Hugging Face's logo

vuiseng9
/
bert-l-r0.020-30pc-sparse

ONNX
Model card Files
xet
 Community
vchua commited on
Commit
3e557bf
·
1 Parent(s): 32669db

Add content

Browse files
Files changed (13) hide show
  1. all_results.json +5 -0
  2. compressed_graph.dot +0 -0
  3. eval_predictions.json +0 -0
  4. eval_results.json +5 -0
  5. ir/sparsity_structures.csv +145 -0
  6. ir/sparsity_structures.md +146 -0
  7. ir/sparsity_structures.pkl +3 -0
  8. ir/squad-BertForQuestionAnswering.cropped.fp32.bin +3 -0
  9. ir/squad-BertForQuestionAnswering.cropped.fp32.mapping +3299 -0
  10. ir/squad-BertForQuestionAnswering.cropped.fp32.onnx +3 -0
  11. ir/squad-BertForQuestionAnswering.cropped.fp32.xml +0 -0
  12. nncf-mvmt-p3.json +68 -0
  13. original_graph.dot +0 -0
all_results.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "eval_exact_match": 87.47398297067171,
3
+ "eval_f1": 93.30917016807663,
4
+ "eval_samples": 10784
5
+ }
compressed_graph.dot ADDED
The diff for this file is too large to render. See raw diff
 
eval_predictions.json ADDED
The diff for this file is too large to render. See raw diff
 
eval_results.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "eval_exact_match": 87.47398297067171,
3
+ "eval_f1": 93.30917016807663,
4
+ "eval_samples": 10784
5
+ }
ir/sparsity_structures.csv ADDED
@@ -0,0 +1,145 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ pt_module_name,block_id,orig_w_shape,final_w_shape,orig_b_shape,final_b_shape,prune_by,id_to_keep,head_id_to_keep,nncf_graph_node
2
+ nncf_module.bert.encoder.layer.0.attention.self.value,0,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[2, 4, 6, 10, 12, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
3
+ nncf_module.bert.encoder.layer.0.attention.self.query,0,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[2, 4, 6, 10, 12, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
4
+ nncf_module.bert.encoder.layer.0.attention.self.key,0,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[2, 4, 6, 10, 12, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
5
+ nncf_module.bert.encoder.layer.0.attention.output.dense,0,"(1024, 1024)","(1024, 384)","(1024,)","(1024,)",group of 64 cols,See pkl,"[2, 4, 6, 10, 12, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
6
+ nncf_module.bert.encoder.layer.0.intermediate.dense,1,"(4096, 1024)","(3910, 1024)","(4096,)","(3910,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
7
+ nncf_module.bert.encoder.layer.0.output.dense,1,"(1024, 4096)","(1024, 3910)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0
8
+ nncf_module.bert.encoder.layer.1.attention.self.query,2,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[6, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
9
+ nncf_module.bert.encoder.layer.1.attention.self.key,2,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[6, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
10
+ nncf_module.bert.encoder.layer.1.attention.output.dense,2,"(1024, 1024)","(1024, 128)","(1024,)","(1024,)",group of 64 cols,See pkl,"[6, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
11
+ nncf_module.bert.encoder.layer.1.attention.self.value,2,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[6, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
12
+ nncf_module.bert.encoder.layer.1.output.dense,3,"(1024, 4096)","(1024, 3894)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0
13
+ nncf_module.bert.encoder.layer.1.intermediate.dense,3,"(4096, 1024)","(3894, 1024)","(4096,)","(3894,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
14
+ nncf_module.bert.encoder.layer.2.attention.self.query,4,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[2, 3, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
15
+ nncf_module.bert.encoder.layer.2.attention.self.value,4,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[2, 3, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
16
+ nncf_module.bert.encoder.layer.2.attention.output.dense,4,"(1024, 1024)","(1024, 192)","(1024,)","(1024,)",group of 64 cols,See pkl,"[2, 3, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
17
+ nncf_module.bert.encoder.layer.2.attention.self.key,4,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[2, 3, 8]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
18
+ nncf_module.bert.encoder.layer.2.intermediate.dense,5,"(4096, 1024)","(3954, 1024)","(4096,)","(3954,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
19
+ nncf_module.bert.encoder.layer.2.output.dense,5,"(1024, 4096)","(1024, 3954)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0
20
+ nncf_module.bert.encoder.layer.3.attention.output.dense,6,"(1024, 1024)","(1024, 128)","(1024,)","(1024,)",group of 64 cols,See pkl,"[4, 12]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
21
+ nncf_module.bert.encoder.layer.3.attention.self.key,6,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[4, 12]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
22
+ nncf_module.bert.encoder.layer.3.attention.self.query,6,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[4, 12]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
23
+ nncf_module.bert.encoder.layer.3.attention.self.value,6,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[4, 12]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
24
+ nncf_module.bert.encoder.layer.3.intermediate.dense,7,"(4096, 1024)","(4001, 1024)","(4096,)","(4001,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
25
+ nncf_module.bert.encoder.layer.3.output.dense,7,"(1024, 4096)","(1024, 4001)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertOutput[output]/NNCFLinear[dense]/linear_0
26
+ nncf_module.bert.encoder.layer.4.attention.self.value,8,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[13, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
27
+ nncf_module.bert.encoder.layer.4.attention.self.key,8,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[13, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
28
+ nncf_module.bert.encoder.layer.4.attention.self.query,8,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[13, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
29
+ nncf_module.bert.encoder.layer.4.attention.output.dense,8,"(1024, 1024)","(1024, 128)","(1024,)","(1024,)",group of 64 cols,See pkl,"[13, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
30
+ nncf_module.bert.encoder.layer.4.intermediate.dense,9,"(4096, 1024)","(3981, 1024)","(4096,)","(3981,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
31
+ nncf_module.bert.encoder.layer.4.output.dense,9,"(1024, 4096)","(1024, 3981)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0
32
+ nncf_module.bert.encoder.layer.5.attention.output.dense,10,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
33
+ nncf_module.bert.encoder.layer.5.attention.self.key,10,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
34
+ nncf_module.bert.encoder.layer.5.attention.self.value,10,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
35
+ nncf_module.bert.encoder.layer.5.attention.self.query,10,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
36
+ nncf_module.bert.encoder.layer.5.output.dense,11,"(1024, 4096)","(1024, 4046)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0
37
+ nncf_module.bert.encoder.layer.5.intermediate.dense,11,"(4096, 1024)","(4046, 1024)","(4096,)","(4046,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
38
+ nncf_module.bert.encoder.layer.6.attention.self.value,12,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
39
+ nncf_module.bert.encoder.layer.6.attention.self.key,12,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
40
+ nncf_module.bert.encoder.layer.6.attention.self.query,12,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
41
+ nncf_module.bert.encoder.layer.6.attention.output.dense,12,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
42
+ nncf_module.bert.encoder.layer.6.intermediate.dense,13,"(4096, 1024)","(4052, 1024)","(4096,)","(4052,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
43
+ nncf_module.bert.encoder.layer.6.output.dense,13,"(1024, 4096)","(1024, 4052)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0
44
+ nncf_module.bert.encoder.layer.7.attention.self.value,14,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[1, 6, 7, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
45
+ nncf_module.bert.encoder.layer.7.attention.output.dense,14,"(1024, 1024)","(1024, 256)","(1024,)","(1024,)",group of 64 cols,See pkl,"[1, 6, 7, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
46
+ nncf_module.bert.encoder.layer.7.attention.self.query,14,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[1, 6, 7, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
47
+ nncf_module.bert.encoder.layer.7.attention.self.key,14,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[1, 6, 7, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
48
+ nncf_module.bert.encoder.layer.7.intermediate.dense,15,"(4096, 1024)","(4056, 1024)","(4096,)","(4056,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
49
+ nncf_module.bert.encoder.layer.7.output.dense,15,"(1024, 4096)","(1024, 4056)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertOutput[output]/NNCFLinear[dense]/linear_0
50
+ nncf_module.bert.encoder.layer.8.attention.self.query,16,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[1, 2, 6, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
51
+ nncf_module.bert.encoder.layer.8.attention.self.key,16,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[1, 2, 6, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
52
+ nncf_module.bert.encoder.layer.8.attention.output.dense,16,"(1024, 1024)","(1024, 256)","(1024,)","(1024,)",group of 64 cols,See pkl,"[1, 2, 6, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
53
+ nncf_module.bert.encoder.layer.8.attention.self.value,16,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[1, 2, 6, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
54
+ nncf_module.bert.encoder.layer.8.intermediate.dense,17,"(4096, 1024)","(4048, 1024)","(4096,)","(4048,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
55
+ nncf_module.bert.encoder.layer.8.output.dense,17,"(1024, 4096)","(1024, 4048)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0
56
+ nncf_module.bert.encoder.layer.9.attention.self.value,18,"(1024, 1024)","(64, 1024)","(1024,)","(64,)",group of 64 rows,See pkl,[12],BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
57
+ nncf_module.bert.encoder.layer.9.attention.self.key,18,"(1024, 1024)","(64, 1024)","(1024,)","(64,)",group of 64 rows,See pkl,[12],BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
58
+ nncf_module.bert.encoder.layer.9.attention.self.query,18,"(1024, 1024)","(64, 1024)","(1024,)","(64,)",group of 64 rows,See pkl,[12],BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
59
+ nncf_module.bert.encoder.layer.9.attention.output.dense,18,"(1024, 1024)","(1024, 64)","(1024,)","(1024,)",group of 64 cols,See pkl,[12],BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
60
+ nncf_module.bert.encoder.layer.9.intermediate.dense,19,"(4096, 1024)","(4049, 1024)","(4096,)","(4049,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
61
+ nncf_module.bert.encoder.layer.9.output.dense,19,"(1024, 4096)","(1024, 4049)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertOutput[output]/NNCFLinear[dense]/linear_0
62
+ nncf_module.bert.encoder.layer.10.attention.self.key,20,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[0, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
63
+ nncf_module.bert.encoder.layer.10.attention.output.dense,20,"(1024, 1024)","(1024, 128)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
64
+ nncf_module.bert.encoder.layer.10.attention.self.value,20,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[0, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
65
+ nncf_module.bert.encoder.layer.10.attention.self.query,20,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[0, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
66
+ nncf_module.bert.encoder.layer.10.intermediate.dense,21,"(4096, 1024)","(4017, 1024)","(4096,)","(4017,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
67
+ nncf_module.bert.encoder.layer.10.output.dense,21,"(1024, 4096)","(1024, 4017)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0
68
+ nncf_module.bert.encoder.layer.11.attention.self.key,22,"(1024, 1024)","(320, 1024)","(1024,)","(320,)",group of 64 rows,See pkl,"[1, 4, 9, 11, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
69
+ nncf_module.bert.encoder.layer.11.attention.self.value,22,"(1024, 1024)","(320, 1024)","(1024,)","(320,)",group of 64 rows,See pkl,"[1, 4, 9, 11, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
70
+ nncf_module.bert.encoder.layer.11.attention.self.query,22,"(1024, 1024)","(320, 1024)","(1024,)","(320,)",group of 64 rows,See pkl,"[1, 4, 9, 11, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
71
+ nncf_module.bert.encoder.layer.11.attention.output.dense,22,"(1024, 1024)","(1024, 320)","(1024,)","(1024,)",group of 64 cols,See pkl,"[1, 4, 9, 11, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
72
+ nncf_module.bert.encoder.layer.11.intermediate.dense,23,"(4096, 1024)","(4023, 1024)","(4096,)","(4023,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
73
+ nncf_module.bert.encoder.layer.11.output.dense,23,"(1024, 4096)","(1024, 4023)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0
74
+ nncf_module.bert.encoder.layer.12.attention.self.query,24,"(1024, 1024)","(320, 1024)","(1024,)","(320,)",group of 64 rows,See pkl,"[4, 5, 7, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
75
+ nncf_module.bert.encoder.layer.12.attention.self.key,24,"(1024, 1024)","(320, 1024)","(1024,)","(320,)",group of 64 rows,See pkl,"[4, 5, 7, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
76
+ nncf_module.bert.encoder.layer.12.attention.self.value,24,"(1024, 1024)","(320, 1024)","(1024,)","(320,)",group of 64 rows,See pkl,"[4, 5, 7, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
77
+ nncf_module.bert.encoder.layer.12.attention.output.dense,24,"(1024, 1024)","(1024, 320)","(1024,)","(1024,)",group of 64 cols,See pkl,"[4, 5, 7, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
78
+ nncf_module.bert.encoder.layer.12.output.dense,25,"(1024, 4096)","(1024, 4002)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertOutput[output]/NNCFLinear[dense]/linear_0
79
+ nncf_module.bert.encoder.layer.12.intermediate.dense,25,"(4096, 1024)","(4002, 1024)","(4096,)","(4002,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
80
+ nncf_module.bert.encoder.layer.13.attention.self.query,26,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[4, 7, 9, 11, 13, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
81
+ nncf_module.bert.encoder.layer.13.attention.self.key,26,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[4, 7, 9, 11, 13, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
82
+ nncf_module.bert.encoder.layer.13.attention.self.value,26,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[4, 7, 9, 11, 13, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
83
+ nncf_module.bert.encoder.layer.13.attention.output.dense,26,"(1024, 1024)","(1024, 384)","(1024,)","(1024,)",group of 64 cols,See pkl,"[4, 7, 9, 11, 13, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
84
+ nncf_module.bert.encoder.layer.13.output.dense,27,"(1024, 4096)","(1024, 3982)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertOutput[output]/NNCFLinear[dense]/linear_0
85
+ nncf_module.bert.encoder.layer.13.intermediate.dense,27,"(4096, 1024)","(3982, 1024)","(4096,)","(3982,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
86
+ nncf_module.bert.encoder.layer.14.attention.output.dense,28,"(1024, 1024)","(1024, 384)","(1024,)","(1024,)",group of 64 cols,See pkl,"[2, 3, 4, 7, 8, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
87
+ nncf_module.bert.encoder.layer.14.attention.self.value,28,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[2, 3, 4, 7, 8, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
88
+ nncf_module.bert.encoder.layer.14.attention.self.key,28,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[2, 3, 4, 7, 8, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
89
+ nncf_module.bert.encoder.layer.14.attention.self.query,28,"(1024, 1024)","(384, 1024)","(1024,)","(384,)",group of 64 rows,See pkl,"[2, 3, 4, 7, 8, 9]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
90
+ nncf_module.bert.encoder.layer.14.output.dense,29,"(1024, 4096)","(1024, 3882)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertOutput[output]/NNCFLinear[dense]/linear_0
91
+ nncf_module.bert.encoder.layer.14.intermediate.dense,29,"(4096, 1024)","(3882, 1024)","(4096,)","(3882,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
92
+ nncf_module.bert.encoder.layer.15.attention.self.query,30,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
93
+ nncf_module.bert.encoder.layer.15.attention.self.key,30,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
94
+ nncf_module.bert.encoder.layer.15.attention.self.value,30,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
95
+ nncf_module.bert.encoder.layer.15.attention.output.dense,30,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
96
+ nncf_module.bert.encoder.layer.15.intermediate.dense,31,"(4096, 1024)","(3729, 1024)","(4096,)","(3729,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
97
+ nncf_module.bert.encoder.layer.15.output.dense,31,"(1024, 4096)","(1024, 3729)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertOutput[output]/NNCFLinear[dense]/linear_0
98
+ nncf_module.bert.encoder.layer.16.attention.output.dense,32,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
99
+ nncf_module.bert.encoder.layer.16.attention.self.query,32,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
100
+ nncf_module.bert.encoder.layer.16.attention.self.value,32,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
101
+ nncf_module.bert.encoder.layer.16.attention.self.key,32,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
102
+ nncf_module.bert.encoder.layer.16.intermediate.dense,33,"(4096, 1024)","(3652, 1024)","(4096,)","(3652,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
103
+ nncf_module.bert.encoder.layer.16.output.dense,33,"(1024, 4096)","(1024, 3652)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertOutput[output]/NNCFLinear[dense]/linear_0
104
+ nncf_module.bert.encoder.layer.17.attention.self.value,34,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
105
+ nncf_module.bert.encoder.layer.17.attention.output.dense,34,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
106
+ nncf_module.bert.encoder.layer.17.attention.self.key,34,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
107
+ nncf_module.bert.encoder.layer.17.attention.self.query,34,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
108
+ nncf_module.bert.encoder.layer.17.intermediate.dense,35,"(4096, 1024)","(3553, 1024)","(4096,)","(3553,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
109
+ nncf_module.bert.encoder.layer.17.output.dense,35,"(1024, 4096)","(1024, 3553)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertOutput[output]/NNCFLinear[dense]/linear_0
110
+ nncf_module.bert.encoder.layer.18.attention.self.query,36,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
111
+ nncf_module.bert.encoder.layer.18.attention.output.dense,36,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
112
+ nncf_module.bert.encoder.layer.18.attention.self.value,36,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
113
+ nncf_module.bert.encoder.layer.18.attention.self.key,36,"(1024, 1024)","(1024, 1024)","(1024,)","(1024,)",group of 64 rows,See pkl,"[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
