.cat_680 3 1 912 51 913 914 dim=0 Tensor.view Tensor.view_526 1 1 914 915 shape=(50,4,36) $input=914 torch.permute torch.permute_859 1 1 907 916 dims=(1,0,2) $input=907 pnnx.Expression pnnx_expr_696 1 1 916 917 expr=mul(@0,1.666667e-01) torch.permute torch.permute_860 1 1 911 918 dims=(1,0,2) $input=911 torch.permute torch.permute_862 1 1 918 919 dims=(0,2,1) $input=918 torch.bmm torch.bmm_560 2 1 917 919 920 $input=917 $mat2=919 F.softmax F.softmax_79 1 1 920 921 dim=-1 $input=920 torch.permute torch.permute_861 1 1 915 922 dims=(1,0,2) $input=915 torch.bmm torch.bmm_561 2 1 921 922 923 $input=921 $mat2=922 torch.permute torch.permute_863 1 1 923 924 dims=(1,0,2) $input=923 Tensor.reshape Tensor.reshape_96 1 1 924 925 shape=(-1,144) $input=924 torch.unsqueeze torch.unsqueeze_905 1 1 925 926 dim=1 $input=925 nn.Linear encoder.emformer_layers.12.attention.out_proj 1 1 926 927 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_753 1 1 900 928 dim=(0) keepdim=True $input=900 pnnx.Expression pnnx_expr_660 2 1 898 927 929 expr=add(@0,@1) torch.tensor_split slice_153 1 2 929 930 931 dim=0 indices=(2) torch.cat torch.cat_682 2 1 931 930 932 dim=0 torch.permute torch.permute_864 1 1 932 933 dims=(1,2,0) $input=932 nn.Conv1d encoder.emformer_layers.12.conv_module.pointwise_conv1 1 1 933 934 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_12 1 1 934 935 dim=1 $input=934 torch.cat torch.cat_683 2 1 52 935 936 dim=2 nn.Conv1d encoder.emformer_layers.12.conv_module.depthwise_conv 1 1 936 937 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_630 1 1 937 938 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_56 1 1 938 939 $input=938 pnnx.Expression pnnx_expr_629 2 1 937 939 940 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.12.conv_module.pointwise_conv2 1 1 940 941 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_155 1 2 941 942 943 dim=2 indices=(8) torch.permute torch.permute_866 1 1 943 944 dims=(2,0,1) $input=943 torch.permute torch.permute_865 1 1 942 945 dims=(2,0,1) $input=942 torch.cat torch.cat_684 2 1 944 945 946 dim=0 pnnx.Expression pnnx_expr_594 2 1 929 946 947 expr=add(@0,@1) nn.Linear encoder.emformer_layers.12.feed_forward.0 1 1 947 948 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_591 1 1 948 949 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_57 1 1 949 950 $input=949 pnnx.Expression pnnx_expr_590 2 1 948 950 951 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.12.feed_forward.4 1 1 951 952 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_588 2 1 947 952 953 expr=add(@0,@1) pnnx.Expression pnnx_expr_583 1 1 953 954 expr=mul(@0,@0) torch.mean torch.mean_754 1 1 954 955 dim=(-1) keepdim=True $input=954 pnnx.Expression pnnx_expr_579 2 1 953 955 956 expr=mul(@0,pow(add(@1,1.900982e+00),-5.000000e-01)) torch.tensor_split slice_157 1 2 956 957 958 dim=0 indices=(2) torch.cat torch.cat_685 2 1 957 958 959 dim=0 nn.Linear encoder.emformer_layers.13.feed_forward_macaron.0 1 1 959 960 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_567 1 1 960 961 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_58 1 1 961 962 $input=961 pnnx.Expression pnnx_expr_566 2 1 960 962 963 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.13.feed_forward_macaron.4 1 1 963 964 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_564 2 1 959 964 965 expr=add(@0,@1) torch.tensor_split slice_160 1 2 965 966 967 dim=0 indices=(2) torch.cat torch.cat_686 2 1 966 967 968 dim=0 nn.Linear encoder.emformer_layers.13.attention.emb_to_query 1 1 968 969 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_687 3 1 53 966 967 970 dim=0 nn.Linear encoder.emformer_layers.13.attention.emb_to_key_value 1 1 970 971 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_725 1 2 971 972 973 chunks=2 dim=2 $input=971 Tensor.view Tensor.view_527 