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@@ -84,7 +84,8 @@ def train(model, train_dataloader,eval_dataloader, tokenizer, optimizer, lr_sche
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if train_config.enable_fsdp:
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if train_config.enable_fsdp:
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batch[key] = batch[key].to(local_rank)
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batch[key] = batch[key].to(local_rank)
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else:
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else:
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- batch[key] = batch[key].to('cuda')
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+
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+ batch[key] = batch[key].to('cuda:0')
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loss = model(**batch).loss
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loss = model(**batch).loss
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loss = loss / gradient_accumulation_steps
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loss = loss / gradient_accumulation_steps
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total_loss += loss.detach().float()
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total_loss += loss.detach().float()
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@@ -198,7 +199,7 @@ def evaluation(model,train_config, eval_dataloader, local_rank, tokenizer):
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if train_config.enable_fsdp:
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if train_config.enable_fsdp:
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batch[key] = batch[key].to(local_rank)
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batch[key] = batch[key].to(local_rank)
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else:
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else:
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- batch[key] = batch[key].to('cuda')
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+ batch[key] = batch[key].to('cuda:0')
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# Ensure no gradients are computed for this scope to save memory
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# Ensure no gradients are computed for this scope to save memory
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with torch.no_grad():
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with torch.no_grad():
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# Forward pass and compute loss
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# Forward pass and compute loss
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