114
+ nncf_module.bert.encoder.layer.18.output.dense,37,"(1024, 4096)","(1024, 3426)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertOutput[output]/NNCFLinear[dense]/linear_0
115
+ nncf_module.bert.encoder.layer.18.intermediate.dense,37,"(4096, 1024)","(3426, 1024)","(4096,)","(3426,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
116
+ nncf_module.bert.encoder.layer.19.attention.self.value,38,"(1024, 1024)","(448, 1024)","(1024,)","(448,)",group of 64 rows,See pkl,"[2, 4, 7, 8, 9, 10, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
117
+ nncf_module.bert.encoder.layer.19.attention.self.key,38,"(1024, 1024)","(448, 1024)","(1024,)","(448,)",group of 64 rows,See pkl,"[2, 4, 7, 8, 9, 10, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
118
+ nncf_module.bert.encoder.layer.19.attention.self.query,38,"(1024, 1024)","(448, 1024)","(1024,)","(448,)",group of 64 rows,See pkl,"[2, 4, 7, 8, 9, 10, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
119
+ nncf_module.bert.encoder.layer.19.attention.output.dense,38,"(1024, 1024)","(1024, 448)","(1024,)","(1024,)",group of 64 cols,See pkl,"[2, 4, 7, 8, 9, 10, 13]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
120
+ nncf_module.bert.encoder.layer.19.intermediate.dense,39,"(4096, 1024)","(2872, 1024)","(4096,)","(2872,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
121
+ nncf_module.bert.encoder.layer.19.output.dense,39,"(1024, 4096)","(1024, 2872)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertOutput[output]/NNCFLinear[dense]/linear_0
122
+ nncf_module.bert.encoder.layer.20.attention.output.dense,40,"(1024, 1024)","(1024, 256)","(1024,)","(1024,)",group of 64 cols,See pkl,"[5, 6, 9, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
123
+ nncf_module.bert.encoder.layer.20.attention.self.value,40,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[5, 6, 9, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
124
+ nncf_module.bert.encoder.layer.20.attention.self.query,40,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[5, 6, 9, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
125
+ nncf_module.bert.encoder.layer.20.attention.self.key,40,"(1024, 1024)","(256, 1024)","(1024,)","(256,)",group of 64 rows,See pkl,"[5, 6, 9, 15]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
126
+ nncf_module.bert.encoder.layer.20.intermediate.dense,41,"(4096, 1024)","(1521, 1024)","(4096,)","(1521,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
127
+ nncf_module.bert.encoder.layer.20.output.dense,41,"(1024, 4096)","(1024, 1521)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertOutput[output]/NNCFLinear[dense]/linear_0
128
+ nncf_module.bert.encoder.layer.21.attention.self.query,42,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[6, 7, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
129
+ nncf_module.bert.encoder.layer.21.attention.self.value,42,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[6, 7, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
130
+ nncf_module.bert.encoder.layer.21.attention.output.dense,42,"(1024, 1024)","(1024, 192)","(1024,)","(1024,)",group of 64 cols,See pkl,"[6, 7, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
131
+ nncf_module.bert.encoder.layer.21.attention.self.key,42,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[6, 7, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
132
+ nncf_module.bert.encoder.layer.21.output.dense,43,"(1024, 4096)","(1024, 574)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertOutput[output]/NNCFLinear[dense]/linear_0
133
+ nncf_module.bert.encoder.layer.21.intermediate.dense,43,"(4096, 1024)","(574, 1024)","(4096,)","(574,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
134
+ nncf_module.bert.encoder.layer.22.attention.self.query,44,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[12, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
135
+ nncf_module.bert.encoder.layer.22.attention.output.dense,44,"(1024, 1024)","(1024, 128)","(1024,)","(1024,)",group of 64 cols,See pkl,"[12, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
136
+ nncf_module.bert.encoder.layer.22.attention.self.value,44,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[12, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
137
+ nncf_module.bert.encoder.layer.22.attention.self.key,44,"(1024, 1024)","(128, 1024)","(1024,)","(128,)",group of 64 rows,See pkl,"[12, 14]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
138
+ nncf_module.bert.encoder.layer.22.intermediate.dense,45,"(4096, 1024)","(316, 1024)","(4096,)","(316,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
139
+ nncf_module.bert.encoder.layer.22.output.dense,45,"(1024, 4096)","(1024, 316)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertOutput[output]/NNCFLinear[dense]/linear_0
140
+ nncf_module.bert.encoder.layer.23.attention.self.key,46,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[0, 3, 7]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0
141
+ nncf_module.bert.encoder.layer.23.attention.output.dense,46,"(1024, 1024)","(1024, 192)","(1024,)","(1024,)",group of 64 cols,See pkl,"[0, 3, 7]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0
142
+ nncf_module.bert.encoder.layer.23.attention.self.value,46,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[0, 3, 7]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0
143
+ nncf_module.bert.encoder.layer.23.attention.self.query,46,"(1024, 1024)","(192, 1024)","(1024,)","(192,)",group of 64 rows,See pkl,"[0, 3, 7]",BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0
144
+ nncf_module.bert.encoder.layer.23.output.dense,47,"(1024, 4096)","(1024, 603)","(1024,)","(1024,)",col,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertOutput[output]/NNCFLinear[dense]/linear_0
145
+ nncf_module.bert.encoder.layer.23.intermediate.dense,47,"(4096, 1024)","(603, 1024)","(4096,)","(603,)",row,See pkl,,BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0
ir/sparsity_structures.md ADDED
@@ -0,0 +1,146 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ | | pt_module_name | block_id | orig_w_shape | final_w_shape | orig_b_shape | final_b_shape | prune_by | id_to_keep | head_id_to_keep | nncf_graph_node |
2
+ |----:|:---------------------------------------------------------|-----------:|:---------------|:----------------|:---------------|:----------------|:-----------------|:-------------|:-------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
3
+ | 0 | nncf_module.bert.encoder.layer.0.attention.self.value | 0 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [2, 4, 6, 10, 12, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
4
+ | 1 | nncf_module.bert.encoder.layer.0.attention.self.query | 0 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [2, 4, 6, 10, 12, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
5
+ | 2 | nncf_module.bert.encoder.layer.0.attention.self.key | 0 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [2, 4, 6, 10, 12, 13] | 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.output.dense | 0 | (1024, 1024) | (1024, 384) | (1024,) | (1024,) | group of 64 cols | See pkl | [2, 4, 6, 10, 12, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
7
+ | 4 | nncf_module.bert.encoder.layer.0.intermediate.dense | 1 | (4096, 1024) | (3910, 1024) | (4096,) | (3910,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
8
+ | 5 | nncf_module.bert.encoder.layer.0.output.dense | 1 | (1024, 4096) | (1024, 3910) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[0]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
9
+ | 6 | nncf_module.bert.encoder.layer.1.attention.self.query | 2 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [6, 8] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
10
+ | 7 | nncf_module.bert.encoder.layer.1.attention.self.key | 2 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [6, 8] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
11
+ | 8 | nncf_module.bert.encoder.layer.1.attention.output.dense | 2 | (1024, 1024) | (1024, 128) | (1024,) | (1024,) | group of 64 cols | See pkl | [6, 8] | 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 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [6, 8] | 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.output.dense | 3 | (1024, 4096) | (1024, 3894) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
14
+ | 11 | nncf_module.bert.encoder.layer.1.intermediate.dense | 3 | (4096, 1024) | (3894, 1024) | (4096,) | (3894,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[1]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
15
+ | 12 | nncf_module.bert.encoder.layer.2.attention.self.query | 4 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [2, 3, 8] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
16
+ | 13 | nncf_module.bert.encoder.layer.2.attention.self.value | 4 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [2, 3, 8] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
17
+ | 14 | nncf_module.bert.encoder.layer.2.attention.output.dense | 4 | (1024, 1024) | (1024, 192) | (1024,) | (1024,) | group of 64 cols | See pkl | [2, 3, 8] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
18
+ | 15 | nncf_module.bert.encoder.layer.2.attention.self.key | 4 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [2, 3, 8] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
19
+ | 16 | nncf_module.bert.encoder.layer.2.intermediate.dense | 5 | (4096, 1024) | (3954, 1024) | (4096,) | (3954,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
20
+ | 17 | nncf_module.bert.encoder.layer.2.output.dense | 5 | (1024, 4096) | (1024, 3954) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[2]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
21
+ | 18 | nncf_module.bert.encoder.layer.3.attention.output.dense | 6 | (1024, 1024) | (1024, 128) | (1024,) | (1024,) | group of 64 cols | See pkl | [4, 12] | 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.key | 6 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [4, 12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
23
+ | 20 | nncf_module.bert.encoder.layer.3.attention.self.query | 6 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [4, 12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
24
+ | 21 | nncf_module.bert.encoder.layer.3.attention.self.value | 6 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [4, 12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[3]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
25
+ | 22 | nncf_module.bert.encoder.layer.3.intermediate.dense | 7 | (4096, 1024) | (4001, 1024) | (4096,) | (4001,) | row | See pkl | | 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 | (1024, 4096) | (1024, 4001) | (1024,) | (1024,) | col | See pkl | | 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.value | 8 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [13, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
28
+ | 25 | nncf_module.bert.encoder.layer.4.attention.self.key | 8 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [13, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
29
+ | 26 | nncf_module.bert.encoder.layer.4.attention.self.query | 8 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [13, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
30
+ | 27 | nncf_module.bert.encoder.layer.4.attention.output.dense | 8 | (1024, 1024) | (1024, 128) | (1024,) | (1024,) | group of 64 cols | See pkl | [13, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
31
+ | 28 | nncf_module.bert.encoder.layer.4.intermediate.dense | 9 | (4096, 1024) | (3981, 1024) | (4096,) | (3981,) | row | See pkl | | 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 | (1024, 4096) | (1024, 3981) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[4]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
33
+ | 30 | nncf_module.bert.encoder.layer.5.attention.output.dense | 10 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
34
+ | 31 | nncf_module.bert.encoder.layer.5.attention.self.key | 10 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
35
+ | 32 | nncf_module.bert.encoder.layer.5.attention.self.value | 10 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
36
+ | 33 | nncf_module.bert.encoder.layer.5.attention.self.query | 10 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
37
+ | 34 | nncf_module.bert.encoder.layer.5.output.dense | 11 | (1024, 4096) | (1024, 4046) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
38
+ | 35 | nncf_module.bert.encoder.layer.5.intermediate.dense | 11 | (4096, 1024) | (4046, 1024) | (4096,) | (4046,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[5]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
39
+ | 36 | nncf_module.bert.encoder.layer.6.attention.self.value | 12 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | 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.key | 12 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
41
+ | 38 | nncf_module.bert.encoder.layer.6.attention.self.query | 12 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
42
+ | 39 | nncf_module.bert.encoder.layer.6.attention.output.dense | 12 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | 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.intermediate.dense | 13 | (4096, 1024) | (4052, 1024) | (4096,) | (4052,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
44
+ | 41 | nncf_module.bert.encoder.layer.6.output.dense | 13 | (1024, 4096) | (1024, 4052) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[6]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
45
+ | 42 | nncf_module.bert.encoder.layer.7.attention.self.value | 14 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [1, 6, 7, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
46
+ | 43 | nncf_module.bert.encoder.layer.7.attention.output.dense | 14 | (1024, 1024) | (1024, 256) | (1024,) | (1024,) | group of 64 cols | See pkl | [1, 6, 7, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
47
+ | 44 | nncf_module.bert.encoder.layer.7.attention.self.query | 14 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [1, 6, 7, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
48
+ | 45 | nncf_module.bert.encoder.layer.7.attention.self.key | 14 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [1, 6, 7, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[7]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
49
+ | 46 | nncf_module.bert.encoder.layer.7.intermediate.dense | 15 | (4096, 1024) | (4056, 1024) | (4096,) | (4056,) | row | See pkl | | 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 | (1024, 4096) | (1024, 4056) | (1024,) | (1024,) | col | See pkl | | 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.query | 16 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [1, 2, 6, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
52
+ | 49 | nncf_module.bert.encoder.layer.8.attention.self.key | 16 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [1, 2, 6, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
53
+ | 50 | nncf_module.bert.encoder.layer.8.attention.output.dense | 16 | (1024, 1024) | (1024, 256) | (1024,) | (1024,) | group of 64 cols | See pkl | [1, 2, 6, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
54
+ | 51 | nncf_module.bert.encoder.layer.8.attention.self.value | 16 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [1, 2, 6, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
55
+ | 52 | nncf_module.bert.encoder.layer.8.intermediate.dense | 17 | (4096, 1024) | (4048, 1024) | (4096,) | (4048,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
56
+ | 53 | nncf_module.bert.encoder.layer.8.output.dense | 17 | (1024, 4096) | (1024, 4048) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[8]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
57
+ | 54 | nncf_module.bert.encoder.layer.9.attention.self.value | 18 | (1024, 1024) | (64, 1024) | (1024,) | (64,) | group of 64 rows | See pkl | [12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
58
+ | 55 | nncf_module.bert.encoder.layer.9.attention.self.key | 18 | (1024, 1024) | (64, 1024) | (1024,) | (64,) | group of 64 rows | See pkl | [12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
59
+ | 56 | nncf_module.bert.encoder.layer.9.attention.self.query | 18 | (1024, 1024) | (64, 1024) | (1024,) | (64,) | group of 64 rows | See pkl | [12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
60
+ | 57 | nncf_module.bert.encoder.layer.9.attention.output.dense | 18 | (1024, 1024) | (1024, 64) | (1024,) | (1024,) | group of 64 cols | See pkl | [12] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[9]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
61
+ | 58 | nncf_module.bert.encoder.layer.9.intermediate.dense | 19 | (4096, 1024) | (4049, 1024) | (4096,) | (4049,) | row | See pkl | | 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 | (1024, 4096) | (1024, 4049) | (1024,) | (1024,) | col | See pkl | | 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 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [0, 15] | 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.output.dense | 20 | (1024, 1024) | (1024, 128) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
65
+ | 62 | nncf_module.bert.encoder.layer.10.attention.self.value | 20 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [0, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
66
+ | 63 | nncf_module.bert.encoder.layer.10.attention.self.query | 20 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [0, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
67
+ | 64 | nncf_module.bert.encoder.layer.10.intermediate.dense | 21 | (4096, 1024) | (4017, 1024) | (4096,) | (4017,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
68
+ | 65 | nncf_module.bert.encoder.layer.10.output.dense | 21 | (1024, 4096) | (1024, 4017) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[10]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
69
+ | 66 | nncf_module.bert.encoder.layer.11.attention.self.key | 22 | (1024, 1024) | (320, 1024) | (1024,) | (320,) | group of 64 rows | See pkl | [1, 4, 9, 11, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
70
+ | 67 | nncf_module.bert.encoder.layer.11.attention.self.value | 22 | (1024, 1024) | (320, 1024) | (1024,) | (320,) | group of 64 rows | See pkl | [1, 4, 9, 11, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
71
+ | 68 | nncf_module.bert.encoder.layer.11.attention.self.query | 22 | (1024, 1024) | (320, 1024) | (1024,) | (320,) | group of 64 rows | See pkl | [1, 4, 9, 11, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
72
+ | 69 | nncf_module.bert.encoder.layer.11.attention.output.dense | 22 | (1024, 1024) | (1024, 320) | (1024,) | (1024,) | group of 64 cols | See pkl | [1, 4, 9, 11, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
73
+ | 70 | nncf_module.bert.encoder.layer.11.intermediate.dense | 23 | (4096, 1024) | (4023, 1024) | (4096,) | (4023,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
74
+ | 71 | nncf_module.bert.encoder.layer.11.output.dense | 23 | (1024, 4096) | (1024, 4023) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
75
+ | 72 | nncf_module.bert.encoder.layer.12.attention.self.query | 24 | (1024, 1024) | (320, 1024) | (1024,) | (320,) | group of 64 rows | See pkl | [4, 5, 7, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
76
+ | 73 | nncf_module.bert.encoder.layer.12.attention.self.key | 24 | (1024, 1024) | (320, 1024) | (1024,) | (320,) | group of 64 rows | See pkl | [4, 5, 7, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
77
+ | 74 | nncf_module.bert.encoder.layer.12.attention.self.value | 24 | (1024, 1024) | (320, 1024) | (1024,) | (320,) | group of 64 rows | See pkl | [4, 5, 7, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