1 1 969 974 shape=(10,4,36) $input=969 torch.tensor_split slice_162 1 2 972 975 976 dim=0 indices=(34) torch.cat torch.cat_688 3 1 975 54 976 977 dim=0 Tensor.view Tensor.view_528 1 1 977 978 shape=(50,4,36) $input=977 torch.tensor_split slice_164 1 2 973 979 980 dim=0 indices=(34) torch.cat torch.cat_689 3 1 979 55 980 981 dim=0 Tensor.view Tensor.view_529 1 1 981 982 shape=(50,4,36) $input=981 torch.permute torch.permute_867 1 1 974 983 dims=(1,0,2) $input=974 pnnx.Expression pnnx_expr_506 1 1 983 984 expr=mul(@0,1.666667e-01) torch.permute torch.permute_868 1 1 978 985 dims=(1,0,2) $input=978 torch.permute torch.permute_870 1 1 985 986 dims=(0,2,1) $input=985 torch.bmm torch.bmm_562 2 1 984 986 987 $input=984 $mat2=986 F.softmax F.softmax_80 1 1 987 988 dim=-1 $input=987 torch.permute torch.permute_869 1 1 982 989 dims=(1,0,2) $input=982 torch.bmm torch.bmm_563 2 1 988 989 990 $input=988 $mat2=989 torch.permute torch.permute_871 1 1 990 991 dims=(1,0,2) $input=990 Tensor.reshape Tensor.reshape_97 1 1 991 992 shape=(-1,144) $input=991 torch.unsqueeze torch.unsqueeze_906 1 1 992 993 dim=1 $input=992 nn.Linear encoder.emformer_layers.13.attention.out_proj 1 1 993 994 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_755 1 1 967 995 dim=(0) keepdim=True $input=967 pnnx.Expression pnnx_expr_470 2 1 965 994 996 expr=add(@0,@1) torch.tensor_split slice_165 1 2 996 997 998 dim=0 indices=(2) torch.cat torch.cat_691 2 1 998 997 999 dim=0 torch.permute torch.permute_872 1 1 999 1000 dims=(1,2,0) $input=999 nn.Conv1d encoder.emformer_layers.13.conv_module.pointwise_conv1 1 1 1000 1001 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_13 1 1 1001 1002 dim=1 $input=1001 torch.cat torch.cat_692 2 1 56 1002 1003 dim=2 nn.Conv1d encoder.emformer_layers.13.conv_module.depthwise_conv 1 1 1003 1004 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_440 1 1 1004 1005 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_59 1 1 1005 1006 $input=1005 pnnx.Expression pnnx_expr_439 2 1 1004 1006 1007 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.13.conv_module.pointwise_conv2 1 1 1007 1008 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_167 1 2 1008 1009 1010 dim=2 indices=(8) torch.permute torch.permute_874 1 1 1010 1011 dims=(2,0,1) $input=1010 torch.permute torch.permute_873 1 1 1009 1012 dims=(2,0,1) $input=1009 torch.cat torch.cat_693 2 1 1011 1012 1013 dim=0 pnnx.Expression pnnx_expr_404 2 1 996 1013 1014 expr=add(@0,@1) nn.Linear encoder.emformer_layers.13.feed_forward.0 1 1 1014 1015 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_401 1 1 1015 1016 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_60 1 1 1016 1017 $input=1016 pnnx.Expression pnnx_expr_400 2 1 1015 1017 1018 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.13.feed_forward.4 1 1 1018 1019 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_398 2 1 1014 1019 1020 expr=add(@0,@1) pnnx.Expression pnnx_expr_393 1 1 1020 1021 expr=mul(@0,@0) torch.mean torch.mean_756 1 1 1021 1022 dim=(-1) keepdim=True $input=1021 pnnx.Expression pnnx_expr_389 2 1 1020 1022 1023 expr=mul(@0,pow(add(@1,2.083574e+00),-5.000000e-01)) torch.tensor_split slice_169 1 2 1023 1024 1025 dim=0 indices=(2) torch.cat torch.cat_694 2 1 1024 1025 1026 dim=0 nn.Linear encoder.emformer_layers.14.feed_forward_macaron.0 1 1 1026 1027 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_377 1 1 1027 1028 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_61 1 1 1028 1029 $input=1028 pnnx.Expression pnnx_expr_376 2 1 1027 1029 1030 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.14.feed_forward_macaron.4 1 1 1030 1031 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_374 2 1 1026 1031 1032 expr=add(@0,@1) torch.tensor_split slice_172 1 2 1032 1033 1034 dim=0 indices=(2) torch.cat torch.cat_695 