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46 Commits

Author SHA1 Message Date
Nikita Shulga
a9b0a921d5 Disable avoid-non-const-global-variables lint check (#62008) 
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
 2021-07-22 18:04:40 -07:00
Nikita Shulga
3a66a1cb99 [clang-tidy] Exclude cppcoreguidelines-avoid-magic-numbers (#57841) 
Summary:
Add cppcoreguidelines-avoid-magic-numbers exclusion to clang-tidy
Remove existing nolint warnings using following script:
```
for file in `git ls-files | grep -v \.py`; do gsed '/^ *\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)/d' -i  $file; done
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/57841

Reviewed By: samestep

Differential Revision: D28295045

Pulled By: malfet

fbshipit-source-id: 7c6e8d1213c9593f169ed3df6a916498f1a97163
 2021-05-07 20:02:33 -07:00
Nikita Shulga
4cb534f92e Make PyTorch code-base clang-tidy compliant (#56892) 
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
 2021-04-28 14:10:25 -07:00
Will Feng
a54416d208 [C++ API] Remove deprecated torch::nn::BatchNorm / FeatureDropout / modules_ordered_dict and torch::nn::init::Nonlinearity / FanMode (#34508) 
Summary:
This PR is BC-breaking in the following way:
- The deprecated `torch::nn::BatchNorm` is removed in favor of `torch::nn::BatchNorm{1,2,3}d`
- The deprecated `torch::nn::FeatureDropout` is removed in favor of `torch::nn::Dropout{2,3}d`
- The deprecated `torch::nn::modules_ordered_dict` is removed. User should do `Sequential sequential({{"m1", MyModule(1)}, {"m2", MyModule(2)}})` instead.
- The deprecated `torch::nn::init::Nonlinearity` is removed, in favor of the following enums:
    - `torch::kLinear`
    - `torch::kConv1D`
    - `torch::kConv2D`
    - `torch::kConv3D`
    - `torch::kConvTranspose1D`
    - `torch::kConvTranspose2D`
    - `torch::kConvTranspose3D`
    - `torch::kSigmoid`
    - `torch::kTanh`
    - `torch::kReLU`
    - `torch::kLeakyReLU`
- The deprecated `torch::nn::init::FanMode` is removed, in favor of the following enums:
    - `torch::kFanIn`
    - `torch::kFanOut`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34508

Differential Revision: D20351601

Pulled By: yf225

fbshipit-source-id: cca0cd112f29a31bb023e348ca8f82780e42bea3
 2020-03-12 10:09:58 -07:00
nicolov
e77abb9a5b Normalize reward-to-go in C++ actor-critic (#33550) 
Summary:
Comparing to the [Python implementation](https://github.com/pytorch/examples/blob/master/reinforcement_learning/actor_critic.py), it seems like the tensor of normalized reward-to-go is computed but never used. Even if it's just an integration test, this PR switches to the normalized version for better convergence.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33550

Differential Revision: D20024393

Pulled By: yf225

fbshipit-source-id: ebcf0fee14ff39f65f6744278fb0cbf1fc92b919
 2020-02-21 09:19:39 -08:00
Pavel Belevich
27afac2134 C++ API parity: Dropout, Dropout2d, Dropout3d 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/29761

Test Plan: Imported from OSS

Differential Revision: D18530820

Pulled By: pbelevich

fbshipit-source-id: 9d351561692f7de099d7c6aaf2ecb930b5c867e9
 2019-11-15 20:32:06 -08:00
Will Feng
e8087a3060 Change C++ API test files to only include torch/torch.h (#27067) 
Summary:
One of the purposes of the C++ API tests in `test/cpp/api/` should be to check that including `torch/torch.h` is a sufficient prerequisite for using all C++ frontend features. This PR change ensures that.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27067

Differential Revision: D17856815

Pulled By: yf225

fbshipit-source-id: 49c057bd807b003e4a00f6ba73131d763a0f277a
 2019-10-10 09:46:29 -07:00
Peter Goldsborough
8232bd526f Move isnan to C++ (#15722) 
Summary:
Wanted to use `Tensor.isnan` in C++, figured it'd be nice to have, so I made it into a tiny native function.

gchanan ezyang apaszke
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15722

Differential Revision: D13591315

Pulled By: goldsborough

fbshipit-source-id: a78bd22101fde87a0257f759b9bfcf3b4208f5fa
 2019-01-08 10:42:33 -08:00
Peter Goldsborough
8311bbee7f Fix Windows build and test in CI (#11716) 
Summary:
This PR adds Windows support for the C++ frontend. A lot of declarations were missing `TORCH_API` macros, and lots of code just did not compile on MSVC.

