nielsr HF staff commited on
Commit
cf6d4b6
1 Parent(s): 603c7eb

Add print statements

Browse files
Files changed (1) hide show
  1. modeling_cogvlm.py +93 -93
modeling_cogvlm.py CHANGED
@@ -243,33 +243,33 @@ class VisionExpertAttention(nn.Module):
243
 
244
  if print_values:
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246
- torch.save(query_states, "query_states.pt")
247
- torch.save(key_states, "key_states.pt")
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- torch.save(value_states, "value_states.pt")
249
-
250
- from huggingface_hub import HfApi
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-
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- api = HfApi()
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- api.upload_file(
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- path_or_fileobj="query_states.pt",
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- path_in_repo="query_states.pt",
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- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
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- )
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- api = HfApi()
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- api.upload_file(
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- path_or_fileobj="key_states.pt",
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- path_in_repo="key_states.pt",
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- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
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- )
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- api = HfApi()
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- api.upload_file(
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- path_or_fileobj="value_states.pt",
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- path_in_repo="value_states.pt",
270
- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
272
- )
273
 
274
  kv_seq_len = key_states.shape[-2]
275
  if past_key_value is not None:
@@ -473,31 +473,31 @@ class CogVLMModel(CogVLMPreTrainedModel):
473
  images_features = rearrange(images_features, 'b n d -> (b n) d')
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  images_features = images_features.to(dtype=inputs_embeds.dtype, device=inputs_embeds.device)
475
 
476
- from huggingface_hub import HfApi
477
 
478
- torch.save(images_features, "images_features.pt")
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- torch.save(inputs_embeds, "inputs_embeds.pt")
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- torch.save(token_type_ids, "token_type_ids.pt")
481
 
482
- api = HfApi()
483
- api.upload_file(
484
- path_or_fileobj="images_features.pt",
485
- path_in_repo="images_features.pt",
486
- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
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- )
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- api.upload_file(
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- path_or_fileobj="inputs_embeds.pt",
491
- path_in_repo="inputs_embeds.pt",
492
- repo_id="nielsr/test-cogvlm",
493
- repo_type="dataset",
494
- )
495
- api.upload_file(
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- path_or_fileobj="token_type_ids.pt",
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- path_in_repo="token_type_ids.pt",
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- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
500
- )
501
 
502
  # print("First values of text embeddings:", inputs_embeds[0, :3, :3])
503
  # print("First values of images_features:", images_features[0, :3])
@@ -590,41 +590,41 @@ class CogVLMModel(CogVLMPreTrainedModel):
590
 
591
  hidden_states = inputs_embeds
592
 
593
- torch.save(hidden_states, "initial_hidden_states.pt")
594
- torch.save(attention_mask, "initial_attention_mask.pt")
595
- torch.save(token_type_ids, "initial_token_type_ids.pt")
596
- torch.save(position_ids, "initial_position_ids.pt")
597
 
598
- from huggingface_hub import HfApi
599
-
600
- api = HfApi()
601
- api.upload_file(
602
- path_or_fileobj="initial_hidden_states.pt",
603
- path_in_repo="initial_hidden_states.pt",
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- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
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- )
607
- api = HfApi()
608
- api.upload_file(
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- path_or_fileobj="initial_attention_mask.pt",
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- path_in_repo="initial_attention_mask.pt",
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- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
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- )
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- api = HfApi()
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- api.upload_file(
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- path_or_fileobj="initial_token_type_ids.pt",
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- path_in_repo="initial_token_type_ids.pt",
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- repo_id="nielsr/test-cogvlm",
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- repo_type="dataset",
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- )
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- api = HfApi()
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- api.upload_file(
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- path_or_fileobj="initial_position_ids.pt",
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- path_in_repo="initial_position_ids.pt",
625
- repo_id="nielsr/test-cogvlm",
626
- repo_type="dataset",
627
- )
628
 
629
  # decoder layers
630
  all_hidden_states = () if output_hidden_states else None
@@ -648,16 +648,16 @@ class CogVLMModel(CogVLMPreTrainedModel):
648
  )
649
  hidden_states = layer_outputs[0]
650
 
651
- if idx == 0:
652
- torch.save(hidden_states, "hidden_states_after_layer_0.pt")
653
 
654
- api = HfApi()
655
- api.upload_file(
656
- path_or_fileobj="hidden_states_after_layer_0.pt",
657
- path_in_repo="hidden_states_after_layer_0.pt",
658
- repo_id="nielsr/test-cogvlm",
659
- repo_type="dataset",
660
- )
661
 
662
  if use_cache:
663
  next_decoder_cache += (layer_outputs[2 if output_attentions else 1],)
 