2 1 1033 1034 1035 dim=0 nn.Linear encoder.emformer_layers.14.attention.emb_to_query 1 1 1035 1036 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_696 3 1 57 1033 1034 1037 dim=0 nn.Linear encoder.emformer_layers.14.attention.emb_to_key_value 1 1 1037 1038 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_726 1 2 1038 1039 1040 chunks=2 dim=2 $input=1038 Tensor.view Tensor.view_530 1 1 1036 1041 shape=(10,4,36) $input=1036 torch.tensor_split slice_174 1 2 1039 1042 1043 dim=0 indices=(34) torch.cat torch.cat_697 3 1 1042 58 1043 1044 dim=0 Tensor.view Tensor.view_531 1 1 1044 1045 shape=(50,4,36) $input=1044 torch.tensor_split slice_176 1 2 1040 1046 1047 dim=0 indices=(34) torch.cat torch.cat_698 3 1 1046 59 1047 1048 dim=0 Tensor.view Tensor.view_532 1 1 1048 1049 shape=(50,4,36) $input=1048 torch.permute torch.permute_875 1 1 1041 1050 dims=(1,0,2) $input=1041 pnnx.Expression pnnx_expr_316 1 1 1050 1051 expr=mul(@0,1.666667e-01) torch.permute torch.permute_876 1 1 1045 1052 dims=(1,0,2) $input=1045 torch.permute torch.permute_878 1 1 1052 1053 dims=(0,2,1) $input=1052 torch.bmm torch.bmm_564 2 1 1051 1053 1054 $input=1051 $mat2=1053 F.softmax F.softmax_81 1 1 1054 1055 dim=-1 $input=1054 torch.permute torch.permute_877 1 1 1049 1056 dims=(1,0,2) $input=1049 torch.bmm torch.bmm_565 2 1 1055 1056 1057 $input=1055 $mat2=1056 torch.permute torch.permute_879 1 1 1057 1058 dims=(1,0,2) $input=1057 Tensor.reshape Tensor.reshape_98 1 1 1058 1059 shape=(-1,144) $input=1058 torch.unsqueeze torch.unsqueeze_907 1 1 1059 1060 dim=1 $input=1059 nn.Linear encoder.emformer_layers.14.attention.out_proj 1 1 1060 1061 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_757 1 1 1034 1062 dim=(0) keepdim=True $input=1034 pnnx.Expression pnnx_expr_280 2 1 1032 1061 1063 expr=add(@0,@1) torch.tensor_split slice_177 1 2 1063 1064 1065 dim=0 indices=(2) torch.cat torch.cat_700 2 1 1065 1064 1066 dim=0 torch.permute torch.permute_880 1 1 1066 1067 dims=(1,2,0) $input=1066 nn.Conv1d encoder.emformer_layers.14.conv_module.pointwise_conv1 1 1 1067 1068 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_14 1 1 1068 1069 dim=1 $input=1068 torch.cat torch.cat_701 2 1 60 1069 1070 dim=2 nn.Conv1d encoder.emformer_layers.14.conv_module.depthwise_conv 1 1 1070 1071 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_250 1 1 1071 1072 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_62 1 1 1072 1073 $input=1072 pnnx.Expression pnnx_expr_249 2 1 1071 1073 1074 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.14.conv_module.pointwise_conv2 1 1 1074 1075 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_179 1 2 1075 1076 1077 dim=2 indices=(8) torch.permute torch.permute_882 1 1 1077 1078 dims=(2,0,1) $input=1077 torch.permute torch.permute_881 1 1 1076 1079 dims=(2,0,1) $input=1076 torch.cat torch.cat_702 2 1 1078 1079 1080 dim=0 pnnx.Expression pnnx_expr_214 2 1 1063 1080 1081 expr=add(@0,@1) nn.Linear encoder.emformer_layers.14.feed_forward.0 1 1 1081 1082 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_211 1 1 1082 1083 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_63 1 1 1083 1084 $input=1083 pnnx.Expression pnnx_expr_210 2 1 1082 1084 1085 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.14.feed_forward.4 1 1 1085 1086 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_208 2 1 1081 1086 1087 expr=add(@0,@1) pnnx.Expression pnnx_expr_203 1 1 1087 1088 expr=mul(@0,@0) torch.mean torch.mean_758 1 1 1088 1089 dim=(-1) keepdim=True $input=1088 pnnx.Expression pnnx_expr_199 2 1 1087 1089 1090 expr=mul(@0,pow(add(@1,1.938745e+00),-5.000000e-01)) torch.tensor_split slice_181 1 2 1090 1091 1092 dim=0 indices=(2) torch.cat torch.cat_703 2 1 1091 1092 1093 dim=0 nn.Linear encoder.emformer_layers.15.feed_forward_macaron.0 1 1 1093 1094 