78
+ | 75 | nncf_module.bert.encoder.layer.12.attention.output.dense | 24 | (1024, 1024) | (1024, 320) | (1024,) | (1024,) | group of 64 cols | See pkl | [4, 5, 7, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
79
+ | 76 | nncf_module.bert.encoder.layer.12.output.dense | 25 | (1024, 4096) | (1024, 4002) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
80
+ | 77 | nncf_module.bert.encoder.layer.12.intermediate.dense | 25 | (4096, 1024) | (4002, 1024) | (4096,) | (4002,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[12]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
81
+ | 78 | nncf_module.bert.encoder.layer.13.attention.self.query | 26 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [4, 7, 9, 11, 13, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
82
+ | 79 | nncf_module.bert.encoder.layer.13.attention.self.key | 26 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [4, 7, 9, 11, 13, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
83
+ | 80 | nncf_module.bert.encoder.layer.13.attention.self.value | 26 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [4, 7, 9, 11, 13, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
84
+ | 81 | nncf_module.bert.encoder.layer.13.attention.output.dense | 26 | (1024, 1024) | (1024, 384) | (1024,) | (1024,) | group of 64 cols | See pkl | [4, 7, 9, 11, 13, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
85
+ | 82 | nncf_module.bert.encoder.layer.13.output.dense | 27 | (1024, 4096) | (1024, 3982) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
86
+ | 83 | nncf_module.bert.encoder.layer.13.intermediate.dense | 27 | (4096, 1024) | (3982, 1024) | (4096,) | (3982,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[13]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
87
+ | 84 | nncf_module.bert.encoder.layer.14.attention.output.dense | 28 | (1024, 1024) | (1024, 384) | (1024,) | (1024,) | group of 64 cols | See pkl | [2, 3, 4, 7, 8, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
88
+ | 85 | nncf_module.bert.encoder.layer.14.attention.self.value | 28 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [2, 3, 4, 7, 8, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
89
+ | 86 | nncf_module.bert.encoder.layer.14.attention.self.key | 28 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [2, 3, 4, 7, 8, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
90
+ | 87 | nncf_module.bert.encoder.layer.14.attention.self.query | 28 | (1024, 1024) | (384, 1024) | (1024,) | (384,) | group of 64 rows | See pkl | [2, 3, 4, 7, 8, 9] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
91
+ | 88 | nncf_module.bert.encoder.layer.14.output.dense | 29 | (1024, 4096) | (1024, 3882) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
92
+ | 89 | nncf_module.bert.encoder.layer.14.intermediate.dense | 29 | (4096, 1024) | (3882, 1024) | (4096,) | (3882,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[14]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
93
+ | 90 | nncf_module.bert.encoder.layer.15.attention.self.query | 30 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
94
+ | 91 | nncf_module.bert.encoder.layer.15.attention.self.key | 30 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
95
+ | 92 | nncf_module.bert.encoder.layer.15.attention.self.value | 30 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
96
+ | 93 | nncf_module.bert.encoder.layer.15.attention.output.dense | 30 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
97
+ | 94 | nncf_module.bert.encoder.layer.15.intermediate.dense | 31 | (4096, 1024) | (3729, 1024) | (4096,) | (3729,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
98
+ | 95 | nncf_module.bert.encoder.layer.15.output.dense | 31 | (1024, 4096) | (1024, 3729) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[15]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
99
+ | 96 | nncf_module.bert.encoder.layer.16.attention.output.dense | 32 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
100
+ | 97 | nncf_module.bert.encoder.layer.16.attention.self.query | 32 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
101
+ | 98 | nncf_module.bert.encoder.layer.16.attention.self.value | 32 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
102
+ | 99 | nncf_module.bert.encoder.layer.16.attention.self.key | 32 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
103
+ | 100 | nncf_module.bert.encoder.layer.16.intermediate.dense | 33 | (4096, 1024) | (3652, 1024) | (4096,) | (3652,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
104
+ | 101 | nncf_module.bert.encoder.layer.16.output.dense | 33 | (1024, 4096) | (1024, 3652) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[16]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
105
+ | 102 | nncf_module.bert.encoder.layer.17.attention.self.value | 34 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
106
+ | 103 | nncf_module.bert.encoder.layer.17.attention.output.dense | 34 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
107
+ | 104 | nncf_module.bert.encoder.layer.17.attention.self.key | 34 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
108
+ | 105 | nncf_module.bert.encoder.layer.17.attention.self.query | 34 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
109
+ | 106 | nncf_module.bert.encoder.layer.17.intermediate.dense | 35 | (4096, 1024) | (3553, 1024) | (4096,) | (3553,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
110
+ | 107 | nncf_module.bert.encoder.layer.17.output.dense | 35 | (1024, 4096) | (1024, 3553) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[17]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
111
+ | 108 | nncf_module.bert.encoder.layer.18.attention.self.query | 36 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
112
+ | 109 | nncf_module.bert.encoder.layer.18.attention.output.dense | 36 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
113
+ | 110 | nncf_module.bert.encoder.layer.18.attention.self.value | 36 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
114
+ | 111 | nncf_module.bert.encoder.layer.18.attention.self.key | 36 | (1024, 1024) | (1024, 1024) | (1024,) | (1024,) | group of 64 rows | See pkl | [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
115
+ | 112 | nncf_module.bert.encoder.layer.18.output.dense | 37 | (1024, 4096) | (1024, 3426) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
116
+ | 113 | nncf_module.bert.encoder.layer.18.intermediate.dense | 37 | (4096, 1024) | (3426, 1024) | (4096,) | (3426,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[18]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
117
+ | 114 | nncf_module.bert.encoder.layer.19.attention.self.value | 38 | (1024, 1024) | (448, 1024) | (1024,) | (448,) | group of 64 rows | See pkl | [2, 4, 7, 8, 9, 10, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
118
+ | 115 | nncf_module.bert.encoder.layer.19.attention.self.key | 38 | (1024, 1024) | (448, 1024) | (1024,) | (448,) | group of 64 rows | See pkl | [2, 4, 7, 8, 9, 10, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
119
+ | 116 | nncf_module.bert.encoder.layer.19.attention.self.query | 38 | (1024, 1024) | (448, 1024) | (1024,) | (448,) | group of 64 rows | See pkl | [2, 4, 7, 8, 9, 10, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
120
+ | 117 | nncf_module.bert.encoder.layer.19.attention.output.dense | 38 | (1024, 1024) | (1024, 448) | (1024,) | (1024,) | group of 64 cols | See pkl | [2, 4, 7, 8, 9, 10, 13] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
121
+ | 118 | nncf_module.bert.encoder.layer.19.intermediate.dense | 39 | (4096, 1024) | (2872, 1024) | (4096,) | (2872,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
122
+ | 119 | nncf_module.bert.encoder.layer.19.output.dense | 39 | (1024, 4096) | (1024, 2872) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[19]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
123
+ | 120 | nncf_module.bert.encoder.layer.20.attention.output.dense | 40 | (1024, 1024) | (1024, 256) | (1024,) | (1024,) | group of 64 cols | See pkl | [5, 6, 9, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
124
+ | 121 | nncf_module.bert.encoder.layer.20.attention.self.value | 40 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [5, 6, 9, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
125
+ | 122 | nncf_module.bert.encoder.layer.20.attention.self.query | 40 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [5, 6, 9, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
126
+ | 123 | nncf_module.bert.encoder.layer.20.attention.self.key | 40 | (1024, 1024) | (256, 1024) | (1024,) | (256,) | group of 64 rows | See pkl | [5, 6, 9, 15] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
127
+ | 124 | nncf_module.bert.encoder.layer.20.intermediate.dense | 41 | (4096, 1024) | (1521, 1024) | (4096,) | (1521,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
128
+ | 125 | nncf_module.bert.encoder.layer.20.output.dense | 41 | (1024, 4096) | (1024, 1521) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[20]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
129
+ | 126 | nncf_module.bert.encoder.layer.21.attention.self.query | 42 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [6, 7, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
130
+ | 127 | nncf_module.bert.encoder.layer.21.attention.self.value | 42 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [6, 7, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
131
+ | 128 | nncf_module.bert.encoder.layer.21.attention.output.dense | 42 | (1024, 1024) | (1024, 192) | (1024,) | (1024,) | group of 64 cols | See pkl | [6, 7, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
132
+ | 129 | nncf_module.bert.encoder.layer.21.attention.self.key | 42 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [6, 7, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
133
+ | 130 | nncf_module.bert.encoder.layer.21.output.dense | 43 | (1024, 4096) | (1024, 574) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
134
+ | 131 | nncf_module.bert.encoder.layer.21.intermediate.dense | 43 | (4096, 1024) | (574, 1024) | (4096,) | (574,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[21]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
135
+ | 132 | nncf_module.bert.encoder.layer.22.attention.self.query | 44 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [12, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
136
+ | 133 | nncf_module.bert.encoder.layer.22.attention.output.dense | 44 | (1024, 1024) | (1024, 128) | (1024,) | (1024,) | group of 64 cols | See pkl | [12, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
137
+ | 134 | nncf_module.bert.encoder.layer.22.attention.self.value | 44 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [12, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
138
+ | 135 | nncf_module.bert.encoder.layer.22.attention.self.key | 44 | (1024, 1024) | (128, 1024) | (1024,) | (128,) | group of 64 rows | See pkl | [12, 14] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
139
+ | 136 | nncf_module.bert.encoder.layer.22.intermediate.dense | 45 | (4096, 1024) | (316, 1024) | (4096,) | (316,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
140
+ | 137 | nncf_module.bert.encoder.layer.22.output.dense | 45 | (1024, 4096) | (1024, 316) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[22]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
141
+ | 138 | nncf_module.bert.encoder.layer.23.attention.self.key | 46 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [0, 3, 7] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[key]/linear_0 |
142
+ | 139 | nncf_module.bert.encoder.layer.23.attention.output.dense | 46 | (1024, 1024) | (1024, 192) | (1024,) | (1024,) | group of 64 cols | See pkl | [0, 3, 7] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfOutput[output]/NNCFLinear[dense]/linear_0 |
143
+ | 140 | nncf_module.bert.encoder.layer.23.attention.self.value | 46 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [0, 3, 7] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[value]/linear_0 |
144
+ | 141 | nncf_module.bert.encoder.layer.23.attention.self.query | 46 | (1024, 1024) | (192, 1024) | (1024,) | (192,) | group of 64 rows | See pkl | [0, 3, 7] | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertAttention[attention]/BertSelfAttention[self]/NNCFLinear[query]/linear_0 |
145
+ | 142 | nncf_module.bert.encoder.layer.23.output.dense | 47 | (1024, 4096) | (1024, 603) | (1024,) | (1024,) | col | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertOutput[output]/NNCFLinear[dense]/linear_0 |
146
+ | 143 | nncf_module.bert.encoder.layer.23.intermediate.dense | 47 | (4096, 1024) | (603, 1024) | (4096,) | (603,) | row | See pkl | | BertForQuestionAnswering/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[23]/BertIntermediate[intermediate]/NNCFLinear[dense]/linear_0 |
ir/sparsity_structures.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3744f8b8d6828fe3f5fae7fb14c6e65d13edd0d0d84aac460aa01ff367b08bc6
3
+ size 634095
ir/squad-BertForQuestionAnswering.cropped.fp32.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e5a0d5ef4d58a54b06198ac84169de0a76d5706d3ec71ceaa5ca93ff55bf68c7
3
+ size 955629532
ir/squad-BertForQuestionAnswering.cropped.fp32.mapping ADDED
@@ -0,0 +1,3299 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <mapping>
3
+ <map>
4
+ <framework name="input.2" output_port_id="input.2" />
5
+ <IR name="input.2" output_port_id="0" />
6
+ </map>
7
+ <map>
8
+ <framework name="input.1" output_port_id="input.1" />
9
+ <IR name="input.1" output_port_id="0" />
10
+ </map>
11
+ <map>
12
+ <framework name="input.0" output_port_id="input.0" />
13
+ <IR name="input.0" output_port_id="0" />
14
+ </map>
15
+ <map>
16
+ <framework name="nncf_module.bert.embeddings.word_embeddings.weight" output_port_id="nncf_module.bert.embeddings.word_embeddings.weight" />
17
+ <IR name="nncf_module.bert.embeddings.word_embeddings.weight" output_port_id="0" />
18
+ </map>
19
+ <map>
20
+ <framework name="414" output_port_id="414" />
21
+ <IR name="414" output_port_id="3" />
22
+ </map>
23
+ <map>
24
+ <framework name="nncf_module.bert.embeddings.token_type_embeddings.weight" output_port_id="nncf_module.bert.embeddings.token_type_embeddings.weight" />
25
+ <IR name="nncf_module.bert.embeddings.token_type_embeddings.weight" output_port_id="0" />
26
+ </map>
27
+ <map>
28
+ <framework name="415" output_port_id="415" />
29
+ <IR name="415" output_port_id="3" />
30
+ </map>
31
+ <map>
32
+ <framework name="416" output_port_id="416" />
33
+ <IR name="416" output_port_id="2" />
34
+ </map>
35
+ <map>
36
+ <framework name="nncf_module.bert.embeddings.position_embeddings.weight" output_port_id="nncf_module.bert.embeddings.position_embeddings.weight" />
37
+ <IR name="nncf_module.bert.embeddings.position_embeddings.weight" output_port_id="0" />
38
+ </map>
39
+ <map>
40
+ <framework name="nncf_module.bert.embeddings.position_ids" output_port_id="nncf_module.bert.embeddings.position_ids" />
41
+ <IR name="nncf_module.bert.embeddings.position_ids" output_port_id="0" />
42
+ </map>
43
+ <map>
44
+ <framework name="402" output_port_id="402" />
45
+ <IR name="402" output_port_id="1" />
46
+ </map>
47
+ <map>
48
+ <framework name="403" output_port_id="403" />
49
+ <IR name="403" output_port_id="0" />
50
+ </map>
51
+ <map>
52
+ <framework name="404" output_port_id="406" />
53
+ <IR name="404" output_port_id="3" />
54
+ </map>
55
+ <map>
56
+ <framework name="404" output_port_id="404" />
57
+ <IR name="404" output_port_id="3" />
58
+ </map>
59
+ <map>
60
+ <framework name="410" output_port_id="410" />
61
+ <IR name="410" output_port_id="2" />
62
+ </map>
63
+ <map>
64
+ <framework name="413" output_port_id="413" />
65
+ <IR name="413" output_port_id="4" />
66
+ </map>
67
+ <map>
68
+ <framework name="417" output_port_id="417" />
69
+ <IR name="417" output_port_id="3" />
70
+ </map>
71
+ <map>
72
+ <framework name="418" output_port_id="418" />
73
+ <IR name="418" output_port_id="2" />
74
+ </map>
75
+ <map>
76
+ <framework name="427" output_port_id="427" />
77
+ <IR name="427" output_port_id="2" />
78
+ </map>
79
+ <map>
80
+ <framework name="428" output_port_id="428" />
81
+ <IR name="428" output_port_id="2" />
82
+ </map>
83
+ <map>
84
+ <framework name="429" output_port_id="429" />
85
+ <IR name="429" output_port_id="2" />
86
+ </map>
87
+ <map>
88
+ <framework name="431" output_port_id="431" />
89
+ <IR name="431" output_port_id="2" />
90
+ </map>
91
+ <map>
92
+ <framework name="432" output_port_id="432" />
93
+ <IR name="432" output_port_id="2" />
94
+ </map>
95
+ <map>
96
+ <framework name="481" output_port_id="481" />
97
+ <IR name="481" output_port_id="2" />
98
+ </map>
99
+ <map>
100
+ <framework name="482" output_port_id="482" />
101
+ <IR name="482" output_port_id="2" />
102
+ </map>
103
+ <map>
104
+ <framework name="434" output_port_id="434" />
105
+ <IR name="434" output_port_id="2" />
106
+ </map>
107
+ <map>
108
+ <framework name="435" output_port_id="435" />
109
+ <IR name="435" output_port_id="2" />
110
+ </map>
111
+ <map>
112
+ <framework name="449" output_port_id="449" />
113
+ <IR name="449" output_port_id="2" />
114
+ </map>
115
+ <map>
116
+ <framework name="483" output_port_id="483" />
117
+ <IR name="483" output_port_id="2" />
118
+ </map>
119
+ <map>
120
+ <framework name="486" output_port_id="486" />
121
+ <IR name="486" output_port_id="2" />
122
+ </map>
123
+ <map>
124
+ <framework name="395" output_port_id="395" />
125
+ <IR name="395" output_port_id="2" />
126
+ </map>
127
+ <map>
128
+ <framework name="396" output_port_id="396" />
129
+ <IR name="396" output_port_id="2" />
130
+ </map>
131
+ <map>
132
+ <framework name="397" output_port_id="397" />
133
+ <IR name="397" output_port_id="1" />
134
+ </map>
135
+ <map>
136
+ <framework name="399" output_port_id="399" />
137
+ <IR name="399" output_port_id="2" />
138
+ </map>
139
+ <map>
140
+ <framework name="401" output_port_id="401" />
141
+ <IR name="401" output_port_id="2" />
142
+ </map>
143
+ <map>
144
+ <framework name="487" output_port_id="487" />
145
+ <IR name="487" output_port_id="2" />
146
+ </map>
147
+ <map>
148
+ <framework name="488" output_port_id="488" />
149
+ <IR name="488" output_port_id="2" />
150
+ </map>
151
+ <map>
152
+ <framework name="451" output_port_id="451" />
153
+ <IR name="451" output_port_id="2" />
154
+ </map>
155
+ <map>
156
+ <framework name="452" output_port_id="452" />
157
+ <IR name="452" output_port_id="2" />
158
+ </map>
159
+ <map>
160
+ <framework name="466" output_port_id="466" />
161
+ <IR name="466" output_port_id="2" />
162
+ </map>
163
+ <map>
164
+ <framework name="467" output_port_id="467" />
165
+ <IR name="467" output_port_id="2" />
166
+ </map>
167
+ <map>
168
+ <framework name="489" output_port_id="489" />
169
+ <IR name="489" output_port_id="2" />
170
+ </map>
171
+ <map>
172
+ <framework name="490" output_port_id="490" />
173
+ <IR name="490" output_port_id="2" />
174
+ </map>
175
+ <map>
176
+ <framework name="502" output_port_id="502" />
177
+ <IR name="502" output_port_id="2" />
178
+ </map>
179
+ <map>
180
+ <framework name="504" output_port_id="504" />
181
+ <IR name="504" output_port_id="2" />
182
+ </map>
183
+ <map>
184
+ <framework name="505" output_port_id="505" />
185
+ <IR name="505" output_port_id="2" />
186
+ </map>
187
+ <map>
188
+ <framework name="506" output_port_id="506" />
189
+ <IR name="506" output_port_id="2" />
190
+ </map>
191
+ <map>
192
+ <framework name="515" output_port_id="515" />
193
+ <IR name="515" output_port_id="2" />
194
+ </map>
195
+ <map>
196
+ <framework name="516" output_port_id="516" />
197
+ <IR name="516" output_port_id="2" />
198
+ </map>
199
+ <map>
200
+ <framework name="517" output_port_id="517" />
201