ebetica ezyang orionr
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11716

Reviewed By: orionr

Differential Revision: D13038253

Pulled By: goldsborough

fbshipit-source-id: c8e5a45efd26117aeb99e768b56fcd5a89fcb9f8
 2018-11-13 16:35:54 -08:00
Peter Goldsborough
332a7db35e Use MNIST dataset in C++ integration test (#13737) 
Summary:
We have an MNIST reader in the C++ data API, so we can get rid of the custom one currently implemented in the integration tests.

ebetica
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13737

Differential Revision: D12990936

Pulled By: goldsborough

fbshipit-source-id: 125a1910ec91d53dbf121570fc9eec6ccfba0477
 2018-11-09 09:55:02 -08:00
Peter Goldsborough
393ad6582d Use torch:: instead of at:: in all C++ APIs (#13523) 
Summary:
In TorchScript and C++ extensions we currently advocate a mix of `torch::` and `at::` namespace usage. In the C++ frontend I had instead exported all symbols from `at::` and some from `c10::` into the `torch::` namespace. This is far, far easier for users to understand, and also avoid bugs around creating tensors vs. variables. The same should from now on be true for the TorchScript C++ API (for running and loading models) and all C++ extensions.

Note that since we're just talking about typedefs, this change does not break any existing code.

Once this lands I will update stuff in `pytorch/tutorials` too.

zdevito ezyang gchanan
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13523

Differential Revision: D12942787

Pulled By: goldsborough

fbshipit-source-id: 76058936bd8707b33d9e5bbc2d0705fc3d820763
 2018-11-06 14:32:25 -08:00
Christian Puhrsch
a9e6a673ae Remove caffe2::Tensor::capacity_nbytes, at::Tensor::to##name##Data, (#11876) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11876

Modern C++ api instead of macros, item() is aligned with Python frontend. caffe2::Tensor::capacity_nbytes is effecitvely unused and confusing w.r.t. caffe2::Tensor::nbytes().

codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCByte   "item<uint8_t>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCLong   "item<int64_t>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCInt    "item<int32_t>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCDouble "item<double>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCFloat  "item<float>"

codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toByteData   "data<uint8_t>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toLongData   "data<int64_t>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toIntData    "data<int32_t>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toDoubleData "data<double>"
codemod -d caffe2           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toFloatData  "data<float>"

codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCByte   "item<uint8_t>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCLong   "item<int64_t>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCInt    "item<int32_t>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCDouble "item<double>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCFloat  "item<float>"

codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toByteData   "data<uint8_t>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toLongData   "data<int64_t>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toIntData    "data<int32_t>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toDoubleData "data<double>"
codemod -d hphp           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toFloatData  "data<float>"

codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCComplexDouble "item<std::complex<double>>"

codemod -d tc           --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCFloat  "item<float>"

Reviewed By: ezyang

Differential Revision: D9948572

fbshipit-source-id: 70c9f5390d92b82c85fdd5f8a5aebca338ab413c
 2018-09-24 10:40:10 -07:00
Peter Goldsborough
825181ea9d Rewrite C++ API tests in gtest (#11953) 
Summary:
This PR is a large codemod to rewrite all C++ API tests with GoogleTest (gtest) instead of Catch.

You can largely trust me to have correctly code-modded the tests, so it's not required to review every of the 2000+ changed lines. However, additional things I changed were:

1. Moved the cmake parts for these tests into their own `CMakeLists.txt` under `test/cpp/api` and calling `add_subdirectory` from `torch/CMakeLists.txt`
2. Fixing DataParallel tests which weren't being compiled because `USE_CUDA` wasn't correctly being set at all.
3. Updated README

ezyang ebetica
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11953

Differential Revision: D9998883

Pulled By: goldsborough

fbshipit-source-id: affe3f320b0ca63e7e0019926a59076bb943db80
 2018-09-21 21:28:16 -07:00
Gregory Chanan
e00fb69b25 Use CATCH prefix to avoid name conflicts with Caffe2. 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/11780

Differential Revision: D9889925

Pulled By: gchanan

fbshipit-source-id: 5eca849c36ced00b8ae7482b7945b445a3e1687e
 2018-09-18 08:12:45 -07:00
Peter Goldsborough
f0a284502a Document BatchNorm and update default behavior (#11484) 
Summary:
This PR:

1. Documents `BatchNorm`,
2. Makes a number of API changes after reconsidering some quirks:
    1. The default value for the `stateful` parameter used to be `false`, but the most common usage of `BatchNorm` out of the wild is certainly stateful, and the default in Python is also statefulness. So we change the default to stateful.
