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bert-squad-nncf-mvmt-hybrid-lt

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Add ckpt@35K

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  1. .gitattributes +1 -0
  2. checkpoint-35000/NNCFNetwork.onnx +3 -0
  3. checkpoint-35000/config.json +25 -0
  4. checkpoint-35000/onnx_sparsity.csv +147 -0
  5. checkpoint-35000/onnx_sparsity.md +148 -0
  6. checkpoint-35000/optimizer.pt +3 -0
  7. checkpoint-35000/pytorch_model.bin +3 -0
  8. checkpoint-35000/rng_state.pth +3 -0
  9. checkpoint-35000/scheduler.pt +3 -0
  10. checkpoint-35000/special_tokens_map.json +1 -0
  11. checkpoint-35000/tokenizer.json +0 -0
  12. checkpoint-35000/tokenizer_config.json +1 -0
  13. checkpoint-35000/torch_mask_structures.csv +73 -0
  14. checkpoint-35000/torch_mask_structures.md +74 -0
  15. checkpoint-35000/trainer_state.json +3 -0
  16. checkpoint-35000/training_args.bin +3 -0
  17. checkpoint-35000/vocab.txt +0 -0
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+ 11,nncf_module.bert.encoder.layer.1.output.dense,3,"(768, 3072)","(768, 2923)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0
14
+ 12,nncf_module.bert.encoder.layer.2.attention.self.value,4,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
15
+ 13,nncf_module.bert.encoder.layer.2.attention.output.dense,4,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
16
+ 14,nncf_module.bert.encoder.layer.2.attention.self.key,4,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
17
+ 15,nncf_module.bert.encoder.layer.2.attention.self.query,4,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
18
+ 16,nncf_module.bert.encoder.layer.2.output.dense,5,"(768, 3072)","(768, 2980)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0
19
+ 17,nncf_module.bert.encoder.layer.2.intermediate.dense,5,"(3072, 768)","(2980, 768)","(3072,)","(2980,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
20
+ 18,nncf_module.bert.encoder.layer.3.attention.output.dense,6,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
21
+ 19,nncf_module.bert.encoder.layer.3.attention.self.value,6,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
22
+ 20,nncf_module.bert.encoder.layer.3.attention.self.key,6,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
23
+ 21,nncf_module.bert.encoder.layer.3.attention.self.query,6,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
24
+ 22,nncf_module.bert.encoder.layer.3.intermediate.dense,7,"(3072, 768)","(2957, 768)","(3072,)","(2957,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
25
+ 23,nncf_module.bert.encoder.layer.3.output.dense,7,"(768, 3072)","(768, 2957)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0
26
+ 24,nncf_module.bert.encoder.layer.4.attention.self.key,8,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
27
+ 25,nncf_module.bert.encoder.layer.4.attention.self.value,8,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
28
+ 26,nncf_module.bert.encoder.layer.4.attention.output.dense,8,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
29
+ 27,nncf_module.bert.encoder.layer.4.attention.self.query,8,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
30
+ 28,nncf_module.bert.encoder.layer.4.intermediate.dense,9,"(3072, 768)","(2906, 768)","(3072,)","(2906,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
31
+ 29,nncf_module.bert.encoder.layer.4.output.dense,9,"(768, 3072)","(768, 2906)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0
32
+ 30,nncf_module.bert.encoder.layer.5.attention.self.value,10,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
33
+ 31,nncf_module.bert.encoder.layer.5.attention.output.dense,10,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
34
+ 32,nncf_module.bert.encoder.layer.5.attention.self.query,10,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
35
+ 33,nncf_module.bert.encoder.layer.5.attention.self.key,10,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
36
+ 34,nncf_module.bert.encoder.layer.5.intermediate.dense,11,"(3072, 768)","(2865, 768)","(3072,)","(2865,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
37
+ 35,nncf_module.bert.encoder.layer.5.output.dense,11,"(768, 3072)","(768, 2865)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0
38
+ 36,nncf_module.bert.encoder.layer.6.attention.self.value,12,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
39
+ 37,nncf_module.bert.encoder.layer.6.attention.self.query,12,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
40
+ 38,nncf_module.bert.encoder.layer.6.attention.self.key,12,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
41
+ 39,nncf_module.bert.encoder.layer.6.attention.output.dense,12,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
42
+ 40,nncf_module.bert.encoder.layer.6.output.dense,13,"(768, 3072)","(768, 2759)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0
43
+ 41,nncf_module.bert.encoder.layer.6.intermediate.dense,13,"(3072, 768)","(2759, 768)","(3072,)","(2759,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
44
+ 42,nncf_module.bert.encoder.layer.7.attention.self.query,14,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
45
+ 43,nncf_module.bert.encoder.layer.7.attention.self.key,14,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
