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small nit fixes #1694

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small nit fixes #1694

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4 changes: 2 additions & 2 deletions torchtitan/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -451,7 +451,7 @@ def forward_backward_step(
with self.maybe_enable_amp:
pred = model_parts[0](inputs, eos_id=self.tokenizer.eos_id)
loss = self.loss_fn(pred, labels)
# need to free to before bwd to avoid peaking memory
# need to free pred before bwd to avoid peaking memory
del pred
loss.backward()

Expand All @@ -471,7 +471,7 @@ def train_step(
accumulated_losses = []
# If data runs out during gradient accumulation, that
# entire step will not be executed.
for microbatch in range(self.gradient_accumulation_steps):
for _microbatch in range(self.gradient_accumulation_steps):
input_dict, labels = next(data_iterator)
loss = self.forward_backward_step(input_dict, labels)
accumulated_losses.append(loss.detach())
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