    2. The `pure_forward` function used to use the internal running mean and variance variables instead of the ones supplied to that function call when `stateful` was true, which certainly seems odd. When you call `pure_forward` you would certainly expect the values you pass explicitly to be used. This is now fixed.
3. Adds tests for `BatchNorm`, finally.

ebetica apaszke ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11484

Reviewed By: pjh5

Differential Revision: D9779618

Pulled By: goldsborough

fbshipit-source-id: 59ba760e085c01454b75644b24b22317b688e459
 2018-09-12 09:09:53 -07:00
Peter Goldsborough
d95fedb436 Use ATen dropout implementation in Dropout module and add FeatureDropout (#11458) 
Summary:
This PR does two things:
1. Replaces the implementation of the `Dropout` module with a call to the ATen function,
2. Replaces `Dropout2d` with a new `FeatureDropout` module that shall take the place of `Dropout2d` and `Dropout3d`. I contemplated calling it `Dropout2d` and making `Dropout3d` an alias for it, but similar to our decision for `BatchNorm{1,2,3}d` (c.f. https://github.com/pytorch/pytorch/pull/9188), we can deviate from Python PyTorch in favor of the ideal-world solution, which is to have a single module, since both actually just call `feature_dropout`.

I also replaced the implementation of `dropout3d`  with a call to `dropout2d` in Python. The code is the same and it's easier for developers to parse than having to manually match the tokens to make sure it's really 100% the same code (which it is, if I matched the tokens correctly).

ebetica ezyang SsnL
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11458

Differential Revision: D9756603

Pulled By: goldsborough

fbshipit-source-id: fe847cd2cda2b6da8b06779255d76e32a974807c
 2018-09-11 20:16:12 -07:00
Edward Yang
6bdbad93b9 Refactor Device to not depend on Backend. (#10478) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10478

- Removed Backend constructor from Device, and fixed all
  use-sites to use DeviceType::CPU instead of kCPU, or
  use a new function backendToDeviceType to perform
  the conversion.
- New method device_type() on Type; it gives you the
  underlying device type, e.g., CPU for SparseCPU.
- We add backward compatibility for kCPU/kCUDA uses,
  by introducing a new special type which is implicitly
  convertible to both DeviceType and Backend.  As long as
  you don't define a function that's overloaded on both
  DeviceType and Backend (but not on BackendOrDeviceType),
  the implicit conversions will ensure that uses
  of at::Device(at::kCPU) keep working. We fixed use-sites in
  the library, but did NOT fix sites in the test code, so that
  we can exercise this BC code.

Reviewed By: Yangqing

Differential Revision: D9301861

fbshipit-source-id: 9a9d88620500715c7b37e655b4fd761f6dd72716
 2018-08-18 17:39:14 -07:00
Peter Goldsborough
2e0dd86903 Make torch::Tensor -> at::Tensor (#10516) 
Summary:
This PR removes the `using Tensor = autograd::Variable;` alias from `torch/tensor.h`, which means `torch::Tensor` is now `at::Tensor`. This PR fixes up some last uses of `.data()` and tidies up the resulting code. For example, I was able to remove `TensorListView` such that code like

```
auto loss = torch::stack(torch::TensorListView(policy_loss)).sum() +
    torch::stack(torch::TensorListView(value_loss)).sum();
```

is now

```
auto loss = torch::stack(policy_loss).sum() + torch::stack(value_loss).sum();
```

CC jgehring

ebetica
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10516

Differential Revision: D9324691

Pulled By: goldsborough

fbshipit-source-id: a7c1cb779c9c829f89cea55f07ac539b00c78449
 2018-08-15 21:25:12 -07:00
Peter Goldsborough
ae44a6b5e3 Fix Sequential::clone() (#9372) 
Summary:
I noticed that `Sequential::clone()` does not work. This is because `Sequential` does not use `reset()` which is normally where modules have to initialize and register its submodules. Further, this is because of the way `Sequential` allows its modules to be passed in the constructor, which doesn't work with `reset()` (since it does "late" initialization).

I've added some better error messages inside `Cloneable::clone()` which makes this kind of mistake clearer for other users, and tests for `Sequential::clone()`.

I also had to give `AnyModule` a deep `clone()` method.

