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In fact, tensors and NumPy arrays can often share the same underlying memory, eliminating the need to copy data (see Bridge with NumPy). Tensors are also optimized for automatic differentiation (we’ll see more about that later in the Autograd section).
The text was updated successfully, but these errors were encountered:
corazzon
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문서 URL
수정이 필요한 URL을 남겨주세요. (예. https://tutorials.pytorch.kr/beginner/basics/intro.html)
https://tutorials.pytorch.kr/beginner/basics/tensorqs_tutorial.html
변경 사항
(1)어떤 단어 / 문장 / 내용이 (2)어떻게 변경되어야 한다고 생각하세요?
(1) 데이터를 복수할 필요가 없습니다.
(2) 데이터를 복사할 필요가 없습니다.
https://github.com/PyTorchKorea/tutorials-kr/blob/master/beginner_source/basics/tensorqs_tutorial.py#L19
추가 정보
위와 같이 생각하신 이유 또는 다른 참고할 정보가 있다면 알려주세요.
원문을 봤을 때 해당 단어가 copy 로 되어있기 때문에 복사로 수정이 필요합니다.
In fact, tensors and NumPy arrays can often share the same underlying memory, eliminating the need to copy data (see Bridge with NumPy). Tensors are also optimized for automatic differentiation (we’ll see more about that later in the Autograd section).
The text was updated successfully, but these errors were encountered: