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[PT2] Add port ids to reference graphs (openvinotoolkit#3267)
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### Changes

Add `in_port_id` and `out_port_id` fields for edge data in reference
files.

### Reason for changes

To check port_ids in for edge
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@AlexanderDokuchaev
AlexanderDokuchaev authored Feb 11, 2025
1 parent c619360 commit c24bf74
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Showing 33 changed files with 14,950 additions and 14,926 deletions.
14 changes: 7 additions & 7 deletions tests/torch2/data/function_hook/nncf_graph/convert_to_nncf_graph.dot
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Expand Up @@ -7,11 +7,11 @@ x [id=0, metatype=PTInputNoopMetatype, type=nncf_model_input];
"conv/post_hook__conv-conv2d-0__0[0]/add/0" [id=5, metatype=PTAddMetatype, type=add];
"/relu/0" [id=6, metatype=PTRELUMetatype, type=relu];
output [id=7, metatype=PTOutputNoopMetatype, type=nncf_model_output];
x -> "conv/conv2d/0" [dtype=float, shape="(1, 1, 3, 3)"];
"conv.weight" -> "conv/conv2d/0" [dtype=float, shape="(1, 1, 1, 1)"];
"conv.bias" -> "conv/conv2d/0" [dtype=float, shape="(1,)"];
"conv/conv2d/0" -> "conv/post_hook__conv-conv2d-0__0[0]/add/0" [dtype=float, shape="(1, 1, 3, 3)"];
"__nncf_hooks.post_hooks.conv/conv2d/0__0.0.w" -> "conv/post_hook__conv-conv2d-0__0[0]/add/0" [dtype=float, shape="(1,)"];
"conv/post_hook__conv-conv2d-0__0[0]/add/0" -> "/relu/0" [dtype=float, shape="(1, 1, 3, 3)"];
"/relu/0" -> output [dtype=float, shape="(1, 1, 3, 3)"];
x -> "conv/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 1, 3, 3)"];
"conv.weight" -> "conv/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(1, 1, 1, 1)"];
"conv.bias" -> "conv/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(1,)"];
"conv/conv2d/0" -> "conv/post_hook__conv-conv2d-0__0[0]/add/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 1, 3, 3)"];
"__nncf_hooks.post_hooks.conv/conv2d/0__0.0.w" -> "conv/post_hook__conv-conv2d-0__0[0]/add/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(1,)"];
"conv/post_hook__conv-conv2d-0__0[0]/add/0" -> "/relu/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 1, 3, 3)"];
"/relu/0" -> output [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 1, 3, 3)"];
}
4 changes: 2 additions & 2 deletions tests/torch2/data/function_hook/nncf_graph/convert_to_nncf_graph_multi_edges.dot
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Expand Up @@ -2,6 +2,6 @@ strict digraph {
x [id=0, metatype=PTInputNoopMetatype, type=nncf_model_input];
"/add/0" [id=1, metatype=PTAddMetatype, type=add];
output [id=2, metatype=PTOutputNoopMetatype, type=nncf_model_output];
x -> "/add/0" [dtype=float, parallel_input_port_ids="[1]", shape="(1, 1)"];
"/add/0" -> output [dtype=float, shape="(1, 1)"];
x -> "/add/0" [dtype=float, in_port_id=0, out_port_id=0, parallel_input_port_ids="[1]", shape="(1, 1)"];
"/add/0" -> output [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 1)"];
}
1,454 changes: 727 additions & 727 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_convnext_small.dot
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3,146 changes: 1,573 additions & 1,573 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_densenet121.dot
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1,154 changes: 577 additions & 577 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_efficientnet_b0.dot
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1,644 changes: 822 additions & 822 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_inception_v3.dot
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852 changes: 426 additions & 426 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_mobilenet_v2.dot
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766 changes: 383 additions & 383 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_mobilenet_v3_small.dot
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360 changes: 180 additions & 180 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_resnet18.dot
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918 changes: 459 additions & 459 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_resnext50_32x4d.dot
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1,088 changes: 544 additions & 544 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_shufflenet_v2_x0_5.dot
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254 changes: 127 additions & 127 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_squeezenet1_0.dot
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3,828 changes: 1,914 additions & 1,914 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_swin_v2_b.dot
