Add memory format argument to the `clone` operator (#27106)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27106
Adds memory_format option to the `clone` operator.
Introduce new `clone` behavior if used with `input_t.clone(memory_format=torch.preserve_format)`:
1) If tensor is non-overlapping and dense - output tensor will have the same strides as input tensor.
2) If not (1) and tensor is stored in the channels last format, output tensor going to have channels last format.
3) Output tensor is going to be contiguous in all other cases.
---
Dense tensor is the tensor that store values in a contiguous block of memory.
Non-overlapping tensor is the tensor in which elements occupy individual non-repetitive memory.
Test Plan: Imported from OSS
Differential Revision: D17699357
Pulled By: VitalyFedyunin
fbshipit-source-id: 5ae1537c2aca1abf0bf1eec4416846129c156f66