46
+ 44,nncf_module.bert.encoder.layer.7.attention.self.value,14,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
47
+ 45,nncf_module.bert.encoder.layer.7.attention.output.dense,14,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
48
+ 46,nncf_module.bert.encoder.layer.7.intermediate.dense,15,"(3072, 768)","(2569, 768)","(3072,)","(2569,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
49
+ 47,nncf_module.bert.encoder.layer.7.output.dense,15,"(768, 3072)","(768, 2569)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0
50
+ 48,nncf_module.bert.encoder.layer.8.attention.self.key,16,"(768, 768)","(256, 768)","(768,)","(256,)","[1, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
51
+ 49,nncf_module.bert.encoder.layer.8.attention.self.value,16,"(768, 768)","(256, 768)","(768,)","(256,)","[1, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
52
+ 50,nncf_module.bert.encoder.layer.8.attention.self.query,16,"(768, 768)","(256, 768)","(768,)","(256,)","[1, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
53
+ 51,nncf_module.bert.encoder.layer.8.attention.output.dense,16,"(768, 768)","(768, 256)","(768,)","(768,)","[1, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
54
+ 52,nncf_module.bert.encoder.layer.8.output.dense,17,"(768, 3072)","(768, 2094)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0
55
+ 53,nncf_module.bert.encoder.layer.8.intermediate.dense,17,"(3072, 768)","(2094, 768)","(3072,)","(2094,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
56
+ 54,nncf_module.bert.encoder.layer.9.attention.self.query,18,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
57
+ 55,nncf_module.bert.encoder.layer.9.attention.output.dense,18,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
58
+ 56,nncf_module.bert.encoder.layer.9.attention.self.value,18,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
59
+ 57,nncf_module.bert.encoder.layer.9.attention.self.key,18,"(768, 768)","(768, 768)","(768,)","(768,)","[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
60
+ 58,nncf_module.bert.encoder.layer.9.intermediate.dense,19,"(3072, 768)","(1009, 768)","(3072,)","(1009,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
61
+ 59,nncf_module.bert.encoder.layer.9.output.dense,19,"(768, 3072)","(768, 1009)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0
62
+ 60,nncf_module.bert.encoder.layer.10.attention.self.key,20,"(768, 768)","(320, 768)","(768,)","(320,)","[0, 3, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
63
+ 61,nncf_module.bert.encoder.layer.10.attention.self.value,20,"(768, 768)","(320, 768)","(768,)","(320,)","[0, 3, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
64
+ 62,nncf_module.bert.encoder.layer.10.attention.self.query,20,"(768, 768)","(320, 768)","(768,)","(320,)","[0, 3, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
65
+ 63,nncf_module.bert.encoder.layer.10.attention.output.dense,20,"(768, 768)","(768, 320)","(768,)","(768,)","[0, 3, 9, 10, 11]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
66
+ 64,nncf_module.bert.encoder.layer.10.output.dense,21,"(768, 3072)","(768, 743)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0
67
+ 65,nncf_module.bert.encoder.layer.10.intermediate.dense,21,"(3072, 768)","(743, 768)","(3072,)","(743,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
68
+ 66,nncf_module.bert.encoder.layer.11.attention.output.dense,22,"(768, 768)","(768, 192)","(768,)","(768,)","[1, 2, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
69
+ 67,nncf_module.bert.encoder.layer.11.attention.self.key,22,"(768, 768)","(192, 768)","(768,)","(192,)","[1, 2, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
70
+ 68,nncf_module.bert.encoder.layer.11.attention.self.value,22,"(768, 768)","(192, 768)","(768,)","(192,)","[1, 2, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
71
+ 69,nncf_module.bert.encoder.layer.11.attention.self.query,22,"(768, 768)","(192, 768)","(768,)","(192,)","[1, 2, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
72
+ 70,nncf_module.bert.encoder.layer.11.intermediate.dense,23,"(3072, 768)","(605, 768)","(3072,)","(605,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
73
+ 71,nncf_module.bert.encoder.layer.11.output.dense,23,"(768, 3072)","(768, 605)","(768,)","(768,)",skip reporting,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0
checkpoint-35000/torch_mask_structures.md ADDED
@@ -0,0 +1,74 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ | | pt_module_name | block_id | weight_shape | prune_w_shape | bias_shape | prune_b_shape | head_id_to_keep | nncf_graph_node |
2
+ |---:|:---------------------------------------------------------|-----------:|:---------------|:----------------|:-------------|:----------------|:---------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
3
+ | 0 | nncf_module.bert.encoder.layer.0.attention.output.dense | 0 | (768, 768) | (768, 192) | (768,) | (768,) | [3, 8, 10] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
4
+ | 1 | nncf_module.bert.encoder.layer.0.attention.self.value | 0 | (768, 768) | (192, 768) | (768,) | (192,) | [3, 8, 10] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
5
+ | 2 | nncf_module.bert.encoder.layer.0.attention.self.key | 0 | (768, 768) | (192, 768) | (768,) | (192,) | [3, 8, 10] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