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146 changes: 73 additions & 73 deletions tests/torch2/data/function_hook/nncf_graph/model_graph_vgg16.dot
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Expand Up @@ -73,77 +73,77 @@ x [id=0, metatype=PTInputNoopMetatype, type=nncf_model_input];
"classifier.6.bias" [id=71, metatype=PTConstNoopMetatype, type=nncf_model_const];
"classifier/6/linear/0" [id=72, metatype=PTLinearMetatype, type=linear];
output [id=73, metatype=PTOutputNoopMetatype, type=nncf_model_output];
x -> "features/0/conv2d/0" [dtype=float, shape="(1, 3, 32, 32)"];
"features.0.weight" -> "features/0/conv2d/0" [dtype=float, shape="(64, 3, 3, 3)"];
"features.0.bias" -> "features/0/conv2d/0" [dtype=float, shape="(64,)"];
"features/0/conv2d/0" -> "features/1/relu_/0" [dtype=float, shape="(1, 64, 32, 32)"];
"features/1/relu_/0" -> "features/2/conv2d/0" [dtype=float, shape="(1, 64, 32, 32)"];
"features.2.weight" -> "features/2/conv2d/0" [dtype=float, shape="(64, 64, 3, 3)"];
"features.2.bias" -> "features/2/conv2d/0" [dtype=float, shape="(64,)"];
"features/2/conv2d/0" -> "features/3/relu_/0" [dtype=float, shape="(1, 64, 32, 32)"];
"features/3/relu_/0" -> "features/4/max_pool2d/0" [dtype=float, shape="(1, 64, 32, 32)"];
"features/4/max_pool2d/0" -> "features/5/conv2d/0" [dtype=float, shape="(1, 64, 16, 16)"];
"features.5.weight" -> "features/5/conv2d/0" [dtype=float, shape="(128, 64, 3, 3)"];
"features.5.bias" -> "features/5/conv2d/0" [dtype=float, shape="(128,)"];
"features/5/conv2d/0" -> "features/6/relu_/0" [dtype=float, shape="(1, 128, 16, 16)"];
"features/6/relu_/0" -> "features/7/conv2d/0" [dtype=float, shape="(1, 128, 16, 16)"];
"features.7.weight" -> "features/7/conv2d/0" [dtype=float, shape="(128, 128, 3, 3)"];
"features.7.bias" -> "features/7/conv2d/0" [dtype=float, shape="(128,)"];
"features/7/conv2d/0" -> "features/8/relu_/0" [dtype=float, shape="(1, 128, 16, 16)"];
"features/8/relu_/0" -> "features/9/max_pool2d/0" [dtype=float, shape="(1, 128, 16, 16)"];
"features/9/max_pool2d/0" -> "features/10/conv2d/0" [dtype=float, shape="(1, 128, 8, 8)"];
"features.10.weight" -> "features/10/conv2d/0" [dtype=float, shape="(256, 128, 3, 3)"];
"features.10.bias" -> "features/10/conv2d/0" [dtype=float, shape="(256,)"];
"features/10/conv2d/0" -> "features/11/relu_/0" [dtype=float, shape="(1, 256, 8, 8)"];
"features/11/relu_/0" -> "features/12/conv2d/0" [dtype=float, shape="(1, 256, 8, 8)"];
"features.12.weight" -> "features/12/conv2d/0" [dtype=float, shape="(256, 256, 3, 3)"];
"features.12.bias" -> "features/12/conv2d/0" [dtype=float, shape="(256,)"];
"features/12/conv2d/0" -> "features/13/relu_/0" [dtype=float, shape="(1, 256, 8, 8)"];
"features/13/relu_/0" -> "features/14/conv2d/0" [dtype=float, shape="(1, 256, 8, 8)"];
"features.14.weight" -> "features/14/conv2d/0" [dtype=float, shape="(256, 256, 3, 3)"];
"features.14.bias" -> "features/14/conv2d/0" [dtype=float, shape="(256,)"];
"features/14/conv2d/0" -> "features/15/relu_/0" [dtype=float, shape="(1, 256, 8, 8)"];
"features/15/relu_/0" -> "features/16/max_pool2d/0" [dtype=float, shape="(1, 256, 8, 8)"];
"features/16/max_pool2d/0" -> "features/17/conv2d/0" [dtype=float, shape="(1, 256, 4, 4)"];
"features.17.weight" -> "features/17/conv2d/0" [dtype=float, shape="(512, 256, 3, 3)"];
"features.17.bias" -> "features/17/conv2d/0" [dtype=float, shape="(512,)"];
"features/17/conv2d/0" -> "features/18/relu_/0" [dtype=float, shape="(1, 512, 4, 4)"];
"features/18/relu_/0" -> "features/19/conv2d/0" [dtype=float, shape="(1, 512, 4, 4)"];
"features.19.weight" -> "features/19/conv2d/0" [dtype=float, shape="(512, 512, 3, 3)"];
"features.19.bias" -> "features/19/conv2d/0" [dtype=float, shape="(512,)"];
"features/19/conv2d/0" -> "features/20/relu_/0" [dtype=float, shape="(1, 512, 4, 4)"];
"features/20/relu_/0" -> "features/21/conv2d/0" [dtype=float, shape="(1, 512, 4, 4)"];
"features.21.weight" -> "features/21/conv2d/0" [dtype=float, shape="(512, 512, 3, 3)"];
"features.21.bias" -> "features/21/conv2d/0" [dtype=float, shape="(512,)"];
"features/21/conv2d/0" -> "features/22/relu_/0" [dtype=float, shape="(1, 512, 4, 4)"];
"features/22/relu_/0" -> "features/23/max_pool2d/0" [dtype=float, shape="(1, 512, 4, 4)"];
"features/23/max_pool2d/0" -> "features/24/conv2d/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features.24.weight" -> "features/24/conv2d/0" [dtype=float, shape="(512, 512, 3, 3)"];
"features.24.bias" -> "features/24/conv2d/0" [dtype=float, shape="(512,)"];
"features/24/conv2d/0" -> "features/25/relu_/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features/25/relu_/0" -> "features/26/conv2d/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features.26.weight" -> "features/26/conv2d/0" [dtype=float, shape="(512, 512, 3, 3)"];
"features.26.bias" -> "features/26/conv2d/0" [dtype=float, shape="(512,)"];