+ <IR name="517" output_port_id="2" />
202
+ </map>
203
+ <map>
204
+ <framework name="519" output_port_id="519" />
205
+ <IR name="519" output_port_id="2" />
206
+ </map>
207
+ <map>
208
+ <framework name="520" output_port_id="520" />
209
+ <IR name="520" output_port_id="2" />
210
+ </map>
211
+ <map>
212
+ <framework name="528" output_port_id="528" />
213
+ <IR name="528" output_port_id="1" />
214
+ </map>
215
+ <map>
216
+ <framework name="530" output_port_id="530" />
217
+ <IR name="530" output_port_id="2" />
218
+ </map>
219
+ <map>
220
+ <framework name="531" output_port_id="531" />
221
+ <IR name="531" output_port_id="2" />
222
+ </map>
223
+ <map>
224
+ <framework name="532" output_port_id="532" />
225
+ <IR name="532" output_port_id="2" />
226
+ </map>
227
+ <map>
228
+ <framework name="541" output_port_id="541" />
229
+ <IR name="541" output_port_id="2" />
230
+ </map>
231
+ <map>
232
+ <framework name="542" output_port_id="542" />
233
+ <IR name="542" output_port_id="2" />
234
+ </map>
235
+ <map>
236
+ <framework name="543" output_port_id="543" />
237
+ <IR name="543" output_port_id="2" />
238
+ </map>
239
+ <map>
240
+ <framework name="545" output_port_id="545" />
241
+ <IR name="545" output_port_id="2" />
242
+ </map>
243
+ <map>
244
+ <framework name="546" output_port_id="546" />
245
+ <IR name="546" output_port_id="2" />
246
+ </map>
247
+ <map>
248
+ <framework name="595" output_port_id="595" />
249
+ <IR name="595" output_port_id="2" />
250
+ </map>
251
+ <map>
252
+ <framework name="596" output_port_id="596" />
253
+ <IR name="596" output_port_id="2" />
254
+ </map>
255
+ <map>
256
+ <framework name="548" output_port_id="548" />
257
+ <IR name="548" output_port_id="2" />
258
+ </map>
259
+ <map>
260
+ <framework name="549" output_port_id="549" />
261
+ <IR name="549" output_port_id="2" />
262
+ </map>
263
+ <map>
264
+ <framework name="563" output_port_id="563" />
265
+ <IR name="563" output_port_id="2" />
266
+ </map>
267
+ <map>
268
+ <framework name="597" output_port_id="597" />
269
+ <IR name="597" output_port_id="2" />
270
+ </map>
271
+ <map>
272
+ <framework name="600" output_port_id="600" />
273
+ <IR name="600" output_port_id="2" />
274
+ </map>
275
+ <map>
276
+ <framework name="601" output_port_id="601" />
277
+ <IR name="601" output_port_id="2" />
278
+ </map>
279
+ <map>
280
+ <framework name="602" output_port_id="602" />
281
+ <IR name="602" output_port_id="2" />
282
+ </map>
283
+ <map>
284
+ <framework name="565" output_port_id="565" />
285
+ <IR name="565" output_port_id="2" />
286
+ </map>
287
+ <map>
288
+ <framework name="566" output_port_id="566" />
289
+ <IR name="566" output_port_id="2" />
290
+ </map>
291
+ <map>
292
+ <framework name="580" output_port_id="580" />
293
+ <IR name="580" output_port_id="2" />
294
+ </map>
295
+ <map>
296
+ <framework name="581" output_port_id="581" />
297
+ <IR name="581" output_port_id="2" />
298
+ </map>
299
+ <map>
300
+ <framework name="603" output_port_id="603" />
301
+ <IR name="603" output_port_id="2" />
302
+ </map>
303
+ <map>
304
+ <framework name="604" output_port_id="604" />
305
+ <IR name="604" output_port_id="2" />
306
+ </map>
307
+ <map>
308
+ <framework name="616" output_port_id="616" />
309
+ <IR name="616" output_port_id="2" />
310
+ </map>
311
+ <map>
312
+ <framework name="618" output_port_id="618" />
313
+ <IR name="618" output_port_id="2" />
314
+ </map>
315
+ <map>
316
+ <framework name="619" output_port_id="619" />
317
+ <IR name="619" output_port_id="2" />
318
+ </map>
319
+ <map>
320
+ <framework name="620" output_port_id="620" />
321
+ <IR name="620" output_port_id="2" />
322
+ </map>
323
+ <map>
324
+ <framework name="629" output_port_id="629" />
325
+ <IR name="629" output_port_id="2" />
326
+ </map>
327
+ <map>
328
+ <framework name="630" output_port_id="630" />
329
+ <IR name="630" output_port_id="2" />
330
+ </map>
331
+ <map>
332
+ <framework name="631" output_port_id="631" />
333
+ <IR name="631" output_port_id="2" />
334
+ </map>
335
+ <map>
336
+ <framework name="633" output_port_id="633" />
337
+ <IR name="633" output_port_id="2" />
338
+ </map>
339
+ <map>
340
+ <framework name="634" output_port_id="634" />
341
+ <IR name="634" output_port_id="2" />
342
+ </map>
343
+ <map>
344
+ <framework name="642" output_port_id="642" />
345
+ <IR name="642" output_port_id="1" />
346
+ </map>
347
+ <map>
348
+ <framework name="644" output_port_id="644" />
349
+ <IR name="644" output_port_id="2" />
350
+ </map>
351
+ <map>
352
+ <framework name="645" output_port_id="645" />
353
+ <IR name="645" output_port_id="2" />
354
+ </map>
355
+ <map>
356
+ <framework name="646" output_port_id="646" />
357
+ <IR name="646" output_port_id="2" />
358
+ </map>
359
+ <map>
360
+ <framework name="655" output_port_id="655" />
361
+ <IR name="655" output_port_id="2" />
362
+ </map>
363
+ <map>
364
+ <framework name="656" output_port_id="656" />
365
+ <IR name="656" output_port_id="2" />
366
+ </map>
367
+ <map>
368
+ <framework name="657" output_port_id="657" />
369
+ <IR name="657" output_port_id="2" />
370
+ </map>
371
+ <map>
372
+ <framework name="659" output_port_id="659" />
373
+ <IR name="659" output_port_id="2" />
374
+ </map>
375
+ <map>
376
+ <framework name="660" output_port_id="660" />
377
+ <IR name="660" output_port_id="2" />
378
+ </map>
379
+ <map>
380
+ <framework name="709" output_port_id="709" />
381
+ <IR name="709" output_port_id="2" />
382
+ </map>
383
+ <map>
384
+ <framework name="710" output_port_id="710" />
385
+ <IR name="710" output_port_id="2" />
386
+ </map>
387
+ <map>
388
+ <framework name="662" output_port_id="662" />
389
+ <IR name="662" output_port_id="2" />
390
+ </map>
391
+ <map>
392
+ <framework name="663" output_port_id="663" />
393
+ <IR name="663" output_port_id="2" />
394
+ </map>
395
+ <map>
396
+ <framework name="677" output_port_id="677" />
397
+ <IR name="677" output_port_id="2" />
398
+ </map>
399
+ <map>
400
+ <framework name="711" output_port_id="711" />
401
+ <IR name="711" output_port_id="2" />
402
+ </map>
403
+ <map>
404
+ <framework name="714" output_port_id="714" />
405
+ <IR name="714" output_port_id="2" />
406
+ </map>
407
+ <map>
408
+ <framework name="715" output_port_id="715" />
409
+ <IR name="715" output_port_id="2" />
410
+ </map>
411
+ <map>
412
+ <framework name="716" output_port_id="716" />
413
+ <IR name="716" output_port_id="2" />
414
+ </map>
415
+ <map>
416
+ <framework name="679" output_port_id="679" />
417
+ <IR name="679" output_port_id="2" />
418
+ </map>
419
+ <map>
420
+ <framework name="680" output_port_id="680" />
421
+ <IR name="680" output_port_id="2" />
422
+ </map>
423
+ <map>
424
+ <framework name="694" output_port_id="694" />
425
+ <IR name="694" output_port_id="2" />
426
+ </map>
427
+ <map>
428
+ <framework name="695" output_port_id="695" />
429
+ <IR name="695" output_port_id="2" />
430
+ </map>
431
+ <map>
432
+ <framework name="717" output_port_id="717" />
433
+ <IR name="717" output_port_id="2" />
434
+ </map>
435
+ <map>
436
+ <framework name="718" output_port_id="718" />
437
+ <IR name="718" output_port_id="2" />
438
+ </map>
439
+ <map>
440
+ <framework name="730" output_port_id="730" />
441
+ <IR name="730" output_port_id="2" />
442
+ </map>
443
+ <map>
444
+ <framework name="732" output_port_id="732" />
445
+ <IR name="732" output_port_id="2" />
446
+ </map>
447
+ <map>
448
+ <framework name="733" output_port_id="733" />
449
+ <IR name="733" output_port_id="2" />
450
+ </map>
451
+ <map>
452
+ <framework name="734" output_port_id="734" />
453
+ <IR name="734" output_port_id="2" />
454
+ </map>
455
+ <map>
456
+ <framework name="743" output_port_id="743" />
457
+ <IR name="743" output_port_id="2" />
458
+ </map>
459
+ <map>
460
+ <framework name="744" output_port_id="744" />
461
+ <IR name="744" output_port_id="2" />
462
+ </map>
463
+ <map>
464
+ <framework name="745" output_port_id="745" />
465
+ <IR name="745" output_port_id="2" />
466
+ </map>
467
+ <map>
468
+ <framework name="747" output_port_id="747" />
469
+ <IR name="747" output_port_id="2" />
470
+ </map>
471
+ <map>
472
+ <framework name="748" output_port_id="748" />
473
+ <IR name="748" output_port_id="2" />
474
+ </map>
475
+ <map>
476
+ <framework name="756" output_port_id="756" />
477
+ <IR name="756" output_port_id="1" />
478
+ </map>
479
+ <map>
480
+ <framework name="758" output_port_id="758" />
481
+ <IR name="758" output_port_id="2" />
482
+ </map>
483
+ <map>
484
+ <framework name="759" output_port_id="759" />
485
+ <IR name="759" output_port_id="2" />
486
+ </map>
487
+ <map>
488
+ <framework name="760" output_port_id="760" />
489
+ <IR name="760" output_port_id="2" />
490
+ </map>
491
+ <map>
492
+ <framework name="769" output_port_id="769" />
493
+ <IR name="769" output_port_id="2" />
494
+ </map>
495
+ <map>
496
+ <framework name="770" output_port_id="770" />
497
+ <IR name="770" output_port_id="2" />
498
+ </map>
499
+ <map>
500
+ <framework name="771" output_port_id="771" />
501
+ <IR name="771" output_port_id="2" />
502
+ </map>
503
+ <map>
504
+ <framework name="773" output_port_id="773" />
505
+ <IR name="773" output_port_id="2" />
506
+ </map>
507
+ <map>
508
+ <framework name="774" output_port_id="774" />
509
+ <IR name="774" output_port_id="2" />
510
+ </map>
511
+ <map>
512
+ <framework name="823" output_port_id="823" />
513
+ <IR name="823" output_port_id="2" />
514
+ </map>
515
+ <map>
516
+ <framework name="824" output_port_id="824" />
517
+ <IR name="824" output_port_id="2" />
518
+ </map>
519
+ <map>
520
+ <framework name="776" output_port_id="776" />
521
+ <IR name="776" output_port_id="2" />
522
+ </map>
523
+ <map>
524
+ <framework name="777" output_port_id="777" />
525
+ <IR name="777" output_port_id="2" />
526
+ </map>
527
+ <map>
528
+ <framework name="791" output_port_id="791" />
529
+ <IR name="791" output_port_id="2" />
530
+ </map>
531
+ <map>
532
+ <framework name="825" output_port_id="825" />
533
+ <IR name="825" output_port_id="2" />
534
+ </map>
535
+ <map>
536
+ <framework name="828" output_port_id="828" />
537
+ <IR name="828" output_port_id="2" />
538
+ </map>
539
+ <map>
540
+ <framework name="829" output_port_id="829" />
541
+ <IR name="829" output_port_id="2" />
542
+ </map>
543
+ <map>
544
+ <framework name="830" output_port_id="830" />
545
+ <IR name="830" output_port_id="2" />
546
+ </map>
547
+ <map>
548
+ <framework name="793" output_port_id="793" />
549
+ <IR name="793" output_port_id="2" />
550
+ </map>
551
+ <map>
552
+ <framework name="794" output_port_id="794" />
553
+ <IR name="794" output_port_id="2" />
554
+ </map>
555
+ <map>
556
+ <framework name="808" output_port_id="808" />
557
+ <IR name="808" output_port_id="2" />
558
+ </map>
559
+ <map>
560
+ <framework name="809" output_port_id="809" />
561
+ <IR name="809" output_port_id="2" />
562
+ </map>
563
+ <map>
564
+ <framework name="831" output_port_id="831" />
565
+ <IR name="831" output_port_id="2" />
566
+ </map>
567
+ <map>
568
+ <framework name="832" output_port_id="832" />
569
+ <IR name="832" output_port_id="2" />
570
+ </map>
571
+ <map>
572
+ <framework name="844" output_port_id="844" />
573
+ <IR name="844" output_port_id="2" />
574
+ </map>
575
+ <map>
576
+ <framework name="846" output_port_id="846" />
577
+ <IR name="846" output_port_id="2" />
578
+ </map>
579
+ <map>
580
+ <framework name="847" output_port_id="847" />
581
+ <IR name="847" output_port_id="2" />
582
+ </map>
583
+ <map>
584
+ <framework name="848" output_port_id="848" />
585
+ <IR name="848" output_port_id="2" />
586
+ </map>
587
+ <map>
588
+ <framework name="857" output_port_id="857" />
589
+ <IR name="857" output_port_id="2" />
590
+ </map>
591
+ <map>
592
+ <framework name="858" output_port_id="858" />
593
+ <IR name="858" output_port_id="2" />
594
+ </map>
595
+ <map>
596
+ <framework name="859" output_port_id="859" />
597
+ <IR name="859" output_port_id="2" />
598
+ </map>
599
+ <map>
600
+ <framework name="861" output_port_id="861" />
601
+ <IR name="861" output_port_id="2" />
602
+ </map>
603
+ <map>
604
+ <framework name="862" output_port_id="862" />
605
+ <IR name="862" output_port_id="2" />
606
+ </map>
607
+ <map>
608
+ <framework name="870" output_port_id="870" />
609
+ <IR name="870" output_port_id="1" />
610
+ </map>
611
+ <map>
612
+ <framework name="872" output_port_id="872" />
613
+ <IR name="872" output_port_id="2" />
614
+ </map>
615
+ <map>
616
+ <framework name="873" output_port_id="873" />
617
+ <IR name="873" output_port_id="2" />
618
+ </map>
619
+ <map>
620
+ <framework name="874" output_port_id="874" />
621
+ <IR name="874" output_port_id="2" />
622
+ </map>
623
+ <map>
624
+ <framework name="883" output_port_id="883" />
625
+ <IR name="883" output_port_id="2" />
626
+ </map>
627
+ <map>
628
+ <framework name="884" output_port_id="884" />
629
+ <IR name="884" output_port_id="2" />
630
+ </map>
631
+ <map>
632
+ <framework name="885" output_port_id="885" />
633
+ <IR name="885" output_port_id="2" />
634
+ </map>
635
+ <map>
636
+ <framework name="887" output_port_id="887" />
637
+ <IR name="887" output_port_id="2" />
638
+ </map>
639
+ <map>
640
+ <framework name="888" output_port_id="888" />
641
+ <IR name="888" output_port_id="2" />
642
+ </map>
643
+ <map>
644
+ <framework name="937" output_port_id="937" />
645
+ <IR name="937" output_port_id="2" />
646
+ </map>
647
+ <map>
648
+ <framework name="938" output_port_id="938" />
649
+ <IR name="938" output_port_id="2" />
650
+ </map>
651
+ <map>
652
+ <framework name="890" output_port_id="890" />
653
+ <IR name="890" output_port_id="2" />
654
+ </map>
655
+ <map>
656
+ <framework name="891" output_port_id="891" />
657
+ <IR name="891" output_port_id="2" />
658
+ </map>
659
+ <map>
660
+ <framework name="905" output_port_id="905" />
661
+ <IR name="905" output_port_id="2" />
662
+ </map>
663
+ <map>
664
+ <framework name="939" output_port_id="939" />
665
+ <IR name="939" output_port_id="2" />
666
+ </map>
667
+ <map>
668
+ <framework name="942" output_port_id="942" />
669
+ <IR name="942" output_port_id="2" />
670
+ </map>
671
+ <map>
672
+ <framework name="943" output_port_id="943" />
673
+ <IR name="943" output_port_id="2" />
674
+ </map>
675
+ <map>
676
+ <framework name="944" output_port_id="944" />
677
+ <IR name="944" output_port_id="2" />
678
+ </map>
679
+ <map>
680
+ <framework name="907" output_port_id="907" />
681
+ <IR name="907" output_port_id="2" />
682
+ </map>
683
+ <map>
684
+ <framework name="908" output_port_id="908" />
685
+ <IR name="908" output_port_id="2" />
686
+ </map>
687
+ <map>
688
+ <framework name="922" output_port_id="922" />
689
+ <IR name="922" output_port_id="2" />
690
+ </map>
691
+ <map>
692
+ <framework name="923" output_port_id="923" />
693
+ <IR name="923" output_port_id="2" />
694
+ </map>
695
+ <map>
696
+ <framework name="945" output_port_id="945" />
697
+ <IR name="945" output_port_id="2" />
698
+ </map>
699
+ <map>
700
+ <framework name="946" output_port_id="946" />
701
+ <IR name="946" output_port_id="2" />
702
+ </map>
703
+ <map>
704
+ <framework name="958" output_port_id="958" />
705
+ <IR name="958" output_port_id="2" />
706
+ </map>
707
+ <map>
708
+ <framework name="960" output_port_id="960" />
709
+ <IR name="960" output_port_id="2" />
710
+ </map>
711
+ <map>
712
+ <framework name="961" output_port_id="961" />
713
+ <IR name="961" output_port_id="2" />
714
+ </map>
715
+ <map>
716
+ <framework name="962" output_port_id="962" />
717
+ <IR name="962" output_port_id="2" />
718
+ </map>
719
+ <map>
720
+ <framework name="971" output_port_id="971" />
721
+ <IR name="971" output_port_id="2" />
722
+ </map>
723
+ <map>
724
+ <framework name="972" output_port_id="972" />
725
+ <IR name="972" output_port_id="2" />
726
+ </map>
727
+ <map>
728
+ <framework name="973" output_port_id="973" />
729
+ <IR name="973" output_port_id="2" />
730
+ </map>
731
+ <map>
732
+ <framework name="975" output_port_id="975" />
733
+ <IR name="975" output_port_id="2" />
734
+ </map>
735
+ <map>
736
+ <framework name="976" output_port_id="976" />
737
+ <IR name="976" output_port_id="2" />
738
+ </map>
739
+ <map>
740
+ <framework name="984" output_port_id="984" />
741
+ <IR name="984" output_port_id="1" />
742
+ </map>
743
+ <map>
744
+ <framework name="986" output_port_id="986" />
745
+ <IR name="986" output_port_id="2" />
746
+ </map>
747
+ <map>
748
+ <framework name="987" output_port_id="987" />
749
+ <IR name="987" output_port_id="2" />
750
+ </map>
751
+ <map>
752
+ <framework name="988" output_port_id="988" />
753
+ <IR name="988" output_port_id="2" />
754
+ </map>
755
+ <map>
756
+ <framework name="997" output_port_id="997" />
757
+ <IR name="997" output_port_id="2" />
758
+ </map>
759
+ <map>
760
+ <framework name="998" output_port_id="998" />
761
+ <IR name="998" output_port_id="2" />
762
+ </map>
763
+ <map>
764
+ <framework name="999" output_port_id="999" />
765
+ <IR name="999" output_port_id="2" />
766
+ </map>
767
+ <map>
768
+ <framework name="1001" output_port_id="1001" />
769
+ <IR name="1001" output_port_id="2" />
770
+ </map>
771
+ <map>
772
+ <framework name="1002" output_port_id="1002" />
773
+ <IR name="1002" output_port_id="2" />
774
+ </map>
775
+ <map>
776
+ <framework name="1051" output_port_id="1051" />
777
+ <IR name="1051" output_port_id="2" />
778
+ </map>
779
+ <map>
780
+ <framework name="1052" output_port_id="1052" />
781
+ <IR name="1052" output_port_id="2" />
782
+ </map>
783
+ <map>
784
+ <framework name="1004" output_port_id="1004" />
785
+ <IR name="1004" output_port_id="2" />
786
+ </map>
787
+ <map>
788
+ <framework name="1005" output_port_id="1005" />
789
+ <IR name="1005" output_port_id="2" />
790
+ </map>
791
+ <map>
792
+ <framework name="1019" output_port_id="1019" />
793
+ <IR name="1019" output_port_id="2" />
794
+ </map>
795
+ <map>
796
+ <framework name="1053" output_port_id="1053" />
797
+ <IR name="1053" output_port_id="2" />
798
+ </map>
799
+ <map>
800
+ <framework name="1056" output_port_id="1056" />
801
+ <IR name="1056" output_port_id="2" />
802
+ </map>
803
+ <map>
804
+ <framework name="1057" output_port_id="1057" />
805
+ <IR name="1057" output_port_id="2" />
806
+ </map>
807
+ <map>
808
+ <framework name="1058" output_port_id="1058" />
809
+ <IR name="1058" output_port_id="2" />
810
+ </map>
811
+ <map>
812
+ <framework name="1021" output_port_id="1021" />
813
+ <IR name="1021" output_port_id="2" />
814
+ </map>
815
+ <map>
816
+ <framework name="1022" output_port_id="1022" />
817
+ <IR name="1022" output_port_id="2" />
818
+ </map>
819
+ <map>
820
+ <framework name="1036" output_port_id="1036" />
821
+ <IR name="1036" output_port_id="2" />
822
+ </map>
823
+ <map>
824
+ <framework name="1037" output_port_id="1037" />
825
+ <IR name="1037" output_port_id="2" />
826
+ </map>
827
+ <map>
828
+ <framework name="1059" output_port_id="1059" />
829
+ <IR name="1059" output_port_id="2" />
830
+ </map>
831
+ <map>
832
+ <framework name="1060" output_port_id="1060" />
833
+ <IR name="1060" output_port_id="2" />
834
+ </map>
835
+ <map>
836
+ <framework name="1072" output_port_id="1072" />
837
+ <IR name="1072" output_port_id="2" />
838
+ </map>
839
+ <map>
840
+ <framework name="1074" output_port_id="1074" />
841
+ <IR name="1074" output_port_id="2" />
842
+ </map>
843
+ <map>
844
+ <framework name="1075" output_port_id="1075" />
845
+ <IR name="1075" output_port_id="2" />
846
+ </map>
847
+ <map>
848
+ <framework name="1076" output_port_id="1076" />
849
+ <IR name="1076" output_port_id="2" />
850
+ </map>
851
+ <map>
852
+ <framework name="1085" output_port_id="1085" />
853
+ <IR name="1085" output_port_id="2" />
854
+ </map>
855
+ <map>
856
+ <framework name="1086" output_port_id="1086" />
857
+ <IR name="1086" output_port_id="2" />
858
+ </map>
859
+ <map>
860
