torch.rand_like
-
torch.rand_like(input, *, dtype=None, layout=None, device=None, requires_grad=False, memory_format=torch.preserve_format) → Tensor
-
Returns a tensor with the same size as
input
that is filled with random numbers from a uniform distribution on the interval .torch.rand_like(input)
is equivalent totorch.rand(input.size(), dtype=input.dtype, layout=input.layout, device=input.device)
.- Parameters
-
input (Tensor) – the size of
input
will determine size of the output tensor. - Keyword Arguments
-
-
dtype (
torch.dtype
, optional) – the desired data type of returned Tensor. Default: ifNone
, defaults to the dtype ofinput
. -
layout (
torch.layout
, optional) – the desired layout of returned tensor. Default: ifNone
, defaults to the layout ofinput
. -
device (
torch.device
, optional) – the desired device of returned tensor. Default: ifNone
, defaults to the device ofinput
. -
requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default:
False
. -
memory_format (
torch.memory_format
, optional) – the desired memory format of returned Tensor. Default:torch.preserve_format
.
-
dtype (
© 2019 Torch Contributors
Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.8.0/generated/torch.rand_like.html