"features/26/conv2d/0" -> "features/27/relu_/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features/27/relu_/0" -> "features/28/conv2d/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features.28.weight" -> "features/28/conv2d/0" [dtype=float, shape="(512, 512, 3, 3)"];
"features.28.bias" -> "features/28/conv2d/0" [dtype=float, shape="(512,)"];
"features/28/conv2d/0" -> "features/29/relu_/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features/29/relu_/0" -> "features/30/max_pool2d/0" [dtype=float, shape="(1, 512, 2, 2)"];
"features/30/max_pool2d/0" -> "avgpool/adaptive_avg_pool2d/0" [dtype=float, shape="(1, 512, 1, 1)"];
"avgpool/adaptive_avg_pool2d/0" -> "/flatten/0" [dtype=float, shape="(1, 512, 7, 7)"];
"/flatten/0" -> "classifier/0/linear/0" [dtype=float, shape="(1, 25088)"];
"classifier.0.weight" -> "classifier/0/linear/0" [dtype=float, shape="(4096, 25088)"];
"classifier.0.bias" -> "classifier/0/linear/0" [dtype=float, shape="(4096,)"];
"classifier/0/linear/0" -> "classifier/1/relu_/0" [dtype=float, shape="(1, 4096)"];
"classifier/1/relu_/0" -> "classifier/2/dropout/0" [dtype=float, shape="(1, 4096)"];
"classifier/2/dropout/0" -> "classifier/3/linear/0" [dtype=float, shape="(1, 4096)"];
"classifier.3.weight" -> "classifier/3/linear/0" [dtype=float, shape="(4096, 4096)"];
"classifier.3.bias" -> "classifier/3/linear/0" [dtype=float, shape="(4096,)"];
"classifier/3/linear/0" -> "classifier/4/relu_/0" [dtype=float, shape="(1, 4096)"];
"classifier/4/relu_/0" -> "classifier/5/dropout/0" [dtype=float, shape="(1, 4096)"];
"classifier/5/dropout/0" -> "classifier/6/linear/0" [dtype=float, shape="(1, 4096)"];
"classifier.6.weight" -> "classifier/6/linear/0" [dtype=float, shape="(1000, 4096)"];
"classifier.6.bias" -> "classifier/6/linear/0" [dtype=float, shape="(1000,)"];
"classifier/6/linear/0" -> output [dtype=float, shape="(1, 1000)"];
x -> "features/0/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 3, 32, 32)"];
"features.0.weight" -> "features/0/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(64, 3, 3, 3)"];
"features.0.bias" -> "features/0/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(64,)"];
"features/0/conv2d/0" -> "features/1/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 64, 32, 32)"];
"features/1/relu_/0" -> "features/2/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 64, 32, 32)"];
"features.2.weight" -> "features/2/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(64, 64, 3, 3)"];
"features.2.bias" -> "features/2/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(64,)"];
"features/2/conv2d/0" -> "features/3/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 64, 32, 32)"];
"features/3/relu_/0" -> "features/4/max_pool2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 64, 32, 32)"];
"features/4/max_pool2d/0" -> "features/5/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 64, 16, 16)"];
"features.5.weight" -> "features/5/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(128, 64, 3, 3)"];
"features.5.bias" -> "features/5/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(128,)"];
"features/5/conv2d/0" -> "features/6/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 128, 16, 16)"];
"features/6/relu_/0" -> "features/7/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 128, 16, 16)"];
"features.7.weight" -> "features/7/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(128, 128, 3, 3)"];
"features.7.bias" -> "features/7/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(128,)"];
"features/7/conv2d/0" -> "features/8/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 128, 16, 16)"];
"features/8/relu_/0" -> "features/9/max_pool2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 128, 16, 16)"];
"features/9/max_pool2d/0" -> "features/10/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 128, 8, 8)"];
"features.10.weight" -> "features/10/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(256, 128, 3, 3)"];
"features.10.bias" -> "features/10/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(256,)"];
"features/10/conv2d/0" -> "features/11/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 8, 8)"];
"features/11/relu_/0" -> "features/12/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 8, 8)"];
"features.12.weight" -> "features/12/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(256, 256, 3, 3)"];
"features.12.bias" -> "features/12/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(256,)"];
"features/12/conv2d/0" -> "features/13/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 8, 8)"];
"features/13/relu_/0" -> "features/14/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 8, 8)"];
"features.14.weight" -> "features/14/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(256, 256, 3, 3)"];
