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chore: correct update_step and correct gradient_accumulation_steps (#26068)

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This commit is contained in:
Phuc Van Phan
2023-09-13 00:31:23 +07:00
committed by GitHub
parent 8f609ab9e0
commit 4fb64e285a
11 changed files with 13 additions and 12 deletions
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2
examples/pytorch/image-classification/run_image_classification_no_trainer.py
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@@ -477,8 +477,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_step
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/image-pretraining/run_mim_no_trainer.py
View File

@@ -701,8 +701,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/language-modeling/run_mlm_no_trainer.py
View File

@@ -636,8 +636,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/multiple-choice/run_swag_no_trainer.py
View File

@@ -583,8 +583,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py
View File

@@ -820,8 +820,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

5
examples/pytorch/question-answering/run_qa_no_trainer.py
View File

@@ -848,10 +848,11 @@ def main():
resume_step = None
completed_steps = starting_epoch * num_update_steps_per_epoch
else:
resume_step = int(training_difference.replace("step_", ""))
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py
View File

@@ -581,8 +581,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/summarization/run_summarization_no_trainer.py
View File

@@ -652,8 +652,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/text-classification/run_glue_no_trainer.py
View File

@@ -530,8 +530,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_step
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/token-classification/run_ner_no_trainer.py
View File

@@ -690,8 +690,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)

2
examples/pytorch/translation/run_translation_no_trainer.py
View File

@@ -633,8 +633,8 @@ def main():
# need to multiply `gradient_accumulation_steps` to reflect real steps
resume_step = int(training_difference.replace("step_", "")) * args.gradient_accumulation_steps
starting_epoch = resume_step // len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_steps
resume_step -= starting_epoch * len(train_dataloader)
completed_steps = resume_step // args.gradient_accumulation_stepp
# update the progress_bar if load from checkpoint
progress_bar.update(completed_steps)