Force grad to be off by default when loading with lazy loader
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a82a165146
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6803531384
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@ -89,7 +89,7 @@ class LazyTensor:
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def __repr__(self):
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def __repr__(self):
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return self.__view(repr)
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return self.__view(repr)
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def materialize(self, checkpoint: Union[zipfile.ZipFile, zipfile.ZipExtFile], map_location=None) -> torch.Tensor:
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def materialize(self, checkpoint: Union[zipfile.ZipFile, zipfile.ZipExtFile], map_location=None, no_grad=True) -> torch.Tensor:
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size = reduce(lambda x, y: x * y, self.shape, 1)
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size = reduce(lambda x, y: x * y, self.shape, 1)
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dtype = self.dtype
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dtype = self.dtype
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nbytes = size if dtype is torch.bool else size * ((torch.finfo if dtype.is_floating_point else torch.iinfo)(dtype).bits >> 3)
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nbytes = size if dtype is torch.bool else size * ((torch.finfo if dtype.is_floating_point else torch.iinfo)(dtype).bits >> 3)
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@ -106,7 +106,7 @@ class LazyTensor:
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storage = torch.serialization._get_restore_location(map_location)(storage, self.location)
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storage = torch.serialization._get_restore_location(map_location)(storage, self.location)
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tensor = torch.tensor([], dtype=storage.dtype, device=storage.device)
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tensor = torch.tensor([], dtype=storage.dtype, device=storage.device)
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tensor.set_(storage, 0, self.shape, self.stride)
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tensor.set_(storage, 0, self.shape, self.stride)
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tensor.requires_grad = self.requires_grad
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tensor.requires_grad = not no_grad and self.requires_grad
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tensor._backward_hooks = self.backward_hooks
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tensor._backward_hooks = self.backward_hooks
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return tensor
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return tensor
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