"features.14.bias" -> "features/14/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(256,)"];
"features/14/conv2d/0" -> "features/15/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 8, 8)"];
"features/15/relu_/0" -> "features/16/max_pool2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 8, 8)"];
"features/16/max_pool2d/0" -> "features/17/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 256, 4, 4)"];
"features.17.weight" -> "features/17/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(512, 256, 3, 3)"];
"features.17.bias" -> "features/17/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(512,)"];
"features/17/conv2d/0" -> "features/18/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 4, 4)"];
"features/18/relu_/0" -> "features/19/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 4, 4)"];
"features.19.weight" -> "features/19/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(512, 512, 3, 3)"];
"features.19.bias" -> "features/19/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(512,)"];
"features/19/conv2d/0" -> "features/20/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 4, 4)"];
"features/20/relu_/0" -> "features/21/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 4, 4)"];
"features.21.weight" -> "features/21/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(512, 512, 3, 3)"];
"features.21.bias" -> "features/21/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(512,)"];
"features/21/conv2d/0" -> "features/22/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 4, 4)"];
"features/22/relu_/0" -> "features/23/max_pool2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 4, 4)"];
"features/23/max_pool2d/0" -> "features/24/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features.24.weight" -> "features/24/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(512, 512, 3, 3)"];
"features.24.bias" -> "features/24/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(512,)"];
"features/24/conv2d/0" -> "features/25/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features/25/relu_/0" -> "features/26/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features.26.weight" -> "features/26/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(512, 512, 3, 3)"];
"features.26.bias" -> "features/26/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(512,)"];
"features/26/conv2d/0" -> "features/27/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features/27/relu_/0" -> "features/28/conv2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features.28.weight" -> "features/28/conv2d/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(512, 512, 3, 3)"];
"features.28.bias" -> "features/28/conv2d/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(512,)"];
"features/28/conv2d/0" -> "features/29/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features/29/relu_/0" -> "features/30/max_pool2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 2, 2)"];
"features/30/max_pool2d/0" -> "avgpool/adaptive_avg_pool2d/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 1, 1)"];
"avgpool/adaptive_avg_pool2d/0" -> "/flatten/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 512, 7, 7)"];
"/flatten/0" -> "classifier/0/linear/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 25088)"];
"classifier.0.weight" -> "classifier/0/linear/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(4096, 25088)"];
"classifier.0.bias" -> "classifier/0/linear/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(4096,)"];
"classifier/0/linear/0" -> "classifier/1/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 4096)"];
"classifier/1/relu_/0" -> "classifier/2/dropout/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 4096)"];
"classifier/2/dropout/0" -> "classifier/3/linear/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 4096)"];
"classifier.3.weight" -> "classifier/3/linear/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(4096, 4096)"];
"classifier.3.bias" -> "classifier/3/linear/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(4096,)"];
"classifier/3/linear/0" -> "classifier/4/relu_/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 4096)"];
"classifier/4/relu_/0" -> "classifier/5/dropout/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 4096)"];
"classifier/5/dropout/0" -> "classifier/6/linear/0" [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 4096)"];
"classifier.6.weight" -> "classifier/6/linear/0" [dtype=float, in_port_id=1, out_port_id=0, shape="(1000, 4096)"];
"classifier.6.bias" -> "classifier/6/linear/0" [dtype=float, in_port_id=2, out_port_id=0, shape="(1000,)"];
"classifier/6/linear/0" -> output [dtype=float, in_port_id=0, out_port_id=0, shape="(1, 1000)"];
}
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