6
+ | 3 | nncf_module.bert.encoder.layer.0.attention.self.query | 0 | (768, 768) | (192, 768) | (768,) | (192,) | [3, 8, 10] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
7
+ | 4 | nncf_module.bert.encoder.layer.0.output.dense | 1 | (768, 3072) | (768, 2940) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
8
+ | 5 | nncf_module.bert.encoder.layer.0.intermediate.dense | 1 | (3072, 768) | (2940, 768) | (3072,) | (2940,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
9
+ | 6 | nncf_module.bert.encoder.layer.1.attention.self.key | 2 | (768, 768) | (256, 768) | (768,) | (256,) | [4, 7, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
10
+ | 7 | nncf_module.bert.encoder.layer.1.attention.self.query | 2 | (768, 768) | (256, 768) | (768,) | (256,) | [4, 7, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
11
+ | 8 | nncf_module.bert.encoder.layer.1.attention.output.dense | 2 | (768, 768) | (768, 256) | (768,) | (768,) | [4, 7, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
12
+ | 9 | nncf_module.bert.encoder.layer.1.attention.self.value | 2 | (768, 768) | (256, 768) | (768,) | (256,) | [4, 7, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
13
+ | 10 | nncf_module.bert.encoder.layer.1.intermediate.dense | 3 | (3072, 768) | (2923, 768) | (3072,) | (2923,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
14
+ | 11 | nncf_module.bert.encoder.layer.1.output.dense | 3 | (768, 3072) | (768, 2923) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
15
+ | 12 | nncf_module.bert.encoder.layer.2.attention.self.value | 4 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
16
+ | 13 | nncf_module.bert.encoder.layer.2.attention.output.dense | 4 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
17
+ | 14 | nncf_module.bert.encoder.layer.2.attention.self.key | 4 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
18
+ | 15 | nncf_module.bert.encoder.layer.2.attention.self.query | 4 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
19
+ | 16 | nncf_module.bert.encoder.layer.2.output.dense | 5 | (768, 3072) | (768, 2980) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
20
+ | 17 | nncf_module.bert.encoder.layer.2.intermediate.dense | 5 | (3072, 768) | (2980, 768) | (3072,) | (2980,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
21
+ | 18 | nncf_module.bert.encoder.layer.3.attention.output.dense | 6 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
22
+ | 19 | nncf_module.bert.encoder.layer.3.attention.self.value | 6 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
23
+ | 20 | nncf_module.bert.encoder.layer.3.attention.self.key | 6 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
24
+ | 21 | nncf_module.bert.encoder.layer.3.attention.self.query | 6 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
25
+ | 22 | nncf_module.bert.encoder.layer.3.intermediate.dense | 7 | (3072, 768) | (2957, 768) | (3072,) | (2957,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
26
+ | 23 | nncf_module.bert.encoder.layer.3.output.dense | 7 | (768, 3072) | (768, 2957) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
27
+ | 24 | nncf_module.bert.encoder.layer.4.attention.self.key | 8 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
28
+ | 25 | nncf_module.bert.encoder.layer.4.attention.self.value | 8 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
29
+ | 26 | nncf_module.bert.encoder.layer.4.attention.output.dense | 8 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
30
+ | 27 | nncf_module.bert.encoder.layer.4.attention.self.query | 8 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
31
+ | 28 | nncf_module.bert.encoder.layer.4.intermediate.dense | 9 | (3072, 768) | (2906, 768) | (3072,) | (2906,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
32
+ | 29 | nncf_module.bert.encoder.layer.4.output.dense | 9 | (768, 3072) | (768, 2906) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
33
+ | 30 | nncf_module.bert.encoder.layer.5.attention.self.value | 10 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
34
+ | 31 | nncf_module.bert.encoder.layer.5.attention.output.dense | 10 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
35
+ | 32 | nncf_module.bert.encoder.layer.5.attention.self.query | 10 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
36
+ | 33 | nncf_module.bert.encoder.layer.5.attention.self.key | 10 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
37
+ | 34 | nncf_module.bert.encoder.layer.5.intermediate.dense | 11 | (3072, 768) | (2865, 768) | (3072,) | (2865,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
38
+ | 35 | nncf_module.bert.encoder.layer.5.output.dense | 11 | (768, 3072) | (768, 2865) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
39
+ | 36 | nncf_module.bert.encoder.layer.6.attention.self.value | 12 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
40
+ | 37 | nncf_module.bert.encoder.layer.6.attention.self.query | 12 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
41
+ | 38 | nncf_module.bert.encoder.layer.6.attention.self.key | 12 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
42
+ | 39 | nncf_module.bert.encoder.layer.6.attention.output.dense | 12 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