ebetica ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9372

Differential Revision: D8865189

Pulled By: goldsborough

fbshipit-source-id: b81586e0d3157cd3c4265b19ac8dd87c5d8dcf94
 2018-07-16 21:53:42 -07:00
Peter Goldsborough
9ce15173fb Move _cudnn_init_dropout_state to TensorOptions and enable cuDNN dropout in C++ API RNNs (#9012) 
Summary:
The goal of this PR was to add support for dropout descriptors in the C++ API's RNN class.
The end result is a 4x-5x speedup for our RNN integration tests since they can now use cuDNN instead of autograd when dropout is set.

To achieve this, I had to move `_cudnn_init_dropout_state` to the `TensorOptions` API.

I also fixed a bug around `RNN::cuda()` not flattening parameters for cuDNN.

ebetica ezyang
Closes https://github.com/pytorch/pytorch/pull/9012

Reviewed By: pjh5

Differential Revision: D8689786

Pulled By: goldsborough

fbshipit-source-id: 44fb191f5a38e41c4ded5417306b5bbc012cd56c
 2018-06-29 17:25:23 -07:00
Peter Goldsborough
f0772c0ab2 Replace max_pool with max_pool_with_indices (#8946) 
Summary:
Re-push from https://github.com/pytorch/pytorch/pull/8892
Closes https://github.com/pytorch/pytorch/pull/8946

Differential Revision: D8666862

Pulled By: goldsborough

fbshipit-source-id: 44cd3d63d347316818a7b0f5f89fce8ff7486736
 2018-06-28 16:10:08 -07:00
Peter Goldsborough
03d0a70a4d Set random seed at the start of C++ tests (#8903) 
Summary:
Sets the random seed at the start of C++ tests so that everything is super deterministic.

I made sure we only generate random values from torch instead of `std::`, so that this seed always applies. I.e. I do:

```
torch::randint(2, {2}, at::kInt64)
```

instead of

```
std::rand() % 2
```

Also got rid of the tests that test the random seeding, since it would interfere here. And the test is not useful since we just use ATen's seeding mechanism, which should work.

Fixes  #7288 #7286 #7289

ebetica ezyang
Closes https://github.com/pytorch/pytorch/pull/8903

Differential Revision: D8667269

Pulled By: goldsborough

fbshipit-source-id: a833e86e156d5e68dae8c53a4b1c433cb0608b6c
 2018-06-27 20:09:46 -07:00
Peter Goldsborough
fef9a66d08 Use torch:: instead of at:: (#8911) 
Summary:
This PR is the final step to making `torch::` the only  namespace users of the C++ API ever see. Basically, I did:

``` cpp

namespace torch {
using namespace at;
}
```

And then changed `torch::` to `at::` almost everywhere. This worked surprisingly well out of the box. So users can now write `torch::relu`  and `torch::log_softmax` and `torch::conv2d` instead of having to know when to use `at::` and when `torch::`. This is happy!

Another thing I did was to have `using Dtype = at::ScalarType`, which will be the eventual name anyway.

ebetica ezyang apaszke zdevito
Closes https://github.com/pytorch/pytorch/pull/8911

Reviewed By: ezyang

Differential Revision: D8668230

Pulled By: goldsborough

fbshipit-source-id: a72ccb70fca763c396c4b0997d3c4767c8cf4fd3
 2018-06-27 14:42:01 -07:00
Orion Reblitz-Richardson
9ec0a2aef4 fbshipit-source-id: ba600fcd2b5cefc7621357bdeb05e24cea02e5af 2018-06-27 04:50:56 -07:00
Peter Goldsborough
290d20b094
Replace max_pool with max_pool_with_indices (#8892) 
* Create max_poolXd_with_indices

* Match ATen names in ONNX symbolic
 2018-06-26 17:09:30 -07:00
Peter Goldsborough
55757357b2
[C++ API] Better forward methods (#8739) 
* Better forward methods in C++ API

capitalize error message in test_torch.test_flatten

Support for operator()

* Add operator() to Functional

* Get rid of SigmoidLinear

* Add BoundFunction to FunctionalImpl

* Remove macro from conv because it makes errors more nasty
 2018-06-26 13:23:16 -07:00
Peter Goldsborough
1f36caceb2
[C++ API] Rework optimization package (#8815) 
* Rework optim folder

* Removed TORCH_OPTIMIZER_CLASS macro

* Got rid of CRTP/Impl

* Removed TORCH_AUTOGRAD_KWARG

* Differentiate between Optimizer and LossClosureOptimizer

* Make Optimizers parameters based instead of model based

* Allow construction of optimizer from arbitrary vector

* Added test for zero grad

* Added test for external parameter vectors

* Now comparing against baseline values

* Documentation

* Post rebase fixes

* Different strategy for creating and accessing buffers in optimizers

* Fix member ordering
 2018-06-26 10:13:14 -07:00
Peter Goldsborough
47492ed451
[C++ API] Bag of fixes (#8843) 
* Bag of fixes

* Rename tensor_range.h to tensor_list_view.h

* Post rebase fixes

* Rename torch::tensor namespace to torch::tensors due to name conflict

* Avoid recursion in Module::to
 2018-06-25 21:11:49 -07:00
Peter Goldsborough
521f5111ad
[C++ API] Use torch::Tensor instead of at::Tensor/Variable mix (#8680) 
* Use torch::Tensor instead of at::Tensor/Variable mix

