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79 lines
2.7 KiB
79 lines
2.7 KiB
import torch
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import torch.distributed as dist
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from colossalai.core import global_context as gpc
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from colossalai.context import ParallelMode
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from functools import partial
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__all__ = ['ColoDDP']
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def free_storage(data: torch.Tensor) -> None:
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"""Free underlying storage of a Tensor."""
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if data.storage().size() > 0:
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# Since we're modifying the Tensor's Storage directly, make sure the Tensor
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# is the sole occupant of the Storage.
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assert data.storage_offset() == 0
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data.storage().resize_(0)
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class ColoDDP(torch.nn.Module):
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def __init__(self, module: torch.nn.Module) -> None:
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super().__init__()
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self.module = module
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self.comm_stream: torch.cuda.Stream = torch.cuda.Stream()
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self.dp_world_size = gpc.get_world_size(ParallelMode.DATA)
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for p in module.parameters():
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if p.requires_grad:
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p.register_hook(partial(self.grad_handle, p))
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def parameters(self, recurse: bool = True):
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return self.module.parameters(recurse)
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def named_parameters(self, prefix: str = '', recurse: bool = True):
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return self.module.named_parameters(prefix, recurse)
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def forward(self, *args, **kwargs):
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self.module.zero_grad(set_to_none=True)
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return self.module(*args, **kwargs)
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def backward(self, loss: torch.Tensor):
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loss.backward()
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torch.cuda.current_stream().wait_stream(self.comm_stream)
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for p in self.module.parameters():
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p.grad = p._saved_grad
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def grad_handle(self, p, grad):
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empty_grad = torch.empty_like(grad)
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free_storage(empty_grad)
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if self.dp_world_size > 1:
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grad = grad / self.dp_world_size
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self.comm_stream.wait_stream(torch.cuda.current_stream())
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with torch.cuda.stream(self.comm_stream):
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dist.all_reduce(grad, group=gpc.get_group(ParallelMode.DATA))
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ColoDDP._save_grad(p, grad)
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grad.record_stream(self.comm_stream)
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else:
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ColoDDP._save_grad(p, grad)
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return empty_grad
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@staticmethod
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def _save_grad(p, grad):
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if hasattr(p, '_saved_grad'):
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p._saved_grad.add_(grad)
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else:
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p._saved_grad = grad
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def zero_grad(self, set_to_none: bool = False) -> None:
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self.module.zero_grad(set_to_none=True)
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for p in self.module.parameters():
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if getattr(p, '_saved_grad', None) is not None:
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if set_to_none:
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p._saved_grad = None
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else:
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if p._saved_grad.grad_fn is not None:
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p._saved_grad.detach_()
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else:
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p._saved_grad.requires_grad_(False)
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p._saved_grad.zero_()
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