Similar to #140425, we are making the implementation usable via header-only code sharing.
Review note: #62546 by @yanbing-j removed expm1 usage from this path. I don't know why and expm1 should be more efficient, so I've put it back. Please let me know if there is a good reason I shouldn't.
Testing: existing correctness tests should cover.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/149673
Approved by: https://github.com/cyyever, https://github.com/Skylion007
Fixes#95796
### Implementation
Adds python implementation for `nn.ZeroPad1d` and `nn.ZeroPad3d` in `torch/nn/modules/padding.py`.
Adds cpp implementation for `nn::ZeroPad1d` and `nn::ZeroPad3d` in the following 3 files, refactored with templates similarly to `nn::ConstantPad`'s implementation: <br>
- `torch/crsc/api/include/torch/nn/modules/padding.h`
- `torch/csrc/api/include/torch/nn/options/padding.h`
- `torch/csrc/api/src/nn/modules/padding.cpp`
Also added relevant definitions in `torch/nn/modules/__init__.py`.
### Testing
Adds the following tests:
- cpp tests of similar length and structure as `ConstantPad` and the existing `ZeroPad2d` impl in `test/cpp/api/modules.cpp`
- cpp API parity tests in `torch/testing/_internal/common_nn.py`
- module init tests in `test/test_module_init.py`
Also added relevant definitions in `test/cpp_api_parity/parity-tracker.md`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96295
Approved by: https://github.com/soulitzer
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69394
Modified loops in files under fbsource/fbcode/caffe2/ from the format
```
for(TYPE var=x0;var<x_max;x++)
```
to the format
```
for(const auto var: irange(xmax))
```
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
Test Plan: Sandcastle
Reviewed By: malfet
Differential Revision: D32837991
fbshipit-source-id: fc7c4f76d2f32a17a0faf329294b3fe7cb81df32
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66743
Modified loops in files under fbsource/fbcode/caffe2/ from the format
`for(TYPE var=x0;var<x_max;x++)`
to the format
`for(const auto var: irange(xmax))`
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
Test Plan: Sandcastle
Reviewed By: malfet
Differential Revision: D31705359
fbshipit-source-id: c9ea2fbc0f9cd29e97a52dcb203addc5f2abb09b
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66234
Modified loops in files under fbsource/fbcode/caffe2/ from the format
`for(TYPE var=x0;var<x_max;x++)`
to the format
`for(const auto var: irange(xmax))`
This was achieved by running r-barnes's loop upgrader script (D28874212) with some modification to exclude all files under /torch/jit and a number of reversions or unused variable suppression warnings added by hand.
bypass_size_limit
allow-large-files
Test Plan: Sandcastle
Reviewed By: ngimel
Differential Revision: D30652629
fbshipit-source-id: 0ae6c4bbbb554bad42e372792a6430e1acf15e3e
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63612
This makes Tensor inherit from a new class TensorBase, that provides a subset of Tensor that doesn't
directly depend on native_functions.yaml. Code that only includes TensorBase.h with thus not need to
be rebuilt every time someone changes an operator signature.
Making `Tensor` inherit from this class means that `const TensorBase&` parameters will be callable
with an ordinary `Tensor`. I've also made `Tensor` constructible and assignable from `TensorBase` to
minimize friction in code mixing the two types.
To help enforce that `Tensor.h` and `Functions.h` aren't accidentally included, I've added an error
into `Operators.h` if `TORCH_ASSERT_NO_OPERATORS` is defined. We can either set this in the build
system for certain folders, or just define it at the top of any file.
I've also included an example of manually special-casing the commonly used `contiguous` operator.
The inline function's slow path defers to `TensorBase::__dispatch_contiguous` which is defined in
`Tensor.cpp`. I've made it so `OptionalTensorRef` is constructible from `TensorBase`, so I can
materialize a `Tensor` for use in dispatch without actually increasing its refcount.
Test Plan: Imported from OSS
Reviewed By: gchanan
Differential Revision: D30728580
Pulled By: ezyang
fbshipit-source-id: 2cbc8eee08043382ee6904ea8e743b1286921c03
Summary:
Enable Gelu bf16/fp32 in CPU path using Mkldnn implementation. User doesn't need to_mkldnn() explicitly. New Gelu fp32 performs better than original one.
Add Gelu backward for https://github.com/pytorch/pytorch/pull/53615.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58525
Reviewed By: ejguan
Differential Revision: D29940369
Pulled By: ezyang
fbshipit-source-id: df9598262ec50e5d7f6e96490562aa1b116948bf
Summary:
As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH`
All changes but the ones to `.clang-tidy` are generated using following script:
```
for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008
Reviewed By: driazati, r-barnes
Differential Revision: D29838584
Pulled By: malfet
fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
Summary:
Fixes https://github.com/pytorch/pytorch/issues/27655
This PR adds a C++ and Python version of ReflectionPad3d with structured kernels. The implementation uses lambdas extensively to better share code from the backward and forward pass.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59791
Reviewed By: gchanan
Differential Revision: D29242015
Pulled By: jbschlosser
fbshipit-source-id: 18e692d3b49b74082be09f373fc95fb7891e1b56
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os
def get_compiled_files_list():
import json
with open("build/compile_commands.json") as f:
data = json.load(f)
files = [os.path.relpath(node['file']) for node in data]
for idx, fname in enumerate(files):
if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
return files
def run_clang_tidy(fname):
check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
changes = check_output(["git", "ls-files", "-m"])
if len(changes) == 0:
return
check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])
def main():
git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
compiled_files = get_compiled_files_list()
for idx, fname in enumerate(git_files):
if fname not in compiled_files:
continue
if fname.startswith("caffe2/contrib/aten/"):
continue
print(f"[{idx}/{len(git_files)}] Processing {fname}")
run_clang_tidy(fname)
if __name__ == "__main__":
main()
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892
Reviewed By: H-Huang
Differential Revision: D27991944
Pulled By: malfet
fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
Summary:
This PR adds a `padding_idx` parameter to `nn.EmbeddingBag` and `nn.functional.embedding_bag`. As with `nn.Embedding`'s `padding_idx` argument, if an embedding's index is equal to `padding_idx` it is ignored, so it is not included in the reduction.
This PR does not add support for `padding_idx` for quantized or ONNX `EmbeddingBag` for opset10/11 (opset9 is supported). In these cases, an error is thrown if `padding_idx` is provided.
Fixes https://github.com/pytorch/pytorch/issues/3194
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49237
Reviewed By: walterddr, VitalyFedyunin
Differential Revision: D26948258
Pulled By: jbschlosser
fbshipit-source-id: 3ca672f7e768941f3261ab405fc7597c97ce3dfc
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45667
First part of #3867 (Pooling operators still to do)
This adds a `padding='same'` mode to the interface of `conv{n}d`and `nn.Conv{n}d`. This should match the behaviour of `tensorflow`. I couldn't find it explicitly documented but through experimentation I found `tensorflow` returns the shape `ceil(len/stride)` and always adds any extra asymmetric padding onto the right side of the input.
Since the `native_functions.yaml` schema doesn't seem to support strings or enums, I've moved the function interface into python and it now dispatches between the numerically padded `conv{n}d` and the `_conv{n}d_same` variant. Underscores because I couldn't see any way to avoid exporting a function into the `torch` namespace.
A note on asymmetric padding. The total padding required can be odd if both the kernel-length is even and the dilation is odd. mkldnn has native support for asymmetric padding, so there is no overhead there, but for other backends I resort to padding the input tensor by 1 on the right hand side to make the remaining padding symmetrical. In these cases, I use `TORCH_WARN_ONCE` to notify the user of the performance implications.
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D27170744
Pulled By: jbschlosser
fbshipit-source-id: b3d8a0380e0787ae781f2e5d8ee365a7bfd49f22
Summary:
`std::vector<bool>` can not return values by reference, since they are stored as bit fields
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47279
Reviewed By: glaringlee
Differential Revision: D24705188
Pulled By: malfet
fbshipit-source-id: 96e71cc4b9881f92af3b4a508d397deab6d68174
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45377
This PR adds a C++ implementation of the TripletMarginWithDistanceLoss, for which the Python implementation was introduced in PR #43680. It's based on PR #44072, but I'm resubmitting this to unlink it from Phabricator.
Test Plan: Imported from OSS
Reviewed By: izdeby
Differential Revision: D24003973
fbshipit-source-id: 2d9ada7260a6f27425ff2fdbbf623dad0fb79405
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42037
This is to fix#41951
Test Plan: Imported from OSS
Reviewed By: yf225
Differential Revision: D22764717
Pulled By: glaringlee
fbshipit-source-id: e6da0aeb05a2356f52446e6d5fad391f2cd1cf6f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35025
This PR fixes `F::interpolate` and `torch::nn::Upsample` implementation to match the Python API implementation.
**This PR is BC-breaking in the following way:**
There are changes to `UpsampleOptions` and `InterpolateFuncOptions`:
- `size` is changed from `std::vector<int64_t>` to `c10::optional<std::vector<int64_t>>`. If you want to pass a list of `int64_t` to this argument, you must pass it as `std::vector<int64_t>`.
- `scale_factor` is changed from `std::vector<double>` to `c10::optional<std::vector<double>>`. If you want to pass a list of `double` to this argument, you must pass it as `std::vector<double>`.
**TODO**: cherry-pick this PR into v1.5 release branch.
Test Plan: Imported from OSS
Differential Revision: D20559892
Pulled By: yf225
fbshipit-source-id: ac18609e351a9f2931eaeced8966b9491b2995f7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35022
This PR fixes `AdaptiveAvgPool{2,3}d` and `AdaptiveMaxPool{2,3}d` implementation to match the Python API implementation. Particularly, `output_size` is changed to accept `c10::nullopt` in its elements, matching the Python API behavior.
**TODO**: cherry-pick this PR into v1.5 release branch.
Test Plan: Imported from OSS
Differential Revision: D20559890
Pulled By: yf225
fbshipit-source-id: ccddbd278dd39165cf1dda11fc0e49387c76dbef
