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Fix(support npu): some little bugs for npu support #129
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internlm/train/pipeline.py
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@@ -299,7 +299,7 @@ def initialize_optimizer(model: Union[nn.Module, nn.ModuleList], isp_communicato | |||
adam_extra_kwargs = {} | |||
# set fused=True to avoid nan grad norm when model size is larger and use_fp32_norm=True | |||
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if internlm_accelerator.get_accelerator_backend() == AcceleratorType.NPU: | |||
if get_accelerator().get_accelerator_backend() == AcceleratorType.NPU: |
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internlm_accelerator = get_accelerator() has already been defined, so no need to use get_accelerator()?
internlm/model/metrics.py
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@@ -155,7 +155,7 @@ def update(self, logits, labels, type_ids=None): | |||
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acc = corrects.sum() | |||
torch.distributed.all_reduce(acc, op=torch.distributed.ReduceOp.SUM, group=self.tp_pg) | |||
torch.npu.synchronize() | |||
internlm_accelerator.synchronize() |
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internlm_accelerator = get_accelerator() has already been defined, so no need to use get_accelerator()?
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LGTM
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