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Fix typo: overlaped_forward_backward -> overlapped_forward_backward

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This commit is contained in:
RK
2025-02-27 12:42:25 +08:00
parent ebe10fcefe
commit bb214e82b5
2 changed files with 4 additions and 4 deletions
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6
dualpipe/dualpipe.py
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@@ -20,7 +20,7 @@ class DualPipe(nn.Module):
assert next(modules[0].parameters()).device == torch.device(torch.cuda.current_device()) assert next(modules[0].parameters()).device == torch.device(torch.cuda.current_device())
self.module = nn.ModuleList(modules) self.module = nn.ModuleList(modules)
self.overlaped_forward_backward = type(modules[0]) == type(modules[1]) and hasattr(type(modules[0]), "overlaped_forward_backward") self.overlapped_forward_backward = type(modules[0]) == type(modules[1]) and hasattr(type(modules[0]), "overlapped_forward_backward")
self.batch_dim = batch_dim self.batch_dim = batch_dim
self.group = process_group or dist.distributed_c10d._get_default_group() self.group = process_group or dist.distributed_c10d._get_default_group()
self.num_ranks = self.group.size() self.num_ranks = self.group.size()
@@ -123,7 +123,7 @@ class DualPipe(nn.Module):
self._forward_compute_chunk(phase0) self._forward_compute_chunk(phase0)
return return
if not self.overlaped_forward_backward: if not self.overlapped_forward_backward:
self._forward_compute_chunk(phase0) self._forward_compute_chunk(phase0)
self._backward_compute_chunk(phase1) self._backward_compute_chunk(phase1)
return return
@@ -165,7 +165,7 @@ class DualPipe(nn.Module):
outputs1, output_grads1 = list(zip(*non_empty)) outputs1, output_grads1 = list(zip(*non_empty))
# forward & backward # forward & backward
outputs0, loss0 = type(module0).overlaped_forward_backward( outputs0, loss0 = type(module0).overlapped_forward_backward(
module0, inputs0, criterion0, labels0, module0, inputs0, criterion0, labels0,
module1, loss1, outputs1, output_grads1, module1, loss1, outputs1, output_grads1,
) )

2
example.py
View File

@@ -52,7 +52,7 @@ class PipelineStage(nn.Module):
return x return x
@classmethod @classmethod
def overlaped_forward_backward( def overlapped_forward_backward(
cls, cls,
module0: "PipelineStage", module0: "PipelineStage",
inputs0: List[torch.Tensor], inputs0: List[torch.Tensor],