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_187 1 1 1094 1095 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_64 1 1 1095 1096 $input=1095 pnnx.Expression pnnx_expr_186 2 1 1094 1096 1097 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.15.feed_forward_macaron.4 1 1 1097 1098 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_184 2 1 1093 1098 1099 expr=add(@0,@1) torch.tensor_split slice_184 1 2 1099 1100 1101 dim=0 indices=(2) torch.cat torch.cat_704 2 1 1100 1101 1102 dim=0 nn.Linear encoder.emformer_layers.15.attention.emb_to_query 1 1 1102 1103 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.cat torch.cat_705 3 1 61 1100 1101 1104 dim=0 nn.Linear encoder.emformer_layers.15.attention.emb_to_key_value 1 1 1104 1105 bias=True in_features=144 out_features=288 @bias=(288)f32 @weight=(288,144)f32 torch.chunk torch.chunk_727 1 2 1105 1106 1107 chunks=2 dim=2 $input=1105 Tensor.view Tensor.view_533 1 1 1103 1108 shape=(10,4,36) $input=1103 torch.tensor_split slice_186 1 2 1106 1109 1110 dim=0 indices=(34) torch.cat torch.cat_706 3 1 1109 62 1110 1111 dim=0 Tensor.view Tensor.view_534 1 1 1111 1112 shape=(50,4,36) $input=1111 torch.tensor_split slice_188 1 2 1107 1113 1114 dim=0 indices=(34) torch.cat torch.cat_707 3 1 1113 63 1114 1115 dim=0 Tensor.view Tensor.view_535 1 1 1115 1116 shape=(50,4,36) $input=1115 torch.permute torch.permute_883 1 1 1108 1117 dims=(1,0,2) $input=1108 pnnx.Expression pnnx_expr_126 1 1 1117 1118 expr=mul(@0,1.666667e-01) torch.permute torch.permute_884 1 1 1112 1119 dims=(1,0,2) $input=1112 torch.permute torch.permute_886 1 1 1119 1120 dims=(0,2,1) $input=1119 torch.bmm torch.bmm_566 2 1 1118 1120 1121 $input=1118 $mat2=1120 F.softmax F.softmax_82 1 1 1121 1122 dim=-1 $input=1121 torch.permute torch.permute_885 1 1 1116 1123 dims=(1,0,2) $input=1116 torch.bmm torch.bmm_567 2 1 1122 1123 1124 $input=1122 $mat2=1123 torch.permute torch.permute_887 1 1 1124 1125 dims=(1,0,2) $input=1124 Tensor.reshape Tensor.reshape_99 1 1 1125 1126 shape=(-1,144) $input=1125 torch.unsqueeze torch.unsqueeze_908 1 1 1126 1127 dim=1 $input=1126 nn.Linear encoder.emformer_layers.15.attention.out_proj 1 1 1127 1128 bias=True in_features=144 out_features=144 @bias=(144)f32 @weight=(144,144)f32 torch.mean torch.mean_759 1 1 1101 1129 dim=(0) keepdim=True $input=1101 pnnx.Expression pnnx_expr_90 2 1 1099 1128 1130 expr=add(@0,@1) torch.tensor_split slice_189 1 2 1130 1131 1132 dim=0 indices=(2) torch.cat torch.cat_709 2 1 1132 1131 1133 dim=0 torch.permute torch.permute_888 1 1 1133 1134 dims=(1,2,0) $input=1133 nn.Conv1d encoder.emformer_layers.15.conv_module.pointwise_conv1 1 1 1134 1135 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=288 padding=(0) padding_mode=zeros stride=(1) @bias=(288)f32 @weight=(288,144,1)f32 F.glu F.glu_15 1 1 1135 1136 dim=1 $input=1135 torch.cat torch.cat_710 2 1 64 1136 1137 dim=2 nn.Conv1d encoder.emformer_layers.15.conv_module.depthwise_conv 1 1 1137 1138 bias=True dilation=(1) groups=144 in_channels=144 kernel_size=(31) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,1,31)f32 pnnx.Expression pnnx_expr_60 1 1 1138 1139 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_65 1 1 1139 1140 $input=1139 pnnx.Expression pnnx_expr_59 2 1 1138 1140 1141 expr=mul(@0,@1) nn.Conv1d encoder.emformer_layers.15.conv_module.pointwise_conv2 1 1 1141 1142 bias=True dilation=(1) groups=1 in_channels=144 kernel_size=(1) out_channels=144 padding=(0) padding_mode=zeros stride=(1) @bias=(144)f32 @weight=(144,144,1)f32 torch.tensor_split slice_191 1 2 1142 1143 1144 dim=2 indices=(8) torch.permute torch.permute_890 1 1 1144 1145 dims=(2,0,1) $input=1144 torch.permute torch.permute_889 1 1 1143 1146 dims=(2,0,1) $input=1143 torch.cat torch.cat_711 2 1 1145 1146 1147 dim=0 pnnx.Expression pnnx_expr_24 2 1 1130 