from_numpy()自动继承输入数组dtype.另一方面，torch.Tensor是torch.FloatTensor的别名.

from_numpy() automatically inherits input array dtype. On the other hand, torch.Tensor is an alias for torch.FloatTensor.

因此，如果将int64数组传递给torch.Tensor，则输出张量为浮点张量，它们将不会共享存储. torch.from_numpy为您提供了torch.LongTensor的期望.

Therefore, if you pass int64 array to torch.Tensor, output tensor is float tensor and they wouldn't share the storage. torch.from_numpy gives you torch.LongTensor as expected.

a = np.arange(10)
ft = torch.Tensor(a)  # same as torch.FloatTensor
it = torch.from_numpy(a)

a.dtype  # == dtype('int64')
ft.dtype  # == torch.float32
it.dtype  # == torch.int64