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https://github.com/saymrwulf/pytorch.git
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7b2e8c323c
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 |
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| .. | ||
| autograd | ||
| backends | ||
| contrib | ||
| csrc | ||
| cuda | ||
| distributed | ||
| distributions | ||
| for_onnx | ||
| jit | ||
| legacy | ||
| lib | ||
| multiprocessing | ||
| nn | ||
| onnx | ||
| optim | ||
| quantization | ||
| sparse | ||
| testing | ||
| utils | ||
| __config__.py | ||
| __future__.py | ||
| __init__.py | ||
| __init__.pyi.in | ||
| _classes.py | ||
| _jit_internal.py | ||
| _namedtensor_internals.py | ||
| _ops.py | ||
| _six.py | ||
| _storage_docs.py | ||
| _tensor_docs.py | ||
| _tensor_str.py | ||
| _torch_docs.py | ||
| _utils.py | ||
| _utils_internal.py | ||
| abi-check.cpp | ||
| CMakeLists.txt | ||
| custom_class.h | ||
| extension.h | ||
| functional.py | ||
| hub.py | ||
| py.typed | ||
| quasirandom.py | ||
| random.py | ||
| README.txt | ||
| script.h | ||
| serialization.py | ||
| storage.py | ||
| tensor.py | ||
Note [TH abstraction violation] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TH/THC provide some hpp headers, which are proper C++ headers rather than C headers. These headers serve double duty as *internal implementation detail* headers, whose contents should largely not be used by external clients. Ideally, we would not install these headers at all; instead, you should use public functions (in headers like `THTensor.h`, NOT `THTensor.hpp`) to manipulate these structs. However, there are a few places in torch/csrc where we violate this abstraction. They are marked with a pointer to this note. Each of those sites will have to be refactored when we refactor the guts of THTensor and related structures.