243
 
244
  if print_values:
245
 
246
+ # torch.save(query_states, "query_states.pt")
247
+ # torch.save(key_states, "key_states.pt")
248
+ # torch.save(value_states, "value_states.pt")
249
+
250
+ # from huggingface_hub import HfApi
251
+
252
+ # api = HfApi()
253
+ # api.upload_file(
254
+ # path_or_fileobj="query_states.pt",
255
+ # path_in_repo="query_states.pt",
256
+ # repo_id="nielsr/test-cogvlm",
257
+ # repo_type="dataset",
258
+ # )
259
+ # api = HfApi()
260
+ # api.upload_file(
261
+ # path_or_fileobj="key_states.pt",
262
+ # path_in_repo="key_states.pt",
263
+ # repo_id="nielsr/test-cogvlm",
264
+ # repo_type="dataset",
265
+ # )
266
+ # api = HfApi()
267
+ # api.upload_file(
268
+ # path_or_fileobj="value_states.pt",
269
+ # path_in_repo="value_states.pt",
270
+ # repo_id="nielsr/test-cogvlm",
271
+ # repo_type="dataset",
272
+ # )
273
 
274
  kv_seq_len = key_states.shape[-2]
275
  if past_key_value is not None:
 
473
  images_features = rearrange(images_features, 'b n d -> (b n) d')
474
  images_features = images_features.to(dtype=inputs_embeds.dtype, device=inputs_embeds.device)
475
 
476
+ # from huggingface_hub import HfApi
477
 
478
+ # torch.save(images_features, "images_features.pt")
479
+ # torch.save(inputs_embeds, "inputs_embeds.pt")
480
+ # torch.save(token_type_ids, "token_type_ids.pt")
481
 
482
+ # api = HfApi()
483
+ # api.upload_file(
484
+ # path_or_fileobj="images_features.pt",
485
+ # path_in_repo="images_features.pt",
486
+ # repo_id="nielsr/test-cogvlm",
487
+ # repo_type="dataset",
488
+ # )
489
+ # api.upload_file(
490
+ # path_or_fileobj="inputs_embeds.pt",
491
+ # path_in_repo="inputs_embeds.pt",
492
+ # repo_id="nielsr/test-cogvlm",
493
+ # repo_type="dataset",
494
+ # )
495
+ # api.upload_file(
496
+ # path_or_fileobj="token_type_ids.pt",
497
+ # path_in_repo="token_type_ids.pt",
498
+ # repo_id="nielsr/test-cogvlm",
499
+ # repo_type="dataset",
500
+ # )
501
 
502
  # print("First values of text embeddings:", inputs_embeds[0, :3, :3])
503
  # print("First values of images_features:", images_features[0, :3])
 
590
 
591
  hidden_states = inputs_embeds
592
 
593
+ # torch.save(hidden_states, "initial_hidden_states.pt")
594
+ # torch.save(attention_mask, "initial_attention_mask.pt")
595
+ # torch.save(token_type_ids, "initial_token_type_ids.pt")
596
+ # torch.save(position_ids, "initial_position_ids.pt")
597
 
598
+ # from huggingface_hub import HfApi
599
+
600
+ # api = HfApi()
601
+ # api.upload_file(
602
+ # path_or_fileobj="initial_hidden_states.pt",
603
+ # path_in_repo="initial_hidden_states.pt",
604
+ # repo_id="nielsr/test-cogvlm",
605
+ # repo_type="dataset",
606
+ # )
607
+ # api = HfApi()
608
+ # api.upload_file(
609
+ # path_or_fileobj="initial_attention_mask.pt",
610
+ # path_in_repo="initial_attention_mask.pt",
611
+ # repo_id="nielsr/test-cogvlm",
612
+ # repo_type="dataset",
613
+ # )
614
+ # api = HfApi()
615
+ # api.upload_file(
616
+ # path_or_fileobj="initial_token_type_ids.pt",
617
+ # path_in_repo="initial_token_type_ids.pt",
618
+ # repo_id="nielsr/test-cogvlm",
619
+ # repo_type="dataset",
620
+ # )
621
+ # api = HfApi()
622
+ # api.upload_file(
623
+ # path_or_fileobj="initial_position_ids.pt",
624
+ # path_in_repo="initial_position_ids.pt",
625
+ # repo_id="nielsr/test-cogvlm",
626
+ # repo_type="dataset",
627
+ # )
628
 
629
  # decoder layers
630
  all_hidden_states = () if output_hidden_states else None
 
648
  )
649
  hidden_states = layer_outputs[0]
650
 
651
+ # if idx == 0:
652
+ # torch.save(hidden_states, "hidden_states_after_layer_0.pt")
653
 
654
+ # api = HfApi()
655
+ # api.upload_file(
656
+ # path_or_fileobj="hidden_states_after_layer_0.pt",
657
+ # path_in_repo="hidden_states_after_layer_0.pt",
658
+ # repo_id="nielsr/test-cogvlm",
659
+ # repo_type="dataset",
660
+ # )
661
 
662
  if use_cache:
663
  next_decoder_cache += (layer_outputs[2 if output_attentions else 1],)