# torch.as_strided¶

torch.as_strided(input, size, stride, storage_offset=0) → Tensor

Create a view of an existing torch.Tensor input with specified size, stride and storage_offset.

Warning

More than one element of a created tensor may refer to a single memory location. As a result, in-place operations (especially ones that are vectorized) may result in incorrect behavior. If you need to write to the tensors, please clone them first.

Many PyTorch functions, which return a view of a tensor, are internally implemented with this function. Those functions, like torch.Tensor.expand(), are easier to read and are therefore more advisable to use.

Parameters
• input (Tensor) – the input tensor.

• size (tuple or ints) – the shape of the output tensor

• stride (tuple or ints) – the stride of the output tensor

• storage_offset (int, optional) – the offset in the underlying storage of the output tensor

Example:

>>> x = torch.randn(3, 3)
>>> x
tensor([[ 0.9039,  0.6291,  1.0795],
[ 0.1586,  2.1939, -0.4900],
[-0.1909, -0.7503,  1.9355]])
>>> t = torch.as_strided(x, (2, 2), (1, 2))
>>> t
tensor([[0.9039, 1.0795],
[0.6291, 0.1586]])
>>> t = torch.as_strided(x, (2, 2), (1, 2), 1)
tensor([[0.6291, 0.1586],
[1.0795, 2.1939]])