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 to input see detach().

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.