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