mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
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def _type(self, new_type=None, async=False):
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if new_type is None:
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return self.__module__ + '.' + self.__class__.__name__
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if isinstance(new_type, str):
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new_type = _import_dotted_name(new_type)
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if new_type == type(self):
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return self
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return new_type(self.size()).copy_(self, async)
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def _cuda(self, idx=None, async=False):
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import torch.cuda
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# This already is a CUDA tensor.
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# Let's check if it needs to be transfered to another GPU.
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if hasattr(self, 'get_device'):
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target_device = idx if idx else torch.cuda.current_device()
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if self.get_device() != target_device:
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with torch.cuda.device(target_device):
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return type(self)(self.size()).copy_(self, async)
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else:
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return self
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else:
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ctx = torch.cuda.device(idx) if idx else torch.cuda._dummy_ctx()
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with ctx:
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return self.type(getattr(torch.cuda, self.__class__.__name__), async)
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def _range(*args, **kwargs):
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return __builtins__['range'](*args, **kwargs)
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def _import_dotted_name(name):
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components = name.split('.')
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obj = __import__(components[0])
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for component in components[1:]:
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obj = getattr(obj, component)
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return obj
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