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Fix the issue of loading ckpt when retraining #2645

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Merged
merged 2 commits into from
Sep 19, 2025
Merged

Fix the issue of loading ckpt when retraining #2645

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e03017c
fix the issue of loading ckpt when retraining with uc is True
Ace-To-HYB Sep 19, 2025
4bc9130
Merge branch 'PaddlePaddle:develop' into fix_train_resume
Ace-To-HYB Sep 19, 2025
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17 changes: 11 additions & 6 deletions paddleformers/trainer/unified_checkpoint/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -327,10 +327,15 @@ def merge_large_tensor_parallel(tensor, tp_group, tp_action, dst_rank, is_dst):
split_tensors = []
for i in range(num_splits):
if get_env_device() == "xpu":
ret = distributed_allgather(tensor[split_parts[i] : split_parts[i + 1], :], group=tp_group, offload=False)
ret = distributed_allgather(
tensor[split_parts[i] : split_parts[i + 1], :].contiguous(), group=tp_group, offload=False
)
else:
ret = distributed_gather(
tensor[split_parts[i] : split_parts[i + 1], :], dst=dst_rank, group=tp_group, offload=False
tensor[split_parts[i] : split_parts[i + 1], :].contiguous(),
dst=dst_rank,
group=tp_group,
offload=False,
)
# Copy to CPUPlace temporarily, may lower speed.
if ret is not None:
Expand Down Expand Up @@ -383,9 +388,9 @@ def merge_tensor_parallel_with_shard(state_dict, tp_actions, all_filter_keys):
tensor = merge_large_tensor_parallel(tensor, tp_group, tp_actions[key], j, is_dst)
else:
if get_env_device() == "xpu":
ret = distributed_allgather(tensor, group=tp_group, offload=False)
ret = distributed_allgather(tensor.contiguous(), group=tp_group, offload=False)
else:
ret = distributed_gather(tensor, dst=j, group=tp_group, offload=False)
ret = distributed_gather(tensor.contiguous(), dst=j, group=tp_group, offload=False)
action = tp_actions.pop(key)
tensor = action(ret) if is_dst else None
else:
Expand Down Expand Up @@ -439,9 +444,9 @@ def merge_tensor_parallel_for_optimizer(state_dict, model_state_dict, tp_actions
tensor = merge_large_tensor_parallel(tensor, tp_group, tp_actions[model_key], j, is_dst)
else:
if get_env_device() == "xpu":
ret = distributed_allgather(tensor, group=tp_group, offload=False)
ret = distributed_allgather(tensor.contiguous(), group=tp_group, offload=False)
else:
ret = distributed_gather(tensor, dst=j, group=tp_group, offload=False)
ret = distributed_gather(tensor.contiguous(), dst=j, group=tp_group, offload=False)
action = tp_actions[model_key]
tensor = action(ret) if is_dst else None
else:
Expand Down