+ <framework name="1087" output_port_id="1087" />
861
+ <IR name="1087" output_port_id="2" />
862
+ </map>
863
+ <map>
864
+ <framework name="1089" output_port_id="1089" />
865
+ <IR name="1089" output_port_id="2" />
866
+ </map>
867
+ <map>
868
+ <framework name="1090" output_port_id="1090" />
869
+ <IR name="1090" output_port_id="2" />
870
+ </map>
871
+ <map>
872
+ <framework name="1098" output_port_id="1098" />
873
+ <IR name="1098" output_port_id="1" />
874
+ </map>
875
+ <map>
876
+ <framework name="1100" output_port_id="1100" />
877
+ <IR name="1100" output_port_id="2" />
878
+ </map>
879
+ <map>
880
+ <framework name="1101" output_port_id="1101" />
881
+ <IR name="1101" output_port_id="2" />
882
+ </map>
883
+ <map>
884
+ <framework name="1102" output_port_id="1102" />
885
+ <IR name="1102" output_port_id="2" />
886
+ </map>
887
+ <map>
888
+ <framework name="1111" output_port_id="1111" />
889
+ <IR name="1111" output_port_id="2" />
890
+ </map>
891
+ <map>
892
+ <framework name="1112" output_port_id="1112" />
893
+ <IR name="1112" output_port_id="2" />
894
+ </map>
895
+ <map>
896
+ <framework name="1113" output_port_id="1113" />
897
+ <IR name="1113" output_port_id="2" />
898
+ </map>
899
+ <map>
900
+ <framework name="1115" output_port_id="1115" />
901
+ <IR name="1115" output_port_id="2" />
902
+ </map>
903
+ <map>
904
+ <framework name="1116" output_port_id="1116" />
905
+ <IR name="1116" output_port_id="2" />
906
+ </map>
907
+ <map>
908
+ <framework name="1165" output_port_id="1165" />
909
+ <IR name="1165" output_port_id="2" />
910
+ </map>
911
+ <map>
912
+ <framework name="1166" output_port_id="1166" />
913
+ <IR name="1166" output_port_id="2" />
914
+ </map>
915
+ <map>
916
+ <framework name="1118" output_port_id="1118" />
917
+ <IR name="1118" output_port_id="2" />
918
+ </map>
919
+ <map>
920
+ <framework name="1119" output_port_id="1119" />
921
+ <IR name="1119" output_port_id="2" />
922
+ </map>
923
+ <map>
924
+ <framework name="1133" output_port_id="1133" />
925
+ <IR name="1133" output_port_id="2" />
926
+ </map>
927
+ <map>
928
+ <framework name="1167" output_port_id="1167" />
929
+ <IR name="1167" output_port_id="2" />
930
+ </map>
931
+ <map>
932
+ <framework name="1170" output_port_id="1170" />
933
+ <IR name="1170" output_port_id="2" />
934
+ </map>
935
+ <map>
936
+ <framework name="1171" output_port_id="1171" />
937
+ <IR name="1171" output_port_id="2" />
938
+ </map>
939
+ <map>
940
+ <framework name="1172" output_port_id="1172" />
941
+ <IR name="1172" output_port_id="2" />
942
+ </map>
943
+ <map>
944
+ <framework name="1135" output_port_id="1135" />
945
+ <IR name="1135" output_port_id="2" />
946
+ </map>
947
+ <map>
948
+ <framework name="1136" output_port_id="1136" />
949
+ <IR name="1136" output_port_id="2" />
950
+ </map>
951
+ <map>
952
+ <framework name="1150" output_port_id="1150" />
953
+ <IR name="1150" output_port_id="2" />
954
+ </map>
955
+ <map>
956
+ <framework name="1151" output_port_id="1151" />
957
+ <IR name="1151" output_port_id="2" />
958
+ </map>
959
+ <map>
960
+ <framework name="1173" output_port_id="1173" />
961
+ <IR name="1173" output_port_id="2" />
962
+ </map>
963
+ <map>
964
+ <framework name="1174" output_port_id="1174" />
965
+ <IR name="1174" output_port_id="2" />
966
+ </map>
967
+ <map>
968
+ <framework name="1186" output_port_id="1186" />
969
+ <IR name="1186" output_port_id="2" />
970
+ </map>
971
+ <map>
972
+ <framework name="1188" output_port_id="1188" />
973
+ <IR name="1188" output_port_id="2" />
974
+ </map>
975
+ <map>
976
+ <framework name="1189" output_port_id="1189" />
977
+ <IR name="1189" output_port_id="2" />
978
+ </map>
979
+ <map>
980
+ <framework name="1190" output_port_id="1190" />
981
+ <IR name="1190" output_port_id="2" />
982
+ </map>
983
+ <map>
984
+ <framework name="1199" output_port_id="1199" />
985
+ <IR name="1199" output_port_id="2" />
986
+ </map>
987
+ <map>
988
+ <framework name="1200" output_port_id="1200" />
989
+ <IR name="1200" output_port_id="2" />
990
+ </map>
991
+ <map>
992
+ <framework name="1201" output_port_id="1201" />
993
+ <IR name="1201" output_port_id="2" />
994
+ </map>
995
+ <map>
996
+ <framework name="1203" output_port_id="1203" />
997
+ <IR name="1203" output_port_id="2" />
998
+ </map>
999
+ <map>
1000
+ <framework name="1204" output_port_id="1204" />
1001
+ <IR name="1204" output_port_id="2" />
1002
+ </map>
1003
+ <map>
1004
+ <framework name="1212" output_port_id="1212" />
1005
+ <IR name="1212" output_port_id="1" />
1006
+ </map>
1007
+ <map>
1008
+ <framework name="1214" output_port_id="1214" />
1009
+ <IR name="1214" output_port_id="2" />
1010
+ </map>
1011
+ <map>
1012
+ <framework name="1215" output_port_id="1215" />
1013
+ <IR name="1215" output_port_id="2" />
1014
+ </map>
1015
+ <map>
1016
+ <framework name="1216" output_port_id="1216" />
1017
+ <IR name="1216" output_port_id="2" />
1018
+ </map>
1019
+ <map>
1020
+ <framework name="1225" output_port_id="1225" />
1021
+ <IR name="1225" output_port_id="2" />
1022
+ </map>
1023
+ <map>
1024
+ <framework name="1226" output_port_id="1226" />
1025
+ <IR name="1226" output_port_id="2" />
1026
+ </map>
1027
+ <map>
1028
+ <framework name="1227" output_port_id="1227" />
1029
+ <IR name="1227" output_port_id="2" />
1030
+ </map>
1031
+ <map>
1032
+ <framework name="1229" output_port_id="1229" />
1033
+ <IR name="1229" output_port_id="2" />
1034
+ </map>
1035
+ <map>
1036
+ <framework name="1230" output_port_id="1230" />
1037
+ <IR name="1230" output_port_id="2" />
1038
+ </map>
1039
+ <map>
1040
+ <framework name="1279" output_port_id="1279" />
1041
+ <IR name="1279" output_port_id="2" />
1042
+ </map>
1043
+ <map>
1044
+ <framework name="1280" output_port_id="1280" />
1045
+ <IR name="1280" output_port_id="2" />
1046
+ </map>
1047
+ <map>
1048
+ <framework name="1232" output_port_id="1232" />
1049
+ <IR name="1232" output_port_id="2" />
1050
+ </map>
1051
+ <map>
1052
+ <framework name="1233" output_port_id="1233" />
1053
+ <IR name="1233" output_port_id="2" />
1054
+ </map>
1055
+ <map>
1056
+ <framework name="1247" output_port_id="1247" />
1057
+ <IR name="1247" output_port_id="2" />
1058
+ </map>
1059
+ <map>
1060
+ <framework name="1281" output_port_id="1281" />
1061
+ <IR name="1281" output_port_id="2" />
1062
+ </map>
1063
+ <map>
1064
+ <framework name="1284" output_port_id="1284" />
1065
+ <IR name="1284" output_port_id="2" />
1066
+ </map>
1067
+ <map>
1068
+ <framework name="1285" output_port_id="1285" />
1069
+ <IR name="1285" output_port_id="2" />
1070
+ </map>
1071
+ <map>
1072
+ <framework name="1286" output_port_id="1286" />
1073
+ <IR name="1286" output_port_id="2" />
1074
+ </map>
1075
+ <map>
1076
+ <framework name="1249" output_port_id="1249" />
1077
+ <IR name="1249" output_port_id="2" />
1078
+ </map>
1079
+ <map>
1080
+ <framework name="1250" output_port_id="1250" />
1081
+ <IR name="1250" output_port_id="2" />
1082
+ </map>
1083
+ <map>
1084
+ <framework name="1264" output_port_id="1264" />
1085
+ <IR name="1264" output_port_id="2" />
1086
+ </map>
1087
+ <map>
1088
+ <framework name="1265" output_port_id="1265" />
1089
+ <IR name="1265" output_port_id="2" />
1090
+ </map>
1091
+ <map>
1092
+ <framework name="1287" output_port_id="1287" />
1093
+ <IR name="1287" output_port_id="2" />
1094
+ </map>
1095
+ <map>
1096
+ <framework name="1288" output_port_id="1288" />
1097
+ <IR name="1288" output_port_id="2" />
1098
+ </map>
1099
+ <map>
1100
+ <framework name="1300" output_port_id="1300" />
1101
+ <IR name="1300" output_port_id="2" />
1102
+ </map>
1103
+ <map>
1104
+ <framework name="1302" output_port_id="1302" />
1105
+ <IR name="1302" output_port_id="2" />
1106
+ </map>
1107
+ <map>
1108
+ <framework name="1303" output_port_id="1303" />
1109
+ <IR name="1303" output_port_id="2" />
1110
+ </map>
1111
+ <map>
1112
+ <framework name="1304" output_port_id="1304" />
1113
+ <IR name="1304" output_port_id="2" />
1114
+ </map>
1115
+ <map>
1116
+ <framework name="1313" output_port_id="1313" />
1117
+ <IR name="1313" output_port_id="2" />
1118
+ </map>
1119
+ <map>
1120
+ <framework name="1314" output_port_id="1314" />
1121
+ <IR name="1314" output_port_id="2" />
1122
+ </map>
1123
+ <map>
1124
+ <framework name="1315" output_port_id="1315" />
1125
+ <IR name="1315" output_port_id="2" />
1126
+ </map>
1127
+ <map>
1128
+ <framework name="1317" output_port_id="1317" />
1129
+ <IR name="1317" output_port_id="2" />
1130
+ </map>
1131
+ <map>
1132
+ <framework name="1318" output_port_id="1318" />
1133
+ <IR name="1318" output_port_id="2" />
1134
+ </map>
1135
+ <map>
1136
+ <framework name="1326" output_port_id="1326" />
1137
+ <IR name="1326" output_port_id="1" />
1138
+ </map>
1139
+ <map>
1140
+ <framework name="1328" output_port_id="1328" />
1141
+ <IR name="1328" output_port_id="2" />
1142
+ </map>
1143
+ <map>
1144
+ <framework name="1329" output_port_id="1329" />
1145
+ <IR name="1329" output_port_id="2" />
1146
+ </map>
1147
+ <map>
1148
+ <framework name="1330" output_port_id="1330" />
1149
+ <IR name="1330" output_port_id="2" />
1150
+ </map>
1151
+ <map>
1152
+ <framework name="1339" output_port_id="1339" />
1153
+ <IR name="1339" output_port_id="2" />
1154
+ </map>
1155
+ <map>
1156
+ <framework name="1340" output_port_id="1340" />
1157
+ <IR name="1340" output_port_id="2" />
1158
+ </map>
1159
+ <map>
1160
+ <framework name="1341" output_port_id="1341" />
1161
+ <IR name="1341" output_port_id="2" />
1162
+ </map>
1163
+ <map>
1164
+ <framework name="1343" output_port_id="1343" />
1165
+ <IR name="1343" output_port_id="2" />
1166
+ </map>
1167
+ <map>
1168
+ <framework name="1344" output_port_id="1344" />
1169
+ <IR name="1344" output_port_id="2" />
1170
+ </map>
1171
+ <map>
1172
+ <framework name="1393" output_port_id="1393" />
1173
+ <IR name="1393" output_port_id="2" />
1174
+ </map>
1175
+ <map>
1176
+ <framework name="1394" output_port_id="1394" />
1177
+ <IR name="1394" output_port_id="2" />
1178
+ </map>
1179
+ <map>
1180
+ <framework name="1346" output_port_id="1346" />
1181
+ <IR name="1346" output_port_id="2" />
1182
+ </map>
1183
+ <map>
1184
+ <framework name="1347" output_port_id="1347" />
1185
+ <IR name="1347" output_port_id="2" />
1186
+ </map>
1187
+ <map>
1188
+ <framework name="1361" output_port_id="1361" />
1189
+ <IR name="1361" output_port_id="2" />
1190
+ </map>
1191
+ <map>
1192
+ <framework name="1395" output_port_id="1395" />
1193
+ <IR name="1395" output_port_id="2" />
1194
+ </map>
1195
+ <map>
1196
+ <framework name="1398" output_port_id="1398" />
1197
+ <IR name="1398" output_port_id="2" />
1198
+ </map>
1199
+ <map>
1200
+ <framework name="1399" output_port_id="1399" />
1201
+ <IR name="1399" output_port_id="2" />
1202
+ </map>
1203
+ <map>
1204
+ <framework name="1400" output_port_id="1400" />
1205
+ <IR name="1400" output_port_id="2" />
1206
+ </map>
1207
+ <map>
1208
+ <framework name="1363" output_port_id="1363" />
1209
+ <IR name="1363" output_port_id="2" />
1210
+ </map>
1211
+ <map>
1212
+ <framework name="1364" output_port_id="1364" />
1213
+ <IR name="1364" output_port_id="2" />
1214
+ </map>
1215
+ <map>
1216
+ <framework name="1378" output_port_id="1378" />
1217
+ <IR name="1378" output_port_id="2" />
1218
+ </map>
1219
+ <map>
1220
+ <framework name="1379" output_port_id="1379" />
1221
+ <IR name="1379" output_port_id="2" />
1222
+ </map>
1223
+ <map>
1224
+ <framework name="1401" output_port_id="1401" />
1225
+ <IR name="1401" output_port_id="2" />
1226
+ </map>
1227
+ <map>
1228
+ <framework name="1402" output_port_id="1402" />
1229
+ <IR name="1402" output_port_id="2" />
1230
+ </map>
1231
+ <map>
1232
+ <framework name="1414" output_port_id="1414" />
1233
+ <IR name="1414" output_port_id="2" />
1234
+ </map>
1235
+ <map>
1236
+ <framework name="1416" output_port_id="1416" />
1237
+ <IR name="1416" output_port_id="2" />
1238
+ </map>
1239
+ <map>
1240
+ <framework name="1417" output_port_id="1417" />
1241
+ <IR name="1417" output_port_id="2" />
1242
+ </map>
1243
+ <map>
1244
+ <framework name="1418" output_port_id="1418" />
1245
+ <IR name="1418" output_port_id="2" />
1246
+ </map>
1247
+ <map>
1248
+ <framework name="1427" output_port_id="1427" />
1249
+ <IR name="1427" output_port_id="2" />
1250
+ </map>
1251
+ <map>
1252
+ <framework name="1428" output_port_id="1428" />
1253
+ <IR name="1428" output_port_id="2" />
1254
+ </map>
1255
+ <map>
1256
+ <framework name="1429" output_port_id="1429" />
1257
+ <IR name="1429" output_port_id="2" />
1258
+ </map>
1259
+ <map>
1260
+ <framework name="1431" output_port_id="1431" />
1261
+ <IR name="1431" output_port_id="2" />
1262
+ </map>
1263
+ <map>
1264
+ <framework name="1432" output_port_id="1432" />
1265
+ <IR name="1432" output_port_id="2" />
1266
+ </map>
1267
+ <map>
1268
+ <framework name="1440" output_port_id="1440" />
1269
+ <IR name="1440" output_port_id="1" />
1270
+ </map>
1271
+ <map>
1272
+ <framework name="1442" output_port_id="1442" />
1273
+ <IR name="1442" output_port_id="2" />
1274
+ </map>
1275
+ <map>
1276
+ <framework name="1443" output_port_id="1443" />
1277
+ <IR name="1443" output_port_id="2" />
1278
+ </map>
1279
+ <map>
1280
+ <framework name="1444" output_port_id="1444" />
1281
+ <IR name="1444" output_port_id="2" />
1282
+ </map>
1283
+ <map>
1284
+ <framework name="1453" output_port_id="1453" />
1285
+ <IR name="1453" output_port_id="2" />
1286
+ </map>
1287
+ <map>
1288
+ <framework name="1454" output_port_id="1454" />
1289
+ <IR name="1454" output_port_id="2" />
1290
+ </map>
1291
+ <map>
1292
+ <framework name="1455" output_port_id="1455" />
1293
+ <IR name="1455" output_port_id="2" />
1294
+ </map>
1295
+ <map>
1296
+ <framework name="1457" output_port_id="1457" />
1297
+ <IR name="1457" output_port_id="2" />
1298
+ </map>
1299
+ <map>
1300
+ <framework name="1458" output_port_id="1458" />
1301
+ <IR name="1458" output_port_id="2" />
1302
+ </map>
1303
+ <map>
1304
+ <framework name="1507" output_port_id="1507" />
1305
+ <IR name="1507" output_port_id="2" />
1306
+ </map>
1307
+ <map>
1308
+ <framework name="1508" output_port_id="1508" />
1309
+ <IR name="1508" output_port_id="2" />
1310
+ </map>
1311
+ <map>
1312
+ <framework name="1460" output_port_id="1460" />
1313
+ <IR name="1460" output_port_id="2" />
1314
+ </map>
1315
+ <map>
1316
+ <framework name="1461" output_port_id="1461" />
1317
+ <IR name="1461" output_port_id="2" />
1318
+ </map>
1319
+ <map>
1320
+ <framework name="1475" output_port_id="1475" />
1321
+ <IR name="1475" output_port_id="2" />
1322
+ </map>
1323
+ <map>
1324
+ <framework name="1509" output_port_id="1509" />
1325
+ <IR name="1509" output_port_id="2" />
1326
+ </map>
1327
+ <map>
1328
+ <framework name="1512" output_port_id="1512" />
1329
+ <IR name="1512" output_port_id="2" />
1330
+ </map>
1331
+ <map>
1332
+ <framework name="1513" output_port_id="1513" />
1333
+ <IR name="1513" output_port_id="2" />
1334
+ </map>
1335
+ <map>
1336
+ <framework name="1514" output_port_id="1514" />
1337
+ <IR name="1514" output_port_id="2" />
1338
+ </map>
1339
+ <map>
1340
+ <framework name="1477" output_port_id="1477" />
1341
+ <IR name="1477" output_port_id="2" />
1342
+ </map>
1343
+ <map>
1344
+ <framework name="1478" output_port_id="1478" />
1345
+ <IR name="1478" output_port_id="2" />
1346
+ </map>
1347
+ <map>
1348
+ <framework name="1492" output_port_id="1492" />
1349
+ <IR name="1492" output_port_id="2" />
1350
+ </map>
1351
+ <map>
1352
+ <framework name="1493" output_port_id="1493" />
1353
+ <IR name="1493" output_port_id="2" />
1354
+ </map>
1355
+ <map>
1356
+ <framework name="1515" output_port_id="1515" />
1357
+ <IR name="1515" output_port_id="2" />
1358
+ </map>
1359
+ <map>
1360
+ <framework name="1516" output_port_id="1516" />
1361
+ <IR name="1516" output_port_id="2" />
1362
+ </map>
1363
+ <map>
1364
+ <framework name="1528" output_port_id="1528" />
1365
+ <IR name="1528" output_port_id="2" />
1366
+ </map>
1367
+ <map>
1368
+ <framework name="1530" output_port_id="1530" />
1369
+ <IR name="1530" output_port_id="2" />
1370
+ </map>
1371
+ <map>
1372
+ <framework name="1531" output_port_id="1531" />
1373
+ <IR name="1531" output_port_id="2" />
1374
+ </map>
1375
+ <map>
1376
+ <framework name="1532" output_port_id="1532" />
1377
+ <IR name="1532" output_port_id="2" />
1378
+ </map>
1379
+ <map>
1380
+ <framework name="1541" output_port_id="1541" />
1381
+ <IR name="1541" output_port_id="2" />
1382
+ </map>
1383
+ <map>
1384
+ <framework name="1542" output_port_id="1542" />
1385
+ <IR name="1542" output_port_id="2" />
1386
+ </map>
1387
+ <map>
1388
+ <framework name="1543" output_port_id="1543" />
1389
+ <IR name="1543" output_port_id="2" />
1390
+ </map>
1391
+ <map>
1392
+ <framework name="1545" output_port_id="1545" />
1393
+ <IR name="1545" output_port_id="2" />
1394
+ </map>
1395
+ <map>
1396
+ <framework name="1546" output_port_id="1546" />
1397
+ <IR name="1546" output_port_id="2" />
1398
+ </map>
1399
+ <map>
1400
+ <framework name="1554" output_port_id="1554" />
1401
+ <IR name="1554" output_port_id="1" />
1402
+ </map>
1403
+ <map>
1404
+ <framework name="1556" output_port_id="1556" />
1405
+ <IR name="1556" output_port_id="2" />
1406
+ </map>
1407
+ <map>
1408
+ <framework name="1557" output_port_id="1557" />
1409
+ <IR name="1557" output_port_id="2" />
1410
+ </map>
1411
+ <map>
1412
+ <framework name="1558" output_port_id="1558" />
1413
+ <IR name="1558" output_port_id="2" />
1414
+ </map>
1415
+ <map>
1416
+ <framework name="1567" output_port_id="1567" />
1417
+ <IR name="1567" output_port_id="2" />
1418
+ </map>
1419
+ <map>
1420
+ <framework name="1568" output_port_id="1568" />
1421
+ <IR name="1568" output_port_id="2" />
1422
+ </map>
1423
+ <map>
1424
+ <framework name="1569" output_port_id="1569" />
1425
+ <IR name="1569" output_port_id="2" />
1426
+ </map>
1427
+ <map>
1428
+ <framework name="1571" output_port_id="1571" />
1429
+ <IR name="1571" output_port_id="2" />
1430
+ </map>
1431
+ <map>
1432
+ <framework name="1572" output_port_id="1572" />
1433
+ <IR name="1572" output_port_id="2" />
1434
+ </map>
1435
+ <map>
1436
+ <framework name="1621" output_port_id="1621" />
1437
+ <IR name="1621" output_port_id="2" />
1438
+ </map>
1439
+ <map>
1440
+ <framework name="1622" output_port_id="1622" />
1441
+ <IR name="1622" output_port_id="2" />
1442
+ </map>
1443
+ <map>
1444
+ <framework name="1574" output_port_id="1574" />
1445
+ <IR name="1574" output_port_id="2" />
1446
+ </map>
1447
+ <map>
1448
+ <framework name="1575" output_port_id="1575" />
1449
+ <IR name="1575" output_port_id="2" />
1450
+ </map>
1451
+ <map>
1452
+ <framework name="1589" output_port_id="1589" />
1453
+ <IR name="1589" output_port_id="2" />
1454
+ </map>
1455
+ <map>
1456
+ <framework name="1623" output_port_id="1623" />
1457
+ <IR name="1623" output_port_id="2" />
1458
+ </map>
1459
+ <map>
1460
+ <framework name="1626" output_port_id="1626" />
1461
+ <IR name="1626" output_port_id="2" />
1462
+ </map>
1463
+ <map>
1464
+ <framework name="1627" output_port_id="1627" />
1465
+ <IR name="1627" output_port_id="2" />
1466
+ </map>
1467
+ <map>
1468
+ <framework name="1628" output_port_id="1628" />
1469
+ <IR name="1628" output_port_id="2" />
1470
+ </map>
1471
+ <map>
1472
+ <framework name="1591" output_port_id="1591" />
1473
+ <IR name="1591" output_port_id="2" />
1474
+ </map>
1475
+ <map>
1476
+ <framework name="1592" output_port_id="1592" />
1477
+ <IR name="1592" output_port_id="2" />
1478
+ </map>
1479
+ <map>
1480
+ <framework name="1606" output_port_id="1606" />
1481
+ <IR name="1606" output_port_id="2" />
1482
+ </map>
1483
+ <map>
1484
+ <framework name="1607" output_port_id="1607" />
1485
+ <IR name="1607" output_port_id="2" />
1486
+ </map>
1487
+ <map>
1488
+ <framework name="1629" output_port_id="1629" />
1489