1147 1148 expr=add(@0,@1) nn.Linear encoder.emformer_layers.15.feed_forward.0 1 1 1148 1149 bias=True in_features=144 out_features=576 @bias=(576)f32 @weight=(576,144)f32 pnnx.Expression pnnx_expr_21 1 1 1149 1150 expr=sub(@0,1.000000e+00) F.sigmoid F.sigmoid_66 1 1 1150 1151 $input=1150 pnnx.Expression pnnx_expr_20 2 1 1149 1151 1152 expr=mul(@0,@1) nn.Linear encoder.emformer_layers.15.feed_forward.4 1 1 1152 1153 bias=True in_features=576 out_features=144 @bias=(144)f32 @weight=(144,576)f32 pnnx.Expression pnnx_expr_18 2 1 1148 1153 1154 expr=add(@0,@1) pnnx.Expression pnnx_expr_13 1 1 1154 1155 expr=mul(@0,@0) torch.mean torch.mean_760 1 1 1155 1156 dim=(-1) keepdim=True $input=1155 pnnx.Expression pnnx_expr_9 2 1 1154 1156 1157 expr=mul(@0,pow(add(@1,1.524804e+00),-5.000000e-01)) torch.cat torch.cat_708 2 1 61 1129 1158 dim=0 torch.cat torch.cat_699 2 1 57 1062 1159 dim=0 torch.cat torch.cat_690 2 1 53 995 1160 dim=0 torch.cat torch.cat_681 2 1 49 928 1161 dim=0 torch.cat torch.cat_672 2 1 45 861 1162 dim=0 torch.cat torch.cat_663 2 1 41 794 1163 dim=0 torch.cat torch.cat_654 2 1 37 727 1164 dim=0 torch.cat torch.cat_645 2 1 33 660 1165 dim=0 torch.cat torch.cat_636 2 1 29 593 1166 dim=0 torch.cat torch.cat_627 2 1 25 526 1167 dim=0 torch.cat torch.cat_618 2 1 21 459 1168 dim=0 torch.cat torch.cat_609 2 1 17 392 1169 dim=0 torch.cat torch.cat_600 2 1 13 325 1170 dim=0 torch.cat torch.cat_591 2 1 9 258 1171 dim=0 torch.cat torch.cat_582 2 1 5 191 1172 dim=0 torch.cat torch.cat_573 2 1 1 124 1173 dim=0 Tensor.slice slice_289 1 1 1173 1174 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1173 Tensor.slice slice_287 1 1 106 1175 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=106 Tensor.slice slice_288 1 1 1175 1176 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1175 Tensor.slice slice_285 1 1 110 1177 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=110 Tensor.slice slice_286 1 1 1177 1178 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1177 Tensor.slice slice_284 1 1 132 1179 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=132 Tensor.slice slice_283 1 1 1172 1180 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1172 Tensor.slice slice_281 1 1 173 1181 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=173 Tensor.slice slice_282 1 1 1181 1182 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1181 Tensor.slice slice_279 1 1 177 1183 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=177 Tensor.slice slice_280 1 1 1183 1184 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1183 Tensor.slice slice_278 1 1 199 1185 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=199 Tensor.slice slice_277 1 1 1171 1186 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1171 Tensor.slice slice_275 1 1 240 1187 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=240 Tensor.slice slice_276 1 1 1187 1188 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1187 Tensor.slice slice_273 1 1 244 1189 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=244 Tensor.slice slice_274 1 1 1189 1190 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1189 Tensor.slice slice_272 1 1 266 1191 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=266 Tensor.slice slice_271 1 1 1170 1192 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1170 Tensor.slice slice_269 1 1 307 1193 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=307 Tensor.slice slice_270 1 1 1193 1194 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1193 Tensor.slice slice_267 1 1 311 1195 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=311 Tensor.slice slice_268 1 1 1195 1196 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1195 Tensor.slice slice_266 1 1 333 1197 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=333 Tensor.slice slice_265 1 1 1169 