torch.clone#
- torch.clone(input, *, memory_format=torch.preserve_format) Tensor #
Returns a copy of
input
.Note
This function is differentiable, so gradients will flow back from the result of this operation to
input
. To create a tensor without an autograd relationship toinput
seedetach()
.In addition, when
torch.preserve_format
is used: If the input tensor is dense (i.e., non-overlapping strided), its memory format (including strides) is retained. Otherwise (e.g., a non-dense view like a stepped slice), the output is converted to the dense (contiguous) format.- Parameters
input (Tensor) – the input tensor.
- Keyword Arguments
memory_format (
torch.memory_format
, optional) – the desired memory format of returned tensor. Default:torch.preserve_format
.