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Trainer.train() when finishing training return:
AttributeError: 'Trainer' object has no attribute 'use_cuda_amp'
During handling of the above exception, another exception occurred:
AttributeError: 'Trainer' object has no attribute 'use_amp'
Steps/Code to reproduce bug
Train a model with these configurations:
training_args = T4RecTrainingArguments(
output_dir=lb_out.as_posix(),
max_sequence_length=20,
data_loader_engine='nvtabular',
num_train_epochs=1,
dataloader_drop_last=False,
per_device_train_batch_size=256,
per_device_eval_batch_size=16,
gradient_accumulation_steps=1,
learning_rate=0.0005,
report_to=[],
save_strategy='no',
logging_steps=500
)
Bug description
Trainer.train() when finishing training return:
AttributeError: 'Trainer' object has no attribute 'use_cuda_amp'
During handling of the above exception, another exception occurred:
AttributeError: 'Trainer' object has no attribute 'use_amp'
Steps/Code to reproduce bug
Train a model with these configurations:
training_args = T4RecTrainingArguments(
output_dir=lb_out.as_posix(),
max_sequence_length=20,
data_loader_engine='nvtabular',
num_train_epochs=1,
dataloader_drop_last=False,
per_device_train_batch_size=256,
per_device_eval_batch_size=16,
gradient_accumulation_steps=1,
learning_rate=0.0005,
report_to=[],
save_strategy='no',
logging_steps=500
)
trainer = Trainer(
model=model,
args=training_args,
schema=schema,
compute_metrics=True,
)
Expected behavior
Model finish training without returning error
Environment details
Additional context
It seems that transformers have remove CUDA amp entirely for CPU amp. huggingface/transformers#27760
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