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Bring back set_epoch for Accelerate-based dataloaders #26850

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Merged
merged 6 commits into from
Oct 26, 2023
Merged

Bring back set_epoch for Accelerate-based dataloaders #26850

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cec09c8
Working tests!
muellerzr Oct 16, 2023
1af2d89
Fix sampler
muellerzr Oct 16, 2023
e280dca
Fix
muellerzr Oct 16, 2023
54fea16
Update src/transformers/trainer.py
muellerzr Oct 17, 2023
6ab2f86
Fix check
muellerzr Oct 24, 2023
6afe340
Clean
muellerzr Oct 24, 2023
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12 changes: 11 additions & 1 deletion src/transformers/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -200,6 +200,11 @@
save_fsdp_model,
save_fsdp_optimizer,
)
DATA_SAMPLERS = [RandomSampler]
if version.parse(accelerate_version) > version.parse("0.23.0"):
from accelerate.data_loader import SeedableRandomSampler

DATA_SAMPLERS += [SeedableRandomSampler]

if is_deepspeed_available():
from accelerate.utils import DeepSpeedSchedulerWrapper
Expand Down Expand Up @@ -1738,7 +1743,10 @@ def _inner_training_loop(
if not args.ignore_data_skip:
for epoch in range(epochs_trained):
sampler = get_dataloader_sampler(train_dataloader)
is_random_sampler = isinstance(sampler, RandomSampler)
sampler_kinds = [RandomSampler]
if version.parse(accelerate_version) > version.parse("0.23.0"):
sampler_kinds.append(SeedableRandomSampler)
is_random_sampler = isinstance(sampler, tuple(sampler_kinds))
if is_torch_less_than_1_11 or not is_random_sampler:
# We just need to begin an iteration to create the randomization of the sampler.
for _ in train_dataloader:
Expand All @@ -1752,6 +1760,8 @@ def _inner_training_loop(
total_batched_samples = 0
for epoch in range(epochs_trained, num_train_epochs):
epoch_iterator = train_dataloader
if hasattr(epoch_iterator, "set_epoch"):
epoch_iterator.set_epoch(epoch)

# Reset the past mems state at the beginning of each epoch if necessary.
if args.past_index >= 0:
Expand Down