* TensorRange -> TensorListView
 2018-06-24 19:03:39 -07:00
Peter Goldsborough
d46312fd15
Create at::from_blob (#8640) 2018-06-19 17:00:28 -07:00
Peter Goldsborough
a2dd707031
[C++ API] Create fixed width dtypes in torch:: namespace (#8639) 
* Create fixed width dtypes in torch:: namespace

* Make kByte -> kUInt8
 2018-06-19 12:40:58 -07:00
Peter Goldsborough
271406f276
[C++ API] Make pImpl easy to use in modules to enable happy reference semantics (#8347) 
* Created TORCH_MODULE macro

Rewrote Linear

Rewrote Dropout and added default constructor to TORCH_MODULE macro

Turned TORCH_MODULE contens into a proper base class

Added some documentation

Got rid of the old Dropout module

Got rid of the old Embedding module

Got rid of the old BatchNorm module

Got rid of the old Conv module

Fixing optimizers

Rebase

Removed old RNN modules and the TORCH_ATTR macro

Removed temporary P:: namespace

Added cloning behavior to all modules

Got rid of some get() calls

self review nits

Remove noexcept from ModuleHolder methods that can throw

Remove spaces

Add missing override to reset() methods

Added examples to documentation in pimpl.h

* Post rebase fixes
 2018-06-18 19:45:53 -07:00
Peter Goldsborough
372d1d6735
Create ATen tensors via TensorOptions (#7869) 
* Created TensorOptions

Storing the type in TensorOptions to solve the Variable problem

Created convenience creation functions for TensorOptions and added tests

Converted zeros to TensorOptions

Converted rand to TensorOptions

Fix codegen for TensorOptions and multiple arguments

Put TensorOptions convenience functions into torch namespace too

All factory functions except *_like support TensorOptions

Integrated with recent JIT changes

Support *_like functions

Fix in place modification

Some cleanups and fixes

Support sparse_coo_tensor

Fix bug in Type.cpp

Fix .empty calls in C++ API

Fix bug in Type.cpp

Trying to fix device placement

Make AutoGPU CPU compatible

Remove some auto_gpu.h uses

Fixing some headers

Fix some remaining CUDA/AutoGPU issues

Fix some AutoGPU uses

Fixes to dispatch_tensor_conversion

Reset version of new variables to zero

Implemented parsing device strings

Random fixes to tests

Self review cleanups

flake8

Undo changes to variable.{h,cpp} because they fail on gcc7.2

Add [cuda] tag to tensor_options_cuda.cpp

Move AutoGPU::set_index_from into .cpp file because Windows is stupid and sucks

Fix linker error in AutoGPU.cpp

Fix bad merge conflict in native_functions.yaml

Fixed caffe2/contrib/aten

Fix new window functions added to TensorFactories.cpp

* Removed torch::TensorOptions

Added code to generate wrapper functions for factory methods

Add implicit constructor from Backend to TensorOptions

Remove Var() from C++ API and use torch:: functions

Use torch:: functions more subtly in C++ API

Make AutoGPU::set_device more exception safe

Check status directly in DynamicCUDAHooksInterface

Rename AutoGPU to DeviceGuard

Removed set_requires_grad from python_variables.h and warn appropriately in Variable::set_requires_grad

remove python_default_init: self.type()

Add back original factory functions, but with deprecation warnings

Disable DeviceGuard for a couple functions in ATen

Remove print statement

Fix DeviceGuard construction from undefined tensor

Fixing CUDA device compiler issues

Moved as many methods as possible into header files

Dont generate python functions for deprecated factories

Remove merge conflict artefact

Fix tensor_options_cuda.cpp

Fix set_requires_grad not being checked

Fix tensor_new.h

TEMPORARILY put some methods in .cpp files to see if it solves issues on windows and mac

Fix bug in DeviceGuard.h

Missing includes

TEMPORARILY moving a few more methods into .cpp to see if it fixes windows

Fixing linker errors

* Fix up SummaryOps to use new factories

Undo device agnostic behavior of DeviceGuard

Use -1 instead of optional for default device index

Also move DeviceGuard methods into header

Fixes around device index after optional -> int32_t switch

Fix use of DeviceGuard in new_with_tensor_copy

Fix tensor_options.cpp

* Fix Type::copy(

* Remove test_non_float_params from ONNX tests

* Set requires_grad=False in ONNX tests that use ints

* Put layout/dtype/device on Tensor

* Post merge fixes

* Change behavior of DeviceGuard to match AutoGPU

* Fix C++ API integration tests

* Fix flip functions
 2018-06-16 00:40:35 -07:00
Peter Goldsborough
4a80755834
Split up detail.h (#7836) 2018-05-30 08:55:34 -07:00
Peter Goldsborough
28b1a3852c
Add backward() to Tensor and Variable (#7774) 
* Add backward() to Tensor and Variable

* Add at:: in front of Tensor

* Trying to not move optional to appease windows?