1198 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1169 Tensor.slice slice_263 1 1 374 1199 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=374 Tensor.slice slice_264 1 1 1199 1200 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1199 Tensor.slice slice_261 1 1 378 1201 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=378 Tensor.slice slice_262 1 1 1201 1202 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1201 Tensor.slice slice_260 1 1 400 1203 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=400 Tensor.slice slice_259 1 1 1168 1204 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1168 Tensor.slice slice_257 1 1 441 1205 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=441 Tensor.slice slice_258 1 1 1205 1206 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1205 Tensor.slice slice_255 1 1 445 1207 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=445 Tensor.slice slice_256 1 1 1207 1208 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1207 Tensor.slice slice_254 1 1 467 1209 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=467 Tensor.slice slice_253 1 1 1167 1210 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1167 Tensor.slice slice_251 1 1 508 1211 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=508 Tensor.slice slice_252 1 1 1211 1212 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1211 Tensor.slice slice_249 1 1 512 1213 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=512 Tensor.slice slice_250 1 1 1213 1214 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1213 Tensor.slice slice_248 1 1 534 1215 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=534 Tensor.slice slice_247 1 1 1166 1216 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1166 Tensor.slice slice_245 1 1 575 1217 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=575 Tensor.slice slice_246 1 1 1217 1218 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1217 Tensor.slice slice_243 1 1 579 1219 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=579 Tensor.slice slice_244 1 1 1219 1220 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1219 Tensor.slice slice_242 1 1 601 1221 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=601 Tensor.slice slice_241 1 1 1165 1222 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1165 Tensor.slice slice_239 1 1 642 1223 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=642 Tensor.slice slice_240 1 1 1223 1224 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1223 Tensor.slice slice_237 1 1 646 1225 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=646 Tensor.slice slice_238 1 1 1225 1226 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1225 Tensor.slice slice_236 1 1 668 1227 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=668 Tensor.slice slice_235 1 1 1164 1228 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1164 Tensor.slice slice_233 1 1 709 1229 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=709 Tensor.slice slice_234 1 1 1229 1230 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1229 Tensor.slice slice_231 1 1 713 1231 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=713 Tensor.slice slice_232 1 1 1231 1232 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1231 Tensor.slice slice_230 1 1 735 1233 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=735 Tensor.slice slice_229 1 1 1163 1234 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1163 Tensor.slice slice_227 1 1 776 1235 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=776 Tensor.slice slice_228 1 1 1235 1236 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1235 Tensor.slice slice_225 1 1 780 1237 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=780 Tensor.slice slice_226 1 1 1237 1238 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1237 