+ <IR name="1629" output_port_id="2" />
1490
+ </map>
1491
+ <map>
1492
+ <framework name="1630" output_port_id="1630" />
1493
+ <IR name="1630" output_port_id="2" />
1494
+ </map>
1495
+ <map>
1496
+ <framework name="1642" output_port_id="1642" />
1497
+ <IR name="1642" output_port_id="2" />
1498
+ </map>
1499
+ <map>
1500
+ <framework name="1644" output_port_id="1644" />
1501
+ <IR name="1644" output_port_id="2" />
1502
+ </map>
1503
+ <map>
1504
+ <framework name="1645" output_port_id="1645" />
1505
+ <IR name="1645" output_port_id="2" />
1506
+ </map>
1507
+ <map>
1508
+ <framework name="1646" output_port_id="1646" />
1509
+ <IR name="1646" output_port_id="2" />
1510
+ </map>
1511
+ <map>
1512
+ <framework name="1655" output_port_id="1655" />
1513
+ <IR name="1655" output_port_id="2" />
1514
+ </map>
1515
+ <map>
1516
+ <framework name="1656" output_port_id="1656" />
1517
+ <IR name="1656" output_port_id="2" />
1518
+ </map>
1519
+ <map>
1520
+ <framework name="1657" output_port_id="1657" />
1521
+ <IR name="1657" output_port_id="2" />
1522
+ </map>
1523
+ <map>
1524
+ <framework name="1659" output_port_id="1659" />
1525
+ <IR name="1659" output_port_id="2" />
1526
+ </map>
1527
+ <map>
1528
+ <framework name="1660" output_port_id="1660" />
1529
+ <IR name="1660" output_port_id="2" />
1530
+ </map>
1531
+ <map>
1532
+ <framework name="1668" output_port_id="1668" />
1533
+ <IR name="1668" output_port_id="1" />
1534
+ </map>
1535
+ <map>
1536
+ <framework name="1670" output_port_id="1670" />
1537
+ <IR name="1670" output_port_id="2" />
1538
+ </map>
1539
+ <map>
1540
+ <framework name="1671" output_port_id="1671" />
1541
+ <IR name="1671" output_port_id="2" />
1542
+ </map>
1543
+ <map>
1544
+ <framework name="1672" output_port_id="1672" />
1545
+ <IR name="1672" output_port_id="2" />
1546
+ </map>
1547
+ <map>
1548
+ <framework name="1681" output_port_id="1681" />
1549
+ <IR name="1681" output_port_id="2" />
1550
+ </map>
1551
+ <map>
1552
+ <framework name="1682" output_port_id="1682" />
1553
+ <IR name="1682" output_port_id="2" />
1554
+ </map>
1555
+ <map>
1556
+ <framework name="1683" output_port_id="1683" />
1557
+ <IR name="1683" output_port_id="2" />
1558
+ </map>
1559
+ <map>
1560
+ <framework name="1685" output_port_id="1685" />
1561
+ <IR name="1685" output_port_id="2" />
1562
+ </map>
1563
+ <map>
1564
+ <framework name="1686" output_port_id="1686" />
1565
+ <IR name="1686" output_port_id="2" />
1566
+ </map>
1567
+ <map>
1568
+ <framework name="1735" output_port_id="1735" />
1569
+ <IR name="1735" output_port_id="2" />
1570
+ </map>
1571
+ <map>
1572
+ <framework name="1736" output_port_id="1736" />
1573
+ <IR name="1736" output_port_id="2" />
1574
+ </map>
1575
+ <map>
1576
+ <framework name="1688" output_port_id="1688" />
1577
+ <IR name="1688" output_port_id="2" />
1578
+ </map>
1579
+ <map>
1580
+ <framework name="1689" output_port_id="1689" />
1581
+ <IR name="1689" output_port_id="2" />
1582
+ </map>
1583
+ <map>
1584
+ <framework name="1703" output_port_id="1703" />
1585
+ <IR name="1703" output_port_id="2" />
1586
+ </map>
1587
+ <map>
1588
+ <framework name="1737" output_port_id="1737" />
1589
+ <IR name="1737" output_port_id="2" />
1590
+ </map>
1591
+ <map>
1592
+ <framework name="1740" output_port_id="1740" />
1593
+ <IR name="1740" output_port_id="2" />
1594
+ </map>
1595
+ <map>
1596
+ <framework name="1741" output_port_id="1741" />
1597
+ <IR name="1741" output_port_id="2" />
1598
+ </map>
1599
+ <map>
1600
+ <framework name="1742" output_port_id="1742" />
1601
+ <IR name="1742" output_port_id="2" />
1602
+ </map>
1603
+ <map>
1604
+ <framework name="1705" output_port_id="1705" />
1605
+ <IR name="1705" output_port_id="2" />
1606
+ </map>
1607
+ <map>
1608
+ <framework name="1706" output_port_id="1706" />
1609
+ <IR name="1706" output_port_id="2" />
1610
+ </map>
1611
+ <map>
1612
+ <framework name="1720" output_port_id="1720" />
1613
+ <IR name="1720" output_port_id="2" />
1614
+ </map>
1615
+ <map>
1616
+ <framework name="1721" output_port_id="1721" />
1617
+ <IR name="1721" output_port_id="2" />
1618
+ </map>
1619
+ <map>
1620
+ <framework name="1743" output_port_id="1743" />
1621
+ <IR name="1743" output_port_id="2" />
1622
+ </map>
1623
+ <map>
1624
+ <framework name="1744" output_port_id="1744" />
1625
+ <IR name="1744" output_port_id="2" />
1626
+ </map>
1627
+ <map>
1628
+ <framework name="1756" output_port_id="1756" />
1629
+ <IR name="1756" output_port_id="2" />
1630
+ </map>
1631
+ <map>
1632
+ <framework name="1758" output_port_id="1758" />
1633
+ <IR name="1758" output_port_id="2" />
1634
+ </map>
1635
+ <map>
1636
+ <framework name="1759" output_port_id="1759" />
1637
+ <IR name="1759" output_port_id="2" />
1638
+ </map>
1639
+ <map>
1640
+ <framework name="1760" output_port_id="1760" />
1641
+ <IR name="1760" output_port_id="2" />
1642
+ </map>
1643
+ <map>
1644
+ <framework name="1769" output_port_id="1769" />
1645
+ <IR name="1769" output_port_id="2" />
1646
+ </map>
1647
+ <map>
1648
+ <framework name="1770" output_port_id="1770" />
1649
+ <IR name="1770" output_port_id="2" />
1650
+ </map>
1651
+ <map>
1652
+ <framework name="1771" output_port_id="1771" />
1653
+ <IR name="1771" output_port_id="2" />
1654
+ </map>
1655
+ <map>
1656
+ <framework name="1773" output_port_id="1773" />
1657
+ <IR name="1773" output_port_id="2" />
1658
+ </map>
1659
+ <map>
1660
+ <framework name="1774" output_port_id="1774" />
1661
+ <IR name="1774" output_port_id="2" />
1662
+ </map>
1663
+ <map>
1664
+ <framework name="1782" output_port_id="1782" />
1665
+ <IR name="1782" output_port_id="1" />
1666
+ </map>
1667
+ <map>
1668
+ <framework name="1784" output_port_id="1784" />
1669
+ <IR name="1784" output_port_id="2" />
1670
+ </map>
1671
+ <map>
1672
+ <framework name="1785" output_port_id="1785" />
1673
+ <IR name="1785" output_port_id="2" />
1674
+ </map>
1675
+ <map>
1676
+ <framework name="1786" output_port_id="1786" />
1677
+ <IR name="1786" output_port_id="2" />
1678
+ </map>
1679
+ <map>
1680
+ <framework name="1795" output_port_id="1795" />
1681
+ <IR name="1795" output_port_id="2" />
1682
+ </map>
1683
+ <map>
1684
+ <framework name="1796" output_port_id="1796" />
1685
+ <IR name="1796" output_port_id="2" />
1686
+ </map>
1687
+ <map>
1688
+ <framework name="1797" output_port_id="1797" />
1689
+ <IR name="1797" output_port_id="2" />
1690
+ </map>
1691
+ <map>
1692
+ <framework name="1799" output_port_id="1799" />
1693
+ <IR name="1799" output_port_id="2" />
1694
+ </map>
1695
+ <map>
1696
+ <framework name="1800" output_port_id="1800" />
1697
+ <IR name="1800" output_port_id="2" />
1698
+ </map>
1699
+ <map>
1700
+ <framework name="1849" output_port_id="1849" />
1701
+ <IR name="1849" output_port_id="2" />
1702
+ </map>
1703
+ <map>
1704
+ <framework name="1850" output_port_id="1850" />
1705
+ <IR name="1850" output_port_id="2" />
1706
+ </map>
1707
+ <map>
1708
+ <framework name="1802" output_port_id="1802" />
1709
+ <IR name="1802" output_port_id="2" />
1710
+ </map>
1711
+ <map>
1712
+ <framework name="1803" output_port_id="1803" />
1713
+ <IR name="1803" output_port_id="2" />
1714
+ </map>
1715
+ <map>
1716
+ <framework name="1817" output_port_id="1817" />
1717
+ <IR name="1817" output_port_id="2" />
1718
+ </map>
1719
+ <map>
1720
+ <framework name="1851" output_port_id="1851" />
1721
+ <IR name="1851" output_port_id="2" />
1722
+ </map>
1723
+ <map>
1724
+ <framework name="1854" output_port_id="1854" />
1725
+ <IR name="1854" output_port_id="2" />
1726
+ </map>
1727
+ <map>
1728
+ <framework name="1855" output_port_id="1855" />
1729
+ <IR name="1855" output_port_id="2" />
1730
+ </map>
1731
+ <map>
1732
+ <framework name="1856" output_port_id="1856" />
1733
+ <IR name="1856" output_port_id="2" />
1734
+ </map>
1735
+ <map>
1736
+ <framework name="1819" output_port_id="1819" />
1737
+ <IR name="1819" output_port_id="2" />
1738
+ </map>
1739
+ <map>
1740
+ <framework name="1820" output_port_id="1820" />
1741
+ <IR name="1820" output_port_id="2" />
1742
+ </map>
1743
+ <map>
1744
+ <framework name="1834" output_port_id="1834" />
1745
+ <IR name="1834" output_port_id="2" />
1746
+ </map>
1747
+ <map>
1748
+ <framework name="1835" output_port_id="1835" />
1749
+ <IR name="1835" output_port_id="2" />
1750
+ </map>
1751
+ <map>
1752
+ <framework name="1857" output_port_id="1857" />
1753
+ <IR name="1857" output_port_id="2" />
1754
+ </map>
1755
+ <map>
1756
+ <framework name="1858" output_port_id="1858" />
1757
+ <IR name="1858" output_port_id="2" />
1758
+ </map>
1759
+ <map>
1760
+ <framework name="1870" output_port_id="1870" />
1761
+ <IR name="1870" output_port_id="2" />
1762
+ </map>
1763
+ <map>
1764
+ <framework name="1872" output_port_id="1872" />
1765
+ <IR name="1872" output_port_id="2" />
1766
+ </map>
1767
+ <map>
1768
+ <framework name="1873" output_port_id="1873" />
1769
+ <IR name="1873" output_port_id="2" />
1770
+ </map>
1771
+ <map>
1772
+ <framework name="1874" output_port_id="1874" />
1773
+ <IR name="1874" output_port_id="2" />
1774
+ </map>
1775
+ <map>
1776
+ <framework name="1883" output_port_id="1883" />
1777
+ <IR name="1883" output_port_id="2" />
1778
+ </map>
1779
+ <map>
1780
+ <framework name="1884" output_port_id="1884" />
1781
+ <IR name="1884" output_port_id="2" />
1782
+ </map>
1783
+ <map>
1784
+ <framework name="1885" output_port_id="1885" />
1785
+ <IR name="1885" output_port_id="2" />
1786
+ </map>
1787
+ <map>
1788
+ <framework name="1887" output_port_id="1887" />
1789
+ <IR name="1887" output_port_id="2" />
1790
+ </map>
1791
+ <map>
1792
+ <framework name="1888" output_port_id="1888" />
1793
+ <IR name="1888" output_port_id="2" />
1794
+ </map>
1795
+ <map>
1796
+ <framework name="1896" output_port_id="1896" />
1797
+ <IR name="1896" output_port_id="1" />
1798
+ </map>
1799
+ <map>
1800
+ <framework name="1898" output_port_id="1898" />
1801
+ <IR name="1898" output_port_id="2" />
1802
+ </map>
1803
+ <map>
1804
+ <framework name="1899" output_port_id="1899" />
1805
+ <IR name="1899" output_port_id="2" />
1806
+ </map>
1807
+ <map>
1808
+ <framework name="1900" output_port_id="1900" />
1809
+ <IR name="1900" output_port_id="2" />
1810
+ </map>
1811
+ <map>
1812
+ <framework name="1909" output_port_id="1909" />
1813
+ <IR name="1909" output_port_id="2" />
1814
+ </map>
1815
+ <map>
1816
+ <framework name="1910" output_port_id="1910" />
1817
+ <IR name="1910" output_port_id="2" />
1818
+ </map>
1819
+ <map>
1820
+ <framework name="1911" output_port_id="1911" />
1821
+ <IR name="1911" output_port_id="2" />
1822
+ </map>
1823
+ <map>
1824
+ <framework name="1913" output_port_id="1913" />
1825
+ <IR name="1913" output_port_id="2" />
1826
+ </map>
1827
+ <map>
1828
+ <framework name="1914" output_port_id="1914" />
1829
+ <IR name="1914" output_port_id="2" />
1830
+ </map>
1831
+ <map>
1832
+ <framework name="1963" output_port_id="1963" />
1833
+ <IR name="1963" output_port_id="2" />
1834
+ </map>
1835
+ <map>
1836
+ <framework name="1964" output_port_id="1964" />
1837
+ <IR name="1964" output_port_id="2" />
1838
+ </map>
1839
+ <map>
1840
+ <framework name="1916" output_port_id="1916" />
1841
+ <IR name="1916" output_port_id="2" />
1842
+ </map>
1843
+ <map>
1844
+ <framework name="1917" output_port_id="1917" />
1845
+ <IR name="1917" output_port_id="2" />
1846
+ </map>
1847
+ <map>
1848
+ <framework name="1931" output_port_id="1931" />
1849
+ <IR name="1931" output_port_id="2" />
1850
+ </map>
1851
+ <map>
1852
+ <framework name="1965" output_port_id="1965" />
1853
+ <IR name="1965" output_port_id="2" />
1854
+ </map>
1855
+ <map>
1856
+ <framework name="1968" output_port_id="1968" />
1857
+ <IR name="1968" output_port_id="2" />
1858
+ </map>
1859
+ <map>
1860
+ <framework name="1969" output_port_id="1969" />
1861
+ <IR name="1969" output_port_id="2" />
1862
+ </map>
1863
+ <map>
1864
+ <framework name="1970" output_port_id="1970" />
1865
+ <IR name="1970" output_port_id="2" />
1866
+ </map>
1867
+ <map>
1868
+ <framework name="1933" output_port_id="1933" />
1869
+ <IR name="1933" output_port_id="2" />
1870
+ </map>
1871
+ <map>
1872
+ <framework name="1934" output_port_id="1934" />
1873
+ <IR name="1934" output_port_id="2" />
1874
+ </map>
1875
+ <map>
1876
+ <framework name="1948" output_port_id="1948" />
1877
+ <IR name="1948" output_port_id="2" />
1878
+ </map>
1879
+ <map>
1880
+ <framework name="1949" output_port_id="1949" />
1881
+ <IR name="1949" output_port_id="2" />
1882
+ </map>
1883
+ <map>
1884
+ <framework name="1971" output_port_id="1971" />
1885
+ <IR name="1971" output_port_id="2" />
1886
+ </map>
1887
+ <map>
1888
+ <framework name="1972" output_port_id="1972" />
1889
+ <IR name="1972" output_port_id="2" />
1890
+ </map>
1891
+ <map>
1892
+ <framework name="1984" output_port_id="1984" />
1893
+ <IR name="1984" output_port_id="2" />
1894
+ </map>
1895
+ <map>
1896
+ <framework name="1986" output_port_id="1986" />
1897
+ <IR name="1986" output_port_id="2" />
1898
+ </map>
1899
+ <map>
1900
+ <framework name="1987" output_port_id="1987" />
1901
+ <IR name="1987" output_port_id="2" />
1902
+ </map>
1903
+ <map>
1904
+ <framework name="1988" output_port_id="1988" />
1905
+ <IR name="1988" output_port_id="2" />
1906
+ </map>
1907
+ <map>
1908
+ <framework name="1997" output_port_id="1997" />
1909
+ <IR name="1997" output_port_id="2" />
1910
+ </map>
1911
+ <map>
1912
+ <framework name="1998" output_port_id="1998" />
1913
+ <IR name="1998" output_port_id="2" />
1914
+ </map>
1915
+ <map>
1916
+ <framework name="1999" output_port_id="1999" />
1917
+ <IR name="1999" output_port_id="2" />
1918
+ </map>
1919
+ <map>
1920
+ <framework name="2001" output_port_id="2001" />
1921
+ <IR name="2001" output_port_id="2" />
1922
+ </map>
1923
+ <map>
1924
+ <framework name="2002" output_port_id="2002" />
1925
+ <IR name="2002" output_port_id="2" />
1926
+ </map>
1927
+ <map>
1928
+ <framework name="2010" output_port_id="2010" />
1929
+ <IR name="2010" output_port_id="1" />
1930
+ </map>
1931
+ <map>
1932
+ <framework name="2012" output_port_id="2012" />
1933
+ <IR name="2012" output_port_id="2" />
1934
+ </map>
1935
+ <map>
1936
+ <framework name="2013" output_port_id="2013" />
1937
+ <IR name="2013" output_port_id="2" />
1938
+ </map>
1939
+ <map>
1940
+ <framework name="2014" output_port_id="2014" />
1941
+ <IR name="2014" output_port_id="2" />
1942
+ </map>
1943
+ <map>
1944
+ <framework name="2023" output_port_id="2023" />
1945
+ <IR name="2023" output_port_id="2" />
1946
+ </map>
1947
+ <map>
1948
+ <framework name="2024" output_port_id="2024" />
1949
+ <IR name="2024" output_port_id="2" />
1950
+ </map>
1951
+ <map>
1952
+ <framework name="2025" output_port_id="2025" />
1953
+ <IR name="2025" output_port_id="2" />
1954
+ </map>
1955
+ <map>
1956
+ <framework name="2027" output_port_id="2027" />
1957
+ <IR name="2027" output_port_id="2" />
1958
+ </map>
1959
+ <map>
1960
+ <framework name="2028" output_port_id="2028" />
1961
+ <IR name="2028" output_port_id="2" />
1962
+ </map>
1963
+ <map>
1964
+ <framework name="2077" output_port_id="2077" />
1965
+ <IR name="2077" output_port_id="2" />
1966
+ </map>
1967
+ <map>
1968
+ <framework name="2078" output_port_id="2078" />
1969
+ <IR name="2078" output_port_id="2" />
1970
+ </map>
1971
+ <map>
1972
+ <framework name="2030" output_port_id="2030" />
1973
+ <IR name="2030" output_port_id="2" />
1974
+ </map>
1975
+ <map>
1976
+ <framework name="2031" output_port_id="2031" />
1977
+ <IR name="2031" output_port_id="2" />
1978
+ </map>
1979
+ <map>
1980
+ <framework name="2045" output_port_id="2045" />
1981
+ <IR name="2045" output_port_id="2" />
1982
+ </map>
1983
+ <map>
1984
+ <framework name="2079" output_port_id="2079" />
1985
+ <IR name="2079" output_port_id="2" />
1986
+ </map>
1987
+ <map>
1988
+ <framework name="2082" output_port_id="2082" />
1989
+ <IR name="2082" output_port_id="2" />
1990
+ </map>
1991
+ <map>
1992
+ <framework name="2083" output_port_id="2083" />
1993
+ <IR name="2083" output_port_id="2" />
1994
+ </map>
1995
+ <map>
1996
+ <framework name="2084" output_port_id="2084" />
1997
+ <IR name="2084" output_port_id="2" />
1998
+ </map>
1999
+ <map>
2000
+ <framework name="2047" output_port_id="2047" />
2001
+ <IR name="2047" output_port_id="2" />
2002
+ </map>
2003
+ <map>
2004
+ <framework name="2048" output_port_id="2048" />
2005
+ <IR name="2048" output_port_id="2" />
2006
+ </map>
2007
+ <map>
2008
+ <framework name="2062" output_port_id="2062" />
2009
+ <IR name="2062" output_port_id="2" />
2010
+ </map>
2011
+ <map>
2012
+ <framework name="2063" output_port_id="2063" />
2013
+ <IR name="2063" output_port_id="2" />
2014
+ </map>
2015
+ <map>
2016
+ <framework name="2085" output_port_id="2085" />
2017
+ <IR name="2085" output_port_id="2" />
2018
+ </map>
2019
+ <map>
2020
+ <framework name="2086" output_port_id="2086" />
2021
+ <IR name="2086" output_port_id="2" />
2022
+ </map>
2023
+ <map>
2024
+ <framework name="2098" output_port_id="2098" />
2025
+ <IR name="2098" output_port_id="2" />
2026
+ </map>
2027
+ <map>
2028
+ <framework name="2100" output_port_id="2100" />
2029
+ <IR name="2100" output_port_id="2" />
2030
+ </map>
2031
+ <map>
2032
+ <framework name="2101" output_port_id="2101" />
2033
+ <IR name="2101" output_port_id="2" />
2034
+ </map>
2035
+ <map>
2036
+ <framework name="2102" output_port_id="2102" />
2037
+ <IR name="2102" output_port_id="2" />
2038
+ </map>
2039
+ <map>
2040
+ <framework name="2111" output_port_id="2111" />
2041
+ <IR name="2111" output_port_id="2" />
2042
+ </map>
2043
+ <map>
2044
+ <framework name="2112" output_port_id="2112" />
2045
+ <IR name="2112" output_port_id="2" />
2046
+ </map>
2047
+ <map>
2048
+ <framework name="2113" output_port_id="2113" />
2049
+ <IR name="2113" output_port_id="2" />
2050
+ </map>
2051
+ <map>
2052
+ <framework name="2115" output_port_id="2115" />
2053
+ <IR name="2115" output_port_id="2" />
2054
+ </map>
2055
+ <map>
2056
+ <framework name="2116" output_port_id="2116" />
2057
+ <IR name="2116" output_port_id="2" />
2058
+ </map>
2059
+ <map>
2060
+ <framework name="2124" output_port_id="2124" />
2061
+ <IR name="2124" output_port_id="1" />
2062
+ </map>
2063
+ <map>
2064
+ <framework name="2126" output_port_id="2126" />
2065
+ <IR name="2126" output_port_id="2" />
2066
+ </map>
2067
+ <map>
2068
+ <framework name="2127" output_port_id="2127" />
2069
+ <IR name="2127" output_port_id="2" />
2070
+ </map>
2071
+ <map>
2072
+ <framework name="2128" output_port_id="2128" />
2073
+ <IR name="2128" output_port_id="2" />
2074
+ </map>
2075
+ <map>
2076
+ <framework name="2137" output_port_id="2137" />
2077
+ <IR name="2137" output_port_id="2" />
2078
+ </map>
2079
+ <map>
2080
+ <framework name="2138" output_port_id="2138" />
2081
+ <IR name="2138" output_port_id="2" />
2082
+ </map>
2083
+ <map>
2084
+ <framework name="2139" output_port_id="2139" />
2085
+ <IR name="2139" output_port_id="2" />
2086
+ </map>
2087
+ <map>
2088
+ <framework name="2141" output_port_id="2141" />
2089
+ <IR name="2141" output_port_id="2" />
2090
+ </map>
2091
+ <map>
2092
+ <framework name="2142" output_port_id="2142" />
2093
+ <IR name="2142" output_port_id="2" />
2094
+ </map>
2095
+ <map>
2096
+ <framework name="2191" output_port_id="2191" />
2097
+ <IR name="2191" output_port_id="2" />
2098
+ </map>
2099
+ <map>
2100
+ <framework name="2192" output_port_id="2192" />
2101
+ <IR name="2192" output_port_id="2" />
2102
+ </map>
2103
+ <map>
2104
+ <framework name="2144" output_port_id="2144" />
2105
+ <IR name="2144" output_port_id="2" />
2106
+ </map>
2107
+ <map>
2108
+ <framework name="2145" output_port_id="2145" />
2109
+ <IR name="2145" output_port_id="2" />
2110
+ </map>
2111
+ <map>
2112
+ <framework name="2159" output_port_id="2159" />
2113
+ <IR name="2159" output_port_id="2" />
