mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
5b78a5eadb
Summary: #19975 was separated by 2 PRs. This one: Introduce MemoryFormat argument to the `x.is_contiguous(memory_format=torch.channels_last)` and to the `y = x.contiguous(memory_format=torch.channels_last)` functions. At this moment both functions just operate with strides and doesn't store any tensor state. (Original RFC #19092) ----- Expands functionality of two tensor functions `.is_contiguous` and `.contiguous` (both python and c++ api). Note: We had several complaints about `.to(memory_format)` function, and decided not to support it. 1. `.contiguous` now support optional keyword-only argument - `memory_format`, which can be either `torch.contiguous_format` or `torch.channels_last`. - Using `torch.contiguous_format` will preserve existing `.contiguous()` behavior. - Calling `x.contiguous(memory_format=torch.channels_last)` returns new tensor which maintain same semantical layout (NCHW), but have different memory allocation pattern. `x.contiguous(memory_format=torch.channels_last)` expects input tensor to be 3d, 4d or 5d; and fails otherwise. 2. `.is_contiguous` now support optional keyword-only argument - `memory_format`, which can be either `torch.contiguous_format` or `torch.channels_last`. - `x.is_contiguous(memory_format=torch.contiguous_format)` preserves same functionality as `x.is_contiguous()` and remains unchanged. - `x.is_contiguous(memory_format=torch.channels_last)` returns true if A) input tensor is contiguous in memory AND B) allocated in the memory in NWHC (or similar for 3d,5d) format. Note: By the end of the phase one `x.is_contiguous(memory_format=torch.channels_last)` will calculate state of the Tensor on every call. This functionality going to be updated later. Pull Request resolved: https://github.com/pytorch/pytorch/pull/20455 Differential Revision: D15341577 Pulled By: VitalyFedyunin fbshipit-source-id: bbb6b4159a8a49149110ad321109a3742383185d
26 lines
547 B
C++
26 lines
547 B
C++
#pragma once
|
|
|
|
#include <torch/csrc/python_headers.h>
|
|
|
|
#include <c10/core/MemoryFormat.h>
|
|
|
|
#include <string>
|
|
|
|
const int MEMORY_FORMAT_NAME_LEN = 64;
|
|
|
|
struct THPMemoryFormat {
|
|
PyObject_HEAD
|
|
at::MemoryFormat memory_format;
|
|
char name[MEMORY_FORMAT_NAME_LEN + 1];
|
|
};
|
|
|
|
extern PyTypeObject THPMemoryFormatType;
|
|
|
|
inline bool THPMemoryFormat_Check(PyObject *obj) {
|
|
return Py_TYPE(obj) == &THPMemoryFormatType;
|
|
}
|
|
|
|
PyObject * THPMemoryFormat_New(at::MemoryFormat memory_format, const std::string& name);
|
|
|
|
void THPMemoryFormat_init(PyObject *module);
|