Tensor.slice slice_224 1 1 802 1239 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=802 Tensor.slice slice_223 1 1 1162 1240 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1162 Tensor.slice slice_221 1 1 843 1241 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=843 Tensor.slice slice_222 1 1 1241 1242 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1241 Tensor.slice slice_219 1 1 847 1243 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=847 Tensor.slice slice_220 1 1 1243 1244 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1243 Tensor.slice slice_218 1 1 869 1245 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=869 Tensor.slice slice_217 1 1 1161 1246 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1161 Tensor.slice slice_215 1 1 910 1247 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=910 Tensor.slice slice_216 1 1 1247 1248 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1247 Tensor.slice slice_213 1 1 914 1249 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=914 Tensor.slice slice_214 1 1 1249 1250 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1249 Tensor.slice slice_212 1 1 936 1251 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=936 Tensor.slice slice_211 1 1 1160 1252 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1160 Tensor.slice slice_209 1 1 977 1253 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=977 Tensor.slice slice_210 1 1 1253 1254 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1253 Tensor.slice slice_207 1 1 981 1255 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=981 Tensor.slice slice_208 1 1 1255 1256 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1255 Tensor.slice slice_206 1 1 1003 1257 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=1003 Tensor.slice slice_205 1 1 1159 1258 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1159 Tensor.slice slice_203 1 1 1044 1259 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=1044 Tensor.slice slice_204 1 1 1259 1260 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1259 Tensor.slice slice_201 1 1 1048 1261 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=1048 Tensor.slice slice_202 1 1 1261 1262 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1261 Tensor.slice slice_200 1 1 1070 1263 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=1070 Tensor.slice slice_199 1 1 1158 1264 dims=(0) ends=(2147483647) starts=(1) steps=(1) $input=1158 Tensor.slice slice_197 1 1 1111 1265 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=1111 Tensor.slice slice_198 1 1 1265 1266 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1265 Tensor.slice slice_195 1 1 1115 1267 dims=(0) ends=(2147483647) starts=(34) steps=(1) $input=1115 Tensor.slice slice_196 1 1 1267 1268 dims=(0) ends=(2147483647) starts=(-8) steps=(1) $input=1267 Tensor.slice slice_194 1 1 1137 1269 dims=(2) ends=(-2) starts=(-32) steps=(1) $input=1137 pnnx.Expression pnnx_expr_0 64 1 1174 1176 1178 1179 1180 1182 1184 1185 1186 1188 1190 1191 1192 1194 1196 1197 1198 1200 1202 1203 1204 1206 1208 1209 1210 1212 1214 1215 1216 1218 1220 1221 1222 1224 1226 1227 1228 1230 1232 1233 1234 1236 1238 1239 1240 1242 1244 1245 1246 1248 1250 1251 1252 1254 1256 1257 1258 1260 1262 1263 1264 1266 1268 1269 1270 expr=[@0,@1,@2,@3,@4,@5,@6,@7,@8,@9,@10,@11,@12,@13,@14,@15,@16,@17,@18,@19,@20,@21,@22,@23,@24,@25,@26,@27,@28,@29,@30,@31,@32,@33,@34,@35,@36,@37,@38,@39,@40,@41,@42,@43,@44,@45,@46,@47,@48,@49,@50,@51,@52,@53,@54,@55,@56,@57,@58,@59,@60,@61,@62,@63] Tensor.slice slice_193 1 1 1157 1271 dims=(0) ends=(2147483647) starts=(2) steps=(1) $input=1157 torch.permute torch.permute_891 1 1 1271 1272 dims=(1,0,2) $input=1271 prim::TupleConstruct pnnx_4332 2 1 1272 1270 1273 pnnx.Output pnnx_output_0 1 0 1273