2114
+ </map>
2115
+ <map>
2116
+ <framework name="2193" output_port_id="2193" />
2117
+ <IR name="2193" output_port_id="2" />
2118
+ </map>
2119
+ <map>
2120
+ <framework name="2196" output_port_id="2196" />
2121
+ <IR name="2196" output_port_id="2" />
2122
+ </map>
2123
+ <map>
2124
+ <framework name="2197" output_port_id="2197" />
2125
+ <IR name="2197" output_port_id="2" />
2126
+ </map>
2127
+ <map>
2128
+ <framework name="2198" output_port_id="2198" />
2129
+ <IR name="2198" output_port_id="2" />
2130
+ </map>
2131
+ <map>
2132
+ <framework name="2161" output_port_id="2161" />
2133
+ <IR name="2161" output_port_id="2" />
2134
+ </map>
2135
+ <map>
2136
+ <framework name="2162" output_port_id="2162" />
2137
+ <IR name="2162" output_port_id="2" />
2138
+ </map>
2139
+ <map>
2140
+ <framework name="2176" output_port_id="2176" />
2141
+ <IR name="2176" output_port_id="2" />
2142
+ </map>
2143
+ <map>
2144
+ <framework name="2177" output_port_id="2177" />
2145
+ <IR name="2177" output_port_id="2" />
2146
+ </map>
2147
+ <map>
2148
+ <framework name="2199" output_port_id="2199" />
2149
+ <IR name="2199" output_port_id="2" />
2150
+ </map>
2151
+ <map>
2152
+ <framework name="2200" output_port_id="2200" />
2153
+ <IR name="2200" output_port_id="2" />
2154
+ </map>
2155
+ <map>
2156
+ <framework name="2212" output_port_id="2212" />
2157
+ <IR name="2212" output_port_id="2" />
2158
+ </map>
2159
+ <map>
2160
+ <framework name="2214" output_port_id="2214" />
2161
+ <IR name="2214" output_port_id="2" />
2162
+ </map>
2163
+ <map>
2164
+ <framework name="2215" output_port_id="2215" />
2165
+ <IR name="2215" output_port_id="2" />
2166
+ </map>
2167
+ <map>
2168
+ <framework name="2216" output_port_id="2216" />
2169
+ <IR name="2216" output_port_id="2" />
2170
+ </map>
2171
+ <map>
2172
+ <framework name="2225" output_port_id="2225" />
2173
+ <IR name="2225" output_port_id="2" />
2174
+ </map>
2175
+ <map>
2176
+ <framework name="2226" output_port_id="2226" />
2177
+ <IR name="2226" output_port_id="2" />
2178
+ </map>
2179
+ <map>
2180
+ <framework name="2227" output_port_id="2227" />
2181
+ <IR name="2227" output_port_id="2" />
2182
+ </map>
2183
+ <map>
2184
+ <framework name="2229" output_port_id="2229" />
2185
+ <IR name="2229" output_port_id="2" />
2186
+ </map>
2187
+ <map>
2188
+ <framework name="2230" output_port_id="2230" />
2189
+ <IR name="2230" output_port_id="2" />
2190
+ </map>
2191
+ <map>
2192
+ <framework name="2238" output_port_id="2238" />
2193
+ <IR name="2238" output_port_id="1" />
2194
+ </map>
2195
+ <map>
2196
+ <framework name="2240" output_port_id="2240" />
2197
+ <IR name="2240" output_port_id="2" />
2198
+ </map>
2199
+ <map>
2200
+ <framework name="2241" output_port_id="2241" />
2201
+ <IR name="2241" output_port_id="2" />
2202
+ </map>
2203
+ <map>
2204
+ <framework name="2242" output_port_id="2242" />
2205
+ <IR name="2242" output_port_id="2" />
2206
+ </map>
2207
+ <map>
2208
+ <framework name="2251" output_port_id="2251" />
2209
+ <IR name="2251" output_port_id="2" />
2210
+ </map>
2211
+ <map>
2212
+ <framework name="2252" output_port_id="2252" />
2213
+ <IR name="2252" output_port_id="2" />
2214
+ </map>
2215
+ <map>
2216
+ <framework name="2253" output_port_id="2253" />
2217
+ <IR name="2253" output_port_id="2" />
2218
+ </map>
2219
+ <map>
2220
+ <framework name="2255" output_port_id="2255" />
2221
+ <IR name="2255" output_port_id="2" />
2222
+ </map>
2223
+ <map>
2224
+ <framework name="2256" output_port_id="2256" />
2225
+ <IR name="2256" output_port_id="2" />
2226
+ </map>
2227
+ <map>
2228
+ <framework name="2305" output_port_id="2305" />
2229
+ <IR name="2305" output_port_id="2" />
2230
+ </map>
2231
+ <map>
2232
+ <framework name="2306" output_port_id="2306" />
2233
+ <IR name="2306" output_port_id="2" />
2234
+ </map>
2235
+ <map>
2236
+ <framework name="2258" output_port_id="2258" />
2237
+ <IR name="2258" output_port_id="2" />
2238
+ </map>
2239
+ <map>
2240
+ <framework name="2259" output_port_id="2259" />
2241
+ <IR name="2259" output_port_id="2" />
2242
+ </map>
2243
+ <map>
2244
+ <framework name="2273" output_port_id="2273" />
2245
+ <IR name="2273" output_port_id="2" />
2246
+ </map>
2247
+ <map>
2248
+ <framework name="2307" output_port_id="2307" />
2249
+ <IR name="2307" output_port_id="2" />
2250
+ </map>
2251
+ <map>
2252
+ <framework name="2310" output_port_id="2310" />
2253
+ <IR name="2310" output_port_id="2" />
2254
+ </map>
2255
+ <map>
2256
+ <framework name="2311" output_port_id="2311" />
2257
+ <IR name="2311" output_port_id="2" />
2258
+ </map>
2259
+ <map>
2260
+ <framework name="2312" output_port_id="2312" />
2261
+ <IR name="2312" output_port_id="2" />
2262
+ </map>
2263
+ <map>
2264
+ <framework name="2275" output_port_id="2275" />
2265
+ <IR name="2275" output_port_id="2" />
2266
+ </map>
2267
+ <map>
2268
+ <framework name="2276" output_port_id="2276" />
2269
+ <IR name="2276" output_port_id="2" />
2270
+ </map>
2271
+ <map>
2272
+ <framework name="2290" output_port_id="2290" />
2273
+ <IR name="2290" output_port_id="2" />
2274
+ </map>
2275
+ <map>
2276
+ <framework name="2291" output_port_id="2291" />
2277
+ <IR name="2291" output_port_id="2" />
2278
+ </map>
2279
+ <map>
2280
+ <framework name="2313" output_port_id="2313" />
2281
+ <IR name="2313" output_port_id="2" />
2282
+ </map>
2283
+ <map>
2284
+ <framework name="2314" output_port_id="2314" />
2285
+ <IR name="2314" output_port_id="2" />
2286
+ </map>
2287
+ <map>
2288
+ <framework name="2326" output_port_id="2326" />
2289
+ <IR name="2326" output_port_id="2" />
2290
+ </map>
2291
+ <map>
2292
+ <framework name="2328" output_port_id="2328" />
2293
+ <IR name="2328" output_port_id="2" />
2294
+ </map>
2295
+ <map>
2296
+ <framework name="2329" output_port_id="2329" />
2297
+ <IR name="2329" output_port_id="2" />
2298
+ </map>
2299
+ <map>
2300
+ <framework name="2330" output_port_id="2330" />
2301
+ <IR name="2330" output_port_id="2" />
2302
+ </map>
2303
+ <map>
2304
+ <framework name="2339" output_port_id="2339" />
2305
+ <IR name="2339" output_port_id="2" />
2306
+ </map>
2307
+ <map>
2308
+ <framework name="2340" output_port_id="2340" />
2309
+ <IR name="2340" output_port_id="2" />
2310
+ </map>
2311
+ <map>
2312
+ <framework name="2341" output_port_id="2341" />
2313
+ <IR name="2341" output_port_id="2" />
2314
+ </map>
2315
+ <map>
2316
+ <framework name="2343" output_port_id="2343" />
2317
+ <IR name="2343" output_port_id="2" />
2318
+ </map>
2319
+ <map>
2320
+ <framework name="2344" output_port_id="2344" />
2321
+ <IR name="2344" output_port_id="2" />
2322
+ </map>
2323
+ <map>
2324
+ <framework name="2352" output_port_id="2352" />
2325
+ <IR name="2352" output_port_id="1" />
2326
+ </map>
2327
+ <map>
2328
+ <framework name="2354" output_port_id="2354" />
2329
+ <IR name="2354" output_port_id="2" />
2330
+ </map>
2331
+ <map>
2332
+ <framework name="2355" output_port_id="2355" />
2333
+ <IR name="2355" output_port_id="2" />
2334
+ </map>
2335
+ <map>
2336
+ <framework name="2356" output_port_id="2356" />
2337
+ <IR name="2356" output_port_id="2" />
2338
+ </map>
2339
+ <map>
2340
+ <framework name="2365" output_port_id="2365" />
2341
+ <IR name="2365" output_port_id="2" />
2342
+ </map>
2343
+ <map>
2344
+ <framework name="2366" output_port_id="2366" />
2345
+ <IR name="2366" output_port_id="2" />
2346
+ </map>
2347
+ <map>
2348
+ <framework name="2367" output_port_id="2367" />
2349
+ <IR name="2367" output_port_id="2" />
2350
+ </map>
2351
+ <map>
2352
+ <framework name="2369" output_port_id="2369" />
2353
+ <IR name="2369" output_port_id="2" />
2354
+ </map>
2355
+ <map>
2356
+ <framework name="2370" output_port_id="2370" />
2357
+ <IR name="2370" output_port_id="2" />
2358
+ </map>
2359
+ <map>
2360
+ <framework name="2419" output_port_id="2419" />
2361
+ <IR name="2419" output_port_id="2" />
2362
+ </map>
2363
+ <map>
2364
+ <framework name="2420" output_port_id="2420" />
2365
+ <IR name="2420" output_port_id="2" />
2366
+ </map>
2367
+ <map>
2368
+ <framework name="2372" output_port_id="2372" />
2369
+ <IR name="2372" output_port_id="2" />
2370
+ </map>
2371
+ <map>
2372
+ <framework name="2373" output_port_id="2373" />
2373
+ <IR name="2373" output_port_id="2" />
2374
+ </map>
2375
+ <map>
2376
+ <framework name="2387" output_port_id="2387" />
2377
+ <IR name="2387" output_port_id="2" />
2378
+ </map>
2379
+ <map>
2380
+ <framework name="2421" output_port_id="2421" />
2381
+ <IR name="2421" output_port_id="2" />
2382
+ </map>
2383
+ <map>
2384
+ <framework name="2424" output_port_id="2424" />
2385
+ <IR name="2424" output_port_id="2" />
2386
+ </map>
2387
+ <map>
2388
+ <framework name="2425" output_port_id="2425" />
2389
+ <IR name="2425" output_port_id="2" />
2390
+ </map>
2391
+ <map>
2392
+ <framework name="2426" output_port_id="2426" />
2393
+ <IR name="2426" output_port_id="2" />
2394
+ </map>
2395
+ <map>
2396
+ <framework name="2389" output_port_id="2389" />
2397
+ <IR name="2389" output_port_id="2" />
2398
+ </map>
2399
+ <map>
2400
+ <framework name="2390" output_port_id="2390" />
2401
+ <IR name="2390" output_port_id="2" />
2402
+ </map>
2403
+ <map>
2404
+ <framework name="2404" output_port_id="2404" />
2405
+ <IR name="2404" output_port_id="2" />
2406
+ </map>
2407
+ <map>
2408
+ <framework name="2405" output_port_id="2405" />
2409
+ <IR name="2405" output_port_id="2" />
2410
+ </map>
2411
+ <map>
2412
+ <framework name="2427" output_port_id="2427" />
2413
+ <IR name="2427" output_port_id="2" />
2414
+ </map>
2415
+ <map>
2416
+ <framework name="2428" output_port_id="2428" />
2417
+ <IR name="2428" output_port_id="2" />
2418
+ </map>
2419
+ <map>
2420
+ <framework name="2440" output_port_id="2440" />
2421
+ <IR name="2440" output_port_id="2" />
2422
+ </map>
2423
+ <map>
2424
+ <framework name="2442" output_port_id="2442" />
2425
+ <IR name="2442" output_port_id="2" />
2426
+ </map>
2427
+ <map>
2428
+ <framework name="2443" output_port_id="2443" />
2429
+ <IR name="2443" output_port_id="2" />
2430
+ </map>
2431
+ <map>
2432
+ <framework name="2444" output_port_id="2444" />
2433
+ <IR name="2444" output_port_id="2" />
2434
+ </map>
2435
+ <map>
2436
+ <framework name="2453" output_port_id="2453" />
2437
+ <IR name="2453" output_port_id="2" />
2438
+ </map>
2439
+ <map>
2440
+ <framework name="2454" output_port_id="2454" />
2441
+ <IR name="2454" output_port_id="2" />
2442
+ </map>
2443
+ <map>
2444
+ <framework name="2455" output_port_id="2455" />
2445
+ <IR name="2455" output_port_id="2" />
2446
+ </map>
2447
+ <map>
2448
+ <framework name="2457" output_port_id="2457" />
2449
+ <IR name="2457" output_port_id="2" />
2450
+ </map>
2451
+ <map>
2452
+ <framework name="2458" output_port_id="2458" />
2453
+ <IR name="2458" output_port_id="2" />
2454
+ </map>
2455
+ <map>
2456
+ <framework name="2466" output_port_id="2466" />
2457
+ <IR name="2466" output_port_id="1" />
2458
+ </map>
2459
+ <map>
2460
+ <framework name="2468" output_port_id="2468" />
2461
+ <IR name="2468" output_port_id="2" />
2462
+ </map>
2463
+ <map>
2464
+ <framework name="2469" output_port_id="2469" />
2465
+ <IR name="2469" output_port_id="2" />
2466
+ </map>
2467
+ <map>
2468
+ <framework name="2470" output_port_id="2470" />
2469
+ <IR name="2470" output_port_id="2" />
2470
+ </map>
2471
+ <map>
2472
+ <framework name="2479" output_port_id="2479" />
2473
+ <IR name="2479" output_port_id="2" />
2474
+ </map>
2475
+ <map>
2476
+ <framework name="2480" output_port_id="2480" />
2477
+ <IR name="2480" output_port_id="2" />
2478
+ </map>
2479
+ <map>
2480
+ <framework name="2481" output_port_id="2481" />
2481
+ <IR name="2481" output_port_id="2" />
2482
+ </map>
2483
+ <map>
2484
+ <framework name="2483" output_port_id="2483" />
2485
+ <IR name="2483" output_port_id="2" />
2486
+ </map>
2487
+ <map>
2488
+ <framework name="2484" output_port_id="2484" />
2489
+ <IR name="2484" output_port_id="2" />
2490
+ </map>
2491
+ <map>
2492
+ <framework name="2533" output_port_id="2533" />
2493
+ <IR name="2533" output_port_id="2" />
2494
+ </map>
2495
+ <map>
2496
+ <framework name="2534" output_port_id="2534" />
2497
+ <IR name="2534" output_port_id="2" />
2498
+ </map>
2499
+ <map>
2500
+ <framework name="2486" output_port_id="2486" />
2501
+ <IR name="2486" output_port_id="2" />
2502
+ </map>
2503
+ <map>
2504
+ <framework name="2487" output_port_id="2487" />
2505
+ <IR name="2487" output_port_id="2" />
2506
+ </map>
2507
+ <map>
2508
+ <framework name="2501" output_port_id="2501" />
2509
+ <IR name="2501" output_port_id="2" />
2510
+ </map>
2511
+ <map>
2512
+ <framework name="2535" output_port_id="2535" />
2513
+ <IR name="2535" output_port_id="2" />
2514
+ </map>
2515
+ <map>
2516
+ <framework name="2538" output_port_id="2538" />
2517
+ <IR name="2538" output_port_id="2" />
2518
+ </map>
2519
+ <map>
2520
+ <framework name="2539" output_port_id="2539" />
2521
+ <IR name="2539" output_port_id="2" />
2522
+ </map>
2523
+ <map>
2524
+ <framework name="2540" output_port_id="2540" />
2525
+ <IR name="2540" output_port_id="2" />
2526
+ </map>
2527
+ <map>
2528
+ <framework name="2503" output_port_id="2503" />
2529
+ <IR name="2503" output_port_id="2" />
2530
+ </map>
2531
+ <map>
2532
+ <framework name="2504" output_port_id="2504" />
2533
+ <IR name="2504" output_port_id="2" />
2534
+ </map>
2535
+ <map>
2536
+ <framework name="2518" output_port_id="2518" />
2537
+ <IR name="2518" output_port_id="2" />
2538
+ </map>
2539
+ <map>
2540
+ <framework name="2519" output_port_id="2519" />
2541
+ <IR name="2519" output_port_id="2" />
2542
+ </map>
2543
+ <map>
2544
+ <framework name="2541" output_port_id="2541" />
2545
+ <IR name="2541" output_port_id="2" />
2546
+ </map>
2547
+ <map>
2548
+ <framework name="2542" output_port_id="2542" />
2549
+ <IR name="2542" output_port_id="2" />
2550
+ </map>
2551
+ <map>
2552
+ <framework name="2554" output_port_id="2554" />
2553
+ <IR name="2554" output_port_id="2" />
2554
+ </map>
2555
+ <map>
2556
+ <framework name="2556" output_port_id="2556" />
2557
+ <IR name="2556" output_port_id="2" />
2558
+ </map>
2559
+ <map>
2560
+ <framework name="2557" output_port_id="2557" />
2561
+ <IR name="2557" output_port_id="2" />
2562
+ </map>
2563
+ <map>
2564
+ <framework name="2558" output_port_id="2558" />
2565
+ <IR name="2558" output_port_id="2" />
2566
+ </map>
2567
+ <map>
2568
+ <framework name="2567" output_port_id="2567" />
2569
+ <IR name="2567" output_port_id="2" />
2570
+ </map>
2571
+ <map>
2572
+ <framework name="2568" output_port_id="2568" />
2573
+ <IR name="2568" output_port_id="2" />
2574
+ </map>
2575
+ <map>
2576
+ <framework name="2569" output_port_id="2569" />
2577
+ <IR name="2569" output_port_id="2" />
2578
+ </map>
2579
+ <map>
2580
+ <framework name="2571" output_port_id="2571" />
2581
+ <IR name="2571" output_port_id="2" />
2582
+ </map>
2583
+ <map>
2584
+ <framework name="2572" output_port_id="2572" />
2585
+ <IR name="2572" output_port_id="2" />
2586
+ </map>
2587
+ <map>
2588
+ <framework name="2580" output_port_id="2580" />
2589
+ <IR name="2580" output_port_id="1" />
2590
+ </map>
2591
+ <map>
2592
+ <framework name="2582" output_port_id="2582" />
2593
+ <IR name="2582" output_port_id="2" />
2594
+ </map>
2595
+ <map>
2596
+ <framework name="2583" output_port_id="2583" />
2597
+ <IR name="2583" output_port_id="2" />
2598
+ </map>
2599
+ <map>
2600
+ <framework name="2584" output_port_id="2584" />
2601
+ <IR name="2584" output_port_id="2" />
2602
+ </map>
2603
+ <map>
2604
+ <framework name="2593" output_port_id="2593" />
2605
+ <IR name="2593" output_port_id="2" />
2606
+ </map>
2607
+ <map>
2608
+ <framework name="2594" output_port_id="2594" />
2609
+ <IR name="2594" output_port_id="2" />
2610
+ </map>
2611
+ <map>
2612
+ <framework name="2595" output_port_id="2595" />
2613
+ <IR name="2595" output_port_id="2" />
2614
+ </map>
2615
+ <map>
2616
+ <framework name="2597" output_port_id="2597" />
2617
+ <IR name="2597" output_port_id="2" />
2618
+ </map>
2619
+ <map>
2620
+ <framework name="2598" output_port_id="2598" />
2621
+ <IR name="2598" output_port_id="2" />
2622
+ </map>
2623
+ <map>
2624
+ <framework name="2647" output_port_id="2647" />
2625
+ <IR name="2647" output_port_id="2" />
2626
+ </map>
2627
+ <map>
2628
+ <framework name="2648" output_port_id="2648" />
2629
+ <IR name="2648" output_port_id="2" />
2630
+ </map>
2631
+ <map>
2632
+ <framework name="2600" output_port_id="2600" />
2633
+ <IR name="2600" output_port_id="2" />
2634
+ </map>
2635
+ <map>
2636
+ <framework name="2601" output_port_id="2601" />
2637
+ <IR name="2601" output_port_id="2" />
2638
+ </map>
2639
+ <map>
2640
+ <framework name="2615" output_port_id="2615" />
2641
+ <IR name="2615" output_port_id="2" />
2642
+ </map>
2643
+ <map>
2644
+ <framework name="2649" output_port_id="2649" />
2645
+ <IR name="2649" output_port_id="2" />
2646
+ </map>
2647
+ <map>
2648
+ <framework name="2652" output_port_id="2652" />
2649
+ <IR name="2652" output_port_id="2" />
2650
+ </map>
2651
+ <map>
2652
+ <framework name="2653" output_port_id="2653" />
2653
+ <IR name="2653" output_port_id="2" />
2654
+ </map>
2655
+ <map>
2656
+ <framework name="2654" output_port_id="2654" />
2657
+ <IR name="2654" output_port_id="2" />
2658
+ </map>
2659
+ <map>
2660
+ <framework name="2617" output_port_id="2617" />
2661
+ <IR name="2617" output_port_id="2" />
2662
+ </map>
2663
+ <map>
2664
+ <framework name="2618" output_port_id="2618" />
2665
+ <IR name="2618" output_port_id="2" />
2666
+ </map>
2667
+ <map>
2668
+ <framework name="2632" output_port_id="2632" />
2669
+ <IR name="2632" output_port_id="2" />
2670
+ </map>
2671
+ <map>
2672
+ <framework name="2633" output_port_id="2633" />
2673
+ <IR name="2633" output_port_id="2" />
2674
+ </map>
2675
+ <map>
2676
+ <framework name="2655" output_port_id="2655" />
2677
+ <IR name="2655" output_port_id="2" />
2678
+ </map>
2679
+ <map>
2680
+ <framework name="2656" output_port_id="2656" />
2681
+ <IR name="2656" output_port_id="2" />
2682
+ </map>
2683
+ <map>
2684
+ <framework name="2668" output_port_id="2668" />
2685
+ <IR name="2668" output_port_id="2" />
2686
+ </map>
2687
+ <map>
2688
+ <framework name="2670" output_port_id="2670" />
2689
+ <IR name="2670" output_port_id="2" />
2690
+ </map>
2691
+ <map>
2692
+ <framework name="2671" output_port_id="2671" />
2693
+ <IR name="2671" output_port_id="2" />
2694
+ </map>
2695
+ <map>
2696
+ <framework name="2672" output_port_id="2672" />
2697
+ <IR name="2672" output_port_id="2" />
2698
+ </map>
2699
+ <map>
2700
+ <framework name="2681" output_port_id="2681" />
2701
+ <IR name="2681" output_port_id="2" />
2702
+ </map>
2703
+ <map>
2704
+ <framework name="2682" output_port_id="2682" />
2705
+ <IR name="2682" output_port_id="2" />
2706
+ </map>
2707
+ <map>
2708
+ <framework name="2683" output_port_id="2683" />
2709
+ <IR name="2683" output_port_id="2" />
2710
+ </map>
2711
+ <map>
2712
+ <framework name="2685" output_port_id="2685" />
2713
+ <IR name="2685" output_port_id="2" />
2714
+ </map>
2715
+ <map>
2716
+ <framework name="2686" output_port_id="2686" />
2717
+ <IR name="2686" output_port_id="2" />
2718
+ </map>
2719
+ <map>
2720
+ <framework name="2694" output_port_id="2694" />
2721
+ <IR name="2694" output_port_id="1" />
2722
+ </map>
2723
+ <map>
2724
+ <framework name="2696" output_port_id="2696" />
2725
+ <IR name="2696" output_port_id="2" />
2726
+ </map>
2727
+ <map>
2728
+ <framework name="2697" output_port_id="2697" />
2729
+ <IR name="2697" output_port_id="2" />
2730
+ </map>
2731
+ <map>
2732
+ <framework name="2698" output_port_id="2698" />
2733
+ <IR name="2698" output_port_id="2" />
2734
+ </map>
2735
+ <map>
2736
+ <framework name="2707" output_port_id="2707" />
2737
+ <IR name="2707" output_port_id="2" />
2738
+ </map>
