empty_strided(size, stride, *, dtype=None, layout=None, device=None, requires_grad=False, pin_memory=False) → Tensor¶
Creates a tensor with the specified
strideand filled with undefined data.
If the constructed tensor is “overlapped” (with multiple indices referring to the same element in memory) its behavior is undefined.
size (tuple of python:ints) – the shape of the output tensor
stride (tuple of python:ints) – the strides of the output tensor
- Keyword Arguments
torch.layout, optional) – the desired layout of returned Tensor. Default:
torch.device, optional) – the desired device of returned tensor. Default: if
None, uses the current device for the default tensor type (see
devicewill be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.
requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default:
pin_memory (bool, optional) – If set, returned tensor would be allocated in the pinned memory. Works only for CPU tensors. Default:
>>> a = torch.empty_strided((2, 3), (1, 2)) >>> a tensor([[8.9683e-44, 4.4842e-44, 5.1239e+07], [0.0000e+00, 0.0000e+00, 3.0705e-41]]) >>> a.stride() (1, 2) >>> a.size() torch.Size([2, 3])