43
+ | 40 | nncf_module.bert.encoder.layer.6.output.dense | 13 | (768, 3072) | (768, 2759) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
44
+ | 41 | nncf_module.bert.encoder.layer.6.intermediate.dense | 13 | (3072, 768) | (2759, 768) | (3072,) | (2759,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
45
+ | 42 | nncf_module.bert.encoder.layer.7.attention.self.query | 14 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
46
+ | 43 | nncf_module.bert.encoder.layer.7.attention.self.key | 14 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
47
+ | 44 | nncf_module.bert.encoder.layer.7.attention.self.value | 14 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
48
+ | 45 | nncf_module.bert.encoder.layer.7.attention.output.dense | 14 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
49
+ | 46 | nncf_module.bert.encoder.layer.7.intermediate.dense | 15 | (3072, 768) | (2569, 768) | (3072,) | (2569,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
50
+ | 47 | nncf_module.bert.encoder.layer.7.output.dense | 15 | (768, 3072) | (768, 2569) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
51
+ | 48 | nncf_module.bert.encoder.layer.8.attention.self.key | 16 | (768, 768) | (256, 768) | (768,) | (256,) | [1, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
52
+ | 49 | nncf_module.bert.encoder.layer.8.attention.self.value | 16 | (768, 768) | (256, 768) | (768,) | (256,) | [1, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
53
+ | 50 | nncf_module.bert.encoder.layer.8.attention.self.query | 16 | (768, 768) | (256, 768) | (768,) | (256,) | [1, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
54
+ | 51 | nncf_module.bert.encoder.layer.8.attention.output.dense | 16 | (768, 768) | (768, 256) | (768,) | (768,) | [1, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
55
+ | 52 | nncf_module.bert.encoder.layer.8.output.dense | 17 | (768, 3072) | (768, 2094) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
56
+ | 53 | nncf_module.bert.encoder.layer.8.intermediate.dense | 17 | (3072, 768) | (2094, 768) | (3072,) | (2094,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
57
+ | 54 | nncf_module.bert.encoder.layer.9.attention.self.query | 18 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
58
+ | 55 | nncf_module.bert.encoder.layer.9.attention.output.dense | 18 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
59
+ | 56 | nncf_module.bert.encoder.layer.9.attention.self.value | 18 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
60
+ | 57 | nncf_module.bert.encoder.layer.9.attention.self.key | 18 | (768, 768) | (768, 768) | (768,) | (768,) | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
61
+ | 58 | nncf_module.bert.encoder.layer.9.intermediate.dense | 19 | (3072, 768) | (1009, 768) | (3072,) | (1009,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
62
+ | 59 | nncf_module.bert.encoder.layer.9.output.dense | 19 | (768, 3072) | (768, 1009) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
63
+ | 60 | nncf_module.bert.encoder.layer.10.attention.self.key | 20 | (768, 768) | (320, 768) | (768,) | (320,) | [0, 3, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
64
+ | 61 | nncf_module.bert.encoder.layer.10.attention.self.value | 20 | (768, 768) | (320, 768) | (768,) | (320,) | [0, 3, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
65
+ | 62 | nncf_module.bert.encoder.layer.10.attention.self.query | 20 | (768, 768) | (320, 768) | (768,) | (320,) | [0, 3, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
66
+ | 63 | nncf_module.bert.encoder.layer.10.attention.output.dense | 20 | (768, 768) | (768, 320) | (768,) | (768,) | [0, 3, 9, 10, 11] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
67
+ | 64 | nncf_module.bert.encoder.layer.10.output.dense | 21 | (768, 3072) | (768, 743) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
68
+ | 65 | nncf_module.bert.encoder.layer.10.intermediate.dense | 21 | (3072, 768) | (743, 768) | (3072,) | (743,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
69
+ | 66 | nncf_module.bert.encoder.layer.11.attention.output.dense | 22 | (768, 768) | (768, 192) | (768,) | (768,) | [1, 2, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
70
+ | 67 | nncf_module.bert.encoder.layer.11.attention.self.key | 22 | (768, 768) | (192, 768) | (768,) | (192,) | [1, 2, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
71
+ | 68 | nncf_module.bert.encoder.layer.11.attention.self.value | 22 | (768, 768) | (192, 768) | (768,) | (192,) | [1, 2, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
72
+ | 69 | nncf_module.bert.encoder.layer.11.attention.self.query | 22 | (768, 768) | (192, 768) | (768,) | (192,) | [1, 2, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
73
+ | 70 | nncf_module.bert.encoder.layer.11.intermediate.dense | 23 | (3072, 768) | (605, 768) | (3072,) | (605,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
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+ | 71 | nncf_module.bert.encoder.layer.11.output.dense | 23 | (768, 3072) | (768, 605) | (768,) | (768,) | skip reporting | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
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