2739
+ <map>
2740
+ <framework name="2708" output_port_id="2708" />
2741
+ <IR name="2708" output_port_id="2" />
2742
+ </map>
2743
+ <map>
2744
+ <framework name="2709" output_port_id="2709" />
2745
+ <IR name="2709" output_port_id="2" />
2746
+ </map>
2747
+ <map>
2748
+ <framework name="2711" output_port_id="2711" />
2749
+ <IR name="2711" output_port_id="2" />
2750
+ </map>
2751
+ <map>
2752
+ <framework name="2712" output_port_id="2712" />
2753
+ <IR name="2712" output_port_id="2" />
2754
+ </map>
2755
+ <map>
2756
+ <framework name="2761" output_port_id="2761" />
2757
+ <IR name="2761" output_port_id="2" />
2758
+ </map>
2759
+ <map>
2760
+ <framework name="2762" output_port_id="2762" />
2761
+ <IR name="2762" output_port_id="2" />
2762
+ </map>
2763
+ <map>
2764
+ <framework name="2714" output_port_id="2714" />
2765
+ <IR name="2714" output_port_id="2" />
2766
+ </map>
2767
+ <map>
2768
+ <framework name="2715" output_port_id="2715" />
2769
+ <IR name="2715" output_port_id="2" />
2770
+ </map>
2771
+ <map>
2772
+ <framework name="2729" output_port_id="2729" />
2773
+ <IR name="2729" output_port_id="2" />
2774
+ </map>
2775
+ <map>
2776
+ <framework name="2763" output_port_id="2763" />
2777
+ <IR name="2763" output_port_id="2" />
2778
+ </map>
2779
+ <map>
2780
+ <framework name="2766" output_port_id="2766" />
2781
+ <IR name="2766" output_port_id="2" />
2782
+ </map>
2783
+ <map>
2784
+ <framework name="2767" output_port_id="2767" />
2785
+ <IR name="2767" output_port_id="2" />
2786
+ </map>
2787
+ <map>
2788
+ <framework name="2768" output_port_id="2768" />
2789
+ <IR name="2768" output_port_id="2" />
2790
+ </map>
2791
+ <map>
2792
+ <framework name="2731" output_port_id="2731" />
2793
+ <IR name="2731" output_port_id="2" />
2794
+ </map>
2795
+ <map>
2796
+ <framework name="2732" output_port_id="2732" />
2797
+ <IR name="2732" output_port_id="2" />
2798
+ </map>
2799
+ <map>
2800
+ <framework name="2746" output_port_id="2746" />
2801
+ <IR name="2746" output_port_id="2" />
2802
+ </map>
2803
+ <map>
2804
+ <framework name="2747" output_port_id="2747" />
2805
+ <IR name="2747" output_port_id="2" />
2806
+ </map>
2807
+ <map>
2808
+ <framework name="2769" output_port_id="2769" />
2809
+ <IR name="2769" output_port_id="2" />
2810
+ </map>
2811
+ <map>
2812
+ <framework name="2770" output_port_id="2770" />
2813
+ <IR name="2770" output_port_id="2" />
2814
+ </map>
2815
+ <map>
2816
+ <framework name="2782" output_port_id="2782" />
2817
+ <IR name="2782" output_port_id="2" />
2818
+ </map>
2819
+ <map>
2820
+ <framework name="2784" output_port_id="2784" />
2821
+ <IR name="2784" output_port_id="2" />
2822
+ </map>
2823
+ <map>
2824
+ <framework name="2785" output_port_id="2785" />
2825
+ <IR name="2785" output_port_id="2" />
2826
+ </map>
2827
+ <map>
2828
+ <framework name="2786" output_port_id="2786" />
2829
+ <IR name="2786" output_port_id="2" />
2830
+ </map>
2831
+ <map>
2832
+ <framework name="2795" output_port_id="2795" />
2833
+ <IR name="2795" output_port_id="2" />
2834
+ </map>
2835
+ <map>
2836
+ <framework name="2796" output_port_id="2796" />
2837
+ <IR name="2796" output_port_id="2" />
2838
+ </map>
2839
+ <map>
2840
+ <framework name="2797" output_port_id="2797" />
2841
+ <IR name="2797" output_port_id="2" />
2842
+ </map>
2843
+ <map>
2844
+ <framework name="2799" output_port_id="2799" />
2845
+ <IR name="2799" output_port_id="2" />
2846
+ </map>
2847
+ <map>
2848
+ <framework name="2800" output_port_id="2800" />
2849
+ <IR name="2800" output_port_id="2" />
2850
+ </map>
2851
+ <map>
2852
+ <framework name="2808" output_port_id="2808" />
2853
+ <IR name="2808" output_port_id="1" />
2854
+ </map>
2855
+ <map>
2856
+ <framework name="2810" output_port_id="2810" />
2857
+ <IR name="2810" output_port_id="2" />
2858
+ </map>
2859
+ <map>
2860
+ <framework name="2811" output_port_id="2811" />
2861
+ <IR name="2811" output_port_id="2" />
2862
+ </map>
2863
+ <map>
2864
+ <framework name="2812" output_port_id="2812" />
2865
+ <IR name="2812" output_port_id="2" />
2866
+ </map>
2867
+ <map>
2868
+ <framework name="2821" output_port_id="2821" />
2869
+ <IR name="2821" output_port_id="2" />
2870
+ </map>
2871
+ <map>
2872
+ <framework name="2822" output_port_id="2822" />
2873
+ <IR name="2822" output_port_id="2" />
2874
+ </map>
2875
+ <map>
2876
+ <framework name="2823" output_port_id="2823" />
2877
+ <IR name="2823" output_port_id="2" />
2878
+ </map>
2879
+ <map>
2880
+ <framework name="2825" output_port_id="2825" />
2881
+ <IR name="2825" output_port_id="2" />
2882
+ </map>
2883
+ <map>
2884
+ <framework name="2826" output_port_id="2826" />
2885
+ <IR name="2826" output_port_id="2" />
2886
+ </map>
2887
+ <map>
2888
+ <framework name="2875" output_port_id="2875" />
2889
+ <IR name="2875" output_port_id="2" />
2890
+ </map>
2891
+ <map>
2892
+ <framework name="2876" output_port_id="2876" />
2893
+ <IR name="2876" output_port_id="2" />
2894
+ </map>
2895
+ <map>
2896
+ <framework name="2828" output_port_id="2828" />
2897
+ <IR name="2828" output_port_id="2" />
2898
+ </map>
2899
+ <map>
2900
+ <framework name="2829" output_port_id="2829" />
2901
+ <IR name="2829" output_port_id="2" />
2902
+ </map>
2903
+ <map>
2904
+ <framework name="2843" output_port_id="2843" />
2905
+ <IR name="2843" output_port_id="2" />
2906
+ </map>
2907
+ <map>
2908
+ <framework name="2877" output_port_id="2877" />
2909
+ <IR name="2877" output_port_id="2" />
2910
+ </map>
2911
+ <map>
2912
+ <framework name="2880" output_port_id="2880" />
2913
+ <IR name="2880" output_port_id="2" />
2914
+ </map>
2915
+ <map>
2916
+ <framework name="2881" output_port_id="2881" />
2917
+ <IR name="2881" output_port_id="2" />
2918
+ </map>
2919
+ <map>
2920
+ <framework name="2882" output_port_id="2882" />
2921
+ <IR name="2882" output_port_id="2" />
2922
+ </map>
2923
+ <map>
2924
+ <framework name="2845" output_port_id="2845" />
2925
+ <IR name="2845" output_port_id="2" />
2926
+ </map>
2927
+ <map>
2928
+ <framework name="2846" output_port_id="2846" />
2929
+ <IR name="2846" output_port_id="2" />
2930
+ </map>
2931
+ <map>
2932
+ <framework name="2860" output_port_id="2860" />
2933
+ <IR name="2860" output_port_id="2" />
2934
+ </map>
2935
+ <map>
2936
+ <framework name="2861" output_port_id="2861" />
2937
+ <IR name="2861" output_port_id="2" />
2938
+ </map>
2939
+ <map>
2940
+ <framework name="2883" output_port_id="2883" />
2941
+ <IR name="2883" output_port_id="2" />
2942
+ </map>
2943
+ <map>
2944
+ <framework name="2884" output_port_id="2884" />
2945
+ <IR name="2884" output_port_id="2" />
2946
+ </map>
2947
+ <map>
2948
+ <framework name="2896" output_port_id="2896" />
2949
+ <IR name="2896" output_port_id="2" />
2950
+ </map>
2951
+ <map>
2952
+ <framework name="2898" output_port_id="2898" />
2953
+ <IR name="2898" output_port_id="2" />
2954
+ </map>
2955
+ <map>
2956
+ <framework name="2899" output_port_id="2899" />
2957
+ <IR name="2899" output_port_id="2" />
2958
+ </map>
2959
+ <map>
2960
+ <framework name="2900" output_port_id="2900" />
2961
+ <IR name="2900" output_port_id="2" />
2962
+ </map>
2963
+ <map>
2964
+ <framework name="2909" output_port_id="2909" />
2965
+ <IR name="2909" output_port_id="2" />
2966
+ </map>
2967
+ <map>
2968
+ <framework name="2910" output_port_id="2910" />
2969
+ <IR name="2910" output_port_id="2" />
2970
+ </map>
2971
+ <map>
2972
+ <framework name="2911" output_port_id="2911" />
2973
+ <IR name="2911" output_port_id="2" />
2974
+ </map>
2975
+ <map>
2976
+ <framework name="2913" output_port_id="2913" />
2977
+ <IR name="2913" output_port_id="2" />
2978
+ </map>
2979
+ <map>
2980
+ <framework name="2914" output_port_id="2914" />
2981
+ <IR name="2914" output_port_id="2" />
2982
+ </map>
2983
+ <map>
2984
+ <framework name="2922" output_port_id="2922" />
2985
+ <IR name="2922" output_port_id="1" />
2986
+ </map>
2987
+ <map>
2988
+ <framework name="2924" output_port_id="2924" />
2989
+ <IR name="2924" output_port_id="2" />
2990
+ </map>
2991
+ <map>
2992
+ <framework name="2925" output_port_id="2925" />
2993
+ <IR name="2925" output_port_id="2" />
2994
+ </map>
2995
+ <map>
2996
+ <framework name="2926" output_port_id="2926" />
2997
+ <IR name="2926" output_port_id="2" />
2998
+ </map>
2999
+ <map>
3000
+ <framework name="2935" output_port_id="2935" />
3001
+ <IR name="2935" output_port_id="2" />
3002
+ </map>
3003
+ <map>
3004
+ <framework name="2936" output_port_id="2936" />
3005
+ <IR name="2936" output_port_id="2" />
3006
+ </map>
3007
+ <map>
3008
+ <framework name="2937" output_port_id="2937" />
3009
+ <IR name="2937" output_port_id="2" />
3010
+ </map>
3011
+ <map>
3012
+ <framework name="2939" output_port_id="2939" />
3013
+ <IR name="2939" output_port_id="2" />
3014
+ </map>
3015
+ <map>
3016
+ <framework name="2940" output_port_id="2940" />
3017
+ <IR name="2940" output_port_id="2" />
3018
+ </map>
3019
+ <map>
3020
+ <framework name="2989" output_port_id="2989" />
3021
+ <IR name="2989" output_port_id="2" />
3022
+ </map>
3023
+ <map>
3024
+ <framework name="2990" output_port_id="2990" />
3025
+ <IR name="2990" output_port_id="2" />
3026
+ </map>
3027
+ <map>
3028
+ <framework name="2942" output_port_id="2942" />
3029
+ <IR name="2942" output_port_id="2" />
3030
+ </map>
3031
+ <map>
3032
+ <framework name="2943" output_port_id="2943" />
3033
+ <IR name="2943" output_port_id="2" />
3034
+ </map>
3035
+ <map>
3036
+ <framework name="2957" output_port_id="2957" />
3037
+ <IR name="2957" output_port_id="2" />
3038
+ </map>
3039
+ <map>
3040
+ <framework name="2991" output_port_id="2991" />
3041
+ <IR name="2991" output_port_id="2" />
3042
+ </map>
3043
+ <map>
3044
+ <framework name="2994" output_port_id="2994" />
3045
+ <IR name="2994" output_port_id="2" />
3046
+ </map>
3047
+ <map>
3048
+ <framework name="2995" output_port_id="2995" />
3049
+ <IR name="2995" output_port_id="2" />
3050
+ </map>
3051
+ <map>
3052
+ <framework name="2996" output_port_id="2996" />
3053
+ <IR name="2996" output_port_id="2" />
3054
+ </map>
3055
+ <map>
3056
+ <framework name="2959" output_port_id="2959" />
3057
+ <IR name="2959" output_port_id="2" />
3058
+ </map>
3059
+ <map>
3060
+ <framework name="2960" output_port_id="2960" />
3061
+ <IR name="2960" output_port_id="2" />
3062
+ </map>
3063
+ <map>
3064
+ <framework name="2974" output_port_id="2974" />
3065
+ <IR name="2974" output_port_id="2" />
3066
+ </map>
3067
+ <map>
3068
+ <framework name="2975" output_port_id="2975" />
3069
+ <IR name="2975" output_port_id="2" />
3070
+ </map>
3071
+ <map>
3072
+ <framework name="2997" output_port_id="2997" />
3073
+ <IR name="2997" output_port_id="2" />
3074
+ </map>
3075
+ <map>
3076
+ <framework name="2998" output_port_id="2998" />
3077
+ <IR name="2998" output_port_id="2" />
3078
+ </map>
3079
+ <map>
3080
+ <framework name="3010" output_port_id="3010" />
3081
+ <IR name="3010" output_port_id="2" />
3082
+ </map>
3083
+ <map>
3084
+ <framework name="3012" output_port_id="3012" />
3085
+ <IR name="3012" output_port_id="2" />
3086
+ </map>
3087
+ <map>
3088
+ <framework name="3013" output_port_id="3013" />
3089
+ <IR name="3013" output_port_id="2" />
3090
+ </map>
3091
+ <map>
3092
+ <framework name="3014" output_port_id="3014" />
3093
+ <IR name="3014" output_port_id="2" />
3094
+ </map>
3095
+ <map>
3096
+ <framework name="3023" output_port_id="3023" />
3097
+ <IR name="3023" output_port_id="2" />
3098
+ </map>
3099
+ <map>
3100
+ <framework name="3024" output_port_id="3024" />
3101
+ <IR name="3024" output_port_id="2" />
3102
+ </map>
3103
+ <map>
3104
+ <framework name="3025" output_port_id="3025" />
3105
+ <IR name="3025" output_port_id="2" />
3106
+ </map>
3107
+ <map>
3108
+ <framework name="3027" output_port_id="3027" />
3109
+ <IR name="3027" output_port_id="2" />
3110
+ </map>
3111
+ <map>
3112
+ <framework name="3028" output_port_id="3028" />
3113
+ <IR name="3028" output_port_id="2" />
3114
+ </map>
3115
+ <map>
3116
+ <framework name="3036" output_port_id="3036" />
3117
+ <IR name="3036" output_port_id="1" />
3118
+ </map>
3119
+ <map>
3120
+ <framework name="3038" output_port_id="3038" />
3121
+ <IR name="3038" output_port_id="2" />
3122
+ </map>
3123
+ <map>
3124
+ <framework name="3039" output_port_id="3039" />
3125
+ <IR name="3039" output_port_id="2" />
3126
+ </map>
3127
+ <map>
3128
+ <framework name="3040" output_port_id="3040" />
3129
+ <IR name="3040" output_port_id="2" />
3130
+ </map>
3131
+ <map>
3132
+ <framework name="3049" output_port_id="3049" />
3133
+ <IR name="3049" output_port_id="2" />
3134
+ </map>
3135
+ <map>
3136
+ <framework name="3050" output_port_id="3050" />
3137
+ <IR name="3050" output_port_id="2" />
3138
+ </map>
3139
+ <map>
3140
+ <framework name="3051" output_port_id="3051" />
3141
+ <IR name="3051" output_port_id="2" />
3142
+ </map>
3143
+ <map>
3144
+ <framework name="3053" output_port_id="3053" />
3145
+ <IR name="3053" output_port_id="2" />
3146
+ </map>
3147
+ <map>
3148
+ <framework name="3054" output_port_id="3054" />
3149
+ <IR name="3054" output_port_id="2" />
3150
+ </map>
3151
+ <map>
3152
+ <framework name="3103" output_port_id="3103" />
3153
+ <IR name="3103" output_port_id="2" />
3154
+ </map>
3155
+ <map>
3156
+ <framework name="3104" output_port_id="3104" />
3157
+ <IR name="3104" output_port_id="2" />
3158
+ </map>
3159
+ <map>
3160
+ <framework name="3056" output_port_id="3056" />
3161
+ <IR name="3056" output_port_id="2" />
3162
+ </map>
3163
+ <map>
3164
+ <framework name="3057" output_port_id="3057" />
3165
+ <IR name="3057" output_port_id="2" />
3166
+ </map>
3167
+ <map>
3168
+ <framework name="3071" output_port_id="3071" />
3169
+ <IR name="3071" output_port_id="2" />
3170
+ </map>
3171
+ <map>
3172
+ <framework name="3105" output_port_id="3105" />
3173
+ <IR name="3105" output_port_id="2" />
3174
+ </map>
3175
+ <map>
3176
+ <framework name="3108" output_port_id="3108" />
3177
+ <IR name="3108" output_port_id="2" />
3178
+ </map>
3179
+ <map>
3180
+ <framework name="3109" output_port_id="3109" />
3181
+ <IR name="3109" output_port_id="2" />
3182
+ </map>
3183
+ <map>
3184
+ <framework name="3110" output_port_id="3110" />
3185
+ <IR name="3110" output_port_id="2" />
3186
+ </map>
3187
+ <map>
3188
+ <framework name="3073" output_port_id="3073" />
3189
+ <IR name="3073" output_port_id="2" />
3190
+ </map>
3191
+ <map>
3192
+ <framework name="3074" output_port_id="3074" />
3193
+ <IR name="3074" output_port_id="2" />
3194
+ </map>
3195
+ <map>
3196
+ <framework name="3088" output_port_id="3088" />
3197
+ <IR name="3088" output_port_id="2" />
3198
+ </map>
3199
+ <map>
3200
+ <framework name="3089" output_port_id="3089" />
3201
+ <IR name="3089" output_port_id="2" />
3202
+ </map>
3203
+ <map>
3204
+ <framework name="3111" output_port_id="3111" />
3205
+ <IR name="3111" output_port_id="2" />
3206
+ </map>
3207
+ <map>
3208
+ <framework name="3112" output_port_id="3112" />
3209
+ <IR name="3112" output_port_id="2" />
3210
+ </map>
3211
+ <map>
3212
+ <framework name="3124" output_port_id="3124" />
3213
+ <IR name="3124" output_port_id="2" />
3214
+ </map>
3215
+ <map>
3216
+ <framework name="3126" output_port_id="3126" />
3217
+ <IR name="3126" output_port_id="2" />
3218
+ </map>
3219
+ <map>
3220
+ <framework name="3127" output_port_id="3127" />
3221
+ <IR name="3127" output_port_id="2" />
3222
+ </map>
3223
+ <map>
3224
+ <framework name="3128" output_port_id="3128" />
3225
+ <IR name="3128" output_port_id="2" />
3226
+ </map>
3227
+ <map>
3228
+ <framework name="3137" output_port_id="3137" />
3229
+ <IR name="3137" output_port_id="2" />
3230
+ </map>
3231
+ <map>
3232
+ <framework name="3138" output_port_id="3138" />
3233
+ <IR name="3138" output_port_id="2" />
3234
+ </map>
3235
+ <map>
3236
+ <framework name="3139" output_port_id="3139" />
3237
+ <IR name="3139" output_port_id="2" />
3238
+ </map>
3239
+ <map>
3240
+ <framework name="3141" output_port_id="3141" />
3241
+ <IR name="3141" output_port_id="2" />
3242
+ </map>
3243
+ <map>
3244
+ <framework name="3142" output_port_id="3142" />
3245
+ <IR name="3142" output_port_id="2" />
3246
+ </map>
3247
+ <map>
3248
+ <framework name="3150" output_port_id="3150" />
3249
+ <IR name="3150" output_port_id="1" />
3250
+ </map>
3251
+ <map>
3252
+ <framework name="3152" output_port_id="3152" />
3253
+ <IR name="3152" output_port_id="2" />
3254
+ </map>
3255
+ <map>
3256
+ <framework name="3153" output_port_id="3153" />
3257
+ <IR name="3153" output_port_id="2" />
3258
+ </map>
3259
+ <map>
3260
+ <framework name="3154" output_port_id="3154" />
3261
+ <IR name="3154" output_port_id="2" />
3262
+ </map>
3263
+ <map>
3264
+ <framework name="3163" output_port_id="3163" />
3265
+ <IR name="3163" output_port_id="2" />
3266
+ </map>
3267
+ <map>
3268
+ <framework name="3164" output_port_id="3164" />
3269
+ <IR name="3164" output_port_id="2" />
3270
+ </map>
3271
+ <map>
3272
+ <framework name="3165" output_port_id="3165" />
3273
+ <IR name="3165" output_port_id="2" />
3274
+ </map>
3275
+ <map>
3276
+ <framework name="3167" output_port_id="3167" />
3277
+ <IR name="3167" output_port_id="2" />
3278
+ </map>
3279
+ <map>
3280
+ <framework name="3168" output_port_id="3168" />
3281
+ <IR name="3168" output_port_id="2" />
3282
+ </map>
3283
+ <map>
3284
+ <framework name="3170" output_port_id="3169" />
3285
+ <IR name="3170" output_port_id="3" />
3286
+ </map>
3287
+ <map>
3288
+ <framework name="3170" output_port_id="3170" />
3289
+ <IR name="3170" output_port_id="4" />
3290
+ </map>
3291
+ <map>
3292
+ <framework name="output.1" output_port_id="output.1" />
3293
+ <IR name="output.1" output_port_id="2" />
3294
+ </map>
3295
+ <map>
3296
+ <framework name="output.0" output_port_id="output.0" />
3297
+ <IR name="output.0" output_port_id="2" />
3298
+ </map>
3299
+ </mapping>
ir/squad-BertForQuestionAnswering.cropped.fp32.onnx ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0b5e178f6a8dd5648467ab67a3b40c6d847e3ebec4379fa80ebbe3d9a7ba7c59
3
+ size 955810091
ir/squad-BertForQuestionAnswering.cropped.fp32.xml ADDED
The diff for this file is too large to render. See raw diff
 
nncf-mvmt-p3.json ADDED
@@ -0,0 +1,68 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "input_info": [
3
+ {
4
+ "sample_size": [1, 384],
5
+ "type": "long"
6
+ },
7
+ {
8
+ "sample_size": [1, 384],
9
+ "type": "long"
10
+ },
11
+ {
12
+ "sample_size": [1, 384],
13
+ "type": "long"
14
+ }
15
+ ],
16
+ "compression":
17
+ [
18
+ {
19
+ "algorithm": "movement_sparsity",
20
+ "params": {
21
+ "schedule": "threshold_polynomial_decay",
22
+ "power": 3,
23
+ "init_importance_threshold": 0.0,
24
+ "final_importance_threshold": 0.1,
25
+ "warmup_start_epoch": 1,
26
+ "warmup_end_epoch": 10,
27
+ "steps_per_epoch": 2767, // 5533,
28
+ "importance_regularization_factor": 0.02,
29
+ "update_per_optimizer_step": true,
30
+ },
31
+ "sparse_structure_by_scopes": [
32
+ ["block", [32, 32], "{re}.*BertAttention*"],
33
+ ["per_dim", [0], "{re}.*BertIntermediate*"],
34
+ ["per_dim", [1], "{re}.*BertOutput*"]
35
+ ],
36
+ "ignored_scopes": ["{re}.*NNCFEmbedding", "{re}.*qa_outputs*"]
37
+ },
38
+ // {
39
+ // "algorithm": "quantization",
40
+ // "initializer": {
41
+ // "range": {
42
+ // "num_init_samples": 32,
43
+ // "type": "percentile",
44
+ // "params":
45
+ // {
46
+ // "min_percentile": 0.01,
47
+ // "max_percentile": 99.99
48
+ // }
49
+ // },
50
+
51
+ // "batchnorm_adaptation": {
52
+ // // "num_bn_adaptation_samples": 2
53
+ // "num_bn_adaptation_samples": 200
54
+ // }
55
+ // },
56
+ // "activations":
57
+ // {
58
+ // "mode": "symmetric"
59
+ // },
60
+ // "weights":
61
+ // {
62
+ // "mode": "symmetric",
63
+ // "signed": true,
64
+ // "per_channel": false
65
+ // }
66
+ // }
67
+ ]
68
+ }
original_graph.dot ADDED
The diff for this file is too large to render. See raw diff