* Move implementation into cpp file

* Undo some formatting changes
 2018-05-24 17:31:41 -07:00
Peter Goldsborough
b12164005f
[C++ API] Remove virtual forward and implement Sequential based on Any(Module) (#7508) 
* Remove virtual forward

* Rebase
 2018-05-24 12:46:51 -07:00
Will Feng
60745b3380 Revert #7750 and #7762 to fix Windows CI on master (#7772) 
* Revert "Add missing brace (#7762)"

This reverts commit ea27c5af50.

* Revert "[C++ API] Add backward() to Tensor and Variable  (#7750)"

This reverts commit 1e2762796f.
 2018-05-22 15:42:52 -07:00
Peter Goldsborough
1e2762796f
[C++ API] Add backward() to Tensor and Variable (#7750) 
* Add backward() to Tensor and Variable

* Added a couple tests
 2018-05-22 10:43:04 -07:00
Peter Goldsborough
549b4069bb
[C++ API] Using new registration mechanism (#7663) 
* Using new registration mechanism

* Fix signature of param() in module.cpp

* Remove ParameterList

* Fix tests
 2018-05-21 17:59:21 -07:00
Peter Goldsborough
cba19e59ca
[C++ API] Implement builder style construction (#7597) 
* Implemented fused builder based construction mechanism

* "weights" -> "weight"

* Use int64_t instead of size_t everywhere in RNN

* Extracted Conv::ExpandingSize into its own thing

* Rename TORCH_PARAMETER to TORCH_ATTR

* Added documentation

* Fix weight names in batchnorm module
 2018-05-17 17:10:15 -04:00
Peter Goldsborough
3414475653
[C++ API] Remove initialize_* functions (#7517) 
* Remove initialize_ functions

* Fix clone() to recursively clone children

* Small codemove
 2018-05-14 18:24:58 -07:00
Peter Goldsborough
6ada041b31 Some small fixes in C++ API (#7510) 2018-05-11 18:56:53 -07:00
Peter Goldsborough
3023dd25f3 Use set_type to implement type conversions in C++ API (#7408) 
* Use set_type to implement .cuda() in C++ API

* Change C++ module parameter types in place

* Fix bug where batchnorm state was not moved to CUDA
 2018-05-09 17:01:19 -04:00
Peter Goldsborough
8fce8673bb
Rename Container to Module in autogradpp and reorg code (#7304) 
* Rename autograd namespace to torch and change torch.h into python.h

* Pave the way for torch::nn::Module

* Reorganize module code structure

* Undo ONNX update

* Remove sleef submodule
 2018-05-07 14:45:00 -07:00
Peter Goldsborough
67d0d14908
Rename autograd namespace to torch and change torch.h into python.h (#7267) 
* Rename autograd namespace to torch and change torch.h into python.h

* Include torch.h instead of python.h in test/cpp/api

* Change some mentions of torch.h to python.h in C++ extensions

* Set paths directly, without find_path
 2018-05-04 08:04:57 -07:00
Peter Goldsborough
afe3c2688f Update C++ API tests to use Catch2 (#7108) 
* Update C++ API tests to use Catch2

* Update download_mnist.py to be less verbose
 2018-04-30 21:36:35 -04:00