Summary:
This PR refactors RNN / GRU / LSTM layers in C++ API to exactly match the implementation in Python API.
**BC-breaking changes:**
- Instead of returning `RNNOutput`, RNN / GRU forward method now returns `std::tuple<Tensor, Tensor>`, and LSTM forward method now returns `std::tuple<Tensor, std::tuple<Tensor, Tensor>>`, matching Python API.
- RNN / LSTM / GRU forward method now accepts the same inputs (input tensor and optionally hidden state), matching Python API.
- RNN / LSTM / GRU now has `forward_with_packed_input` method which accepts `PackedSequence` as input and optionally hidden state, matching the `forward(PackedSequence, ...)` variant in Python API.
- In `RNNOptions`
- `tanh()` / `relu()` / `activation` are removed. Instead, `nonlinearity` is added which takes either `torch::kTanh` or `torch::kReLU`
- `layers` -> `num_layers`
- `with_bias` -> `bias`
- In `LSTMOptions`
- `layers` -> `num_layers`
- `with_bias` -> `bias`
- In `GRUOptions`
- `layers` -> `num_layers`
- `with_bias` -> `bias`
The majority of the changes in this PR focused on refactoring the implementations in `torch/csrc/api/src/nn/modules/rnn.cpp` to match the Python API. RNN tests are then changed to reflected the revised API design.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34322
Differential Revision: D20311699
Pulled By: yf225
fbshipit-source-id: e2b60fc7bac64367a8434647d74c08568a7b28f7
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
Summary:
One example in the current docs for `torch::nn::ModuleList` doesn't compile, and this PR fixes it.
Fixes https://github.com/pytorch/pytorch/issues/32414.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34463
Test Plan: Imported from GitHub, without a `Test Plan:` line.
Differential Revision: D20331120
Pulled By: yf225
fbshipit-source-id: 50bb078fe1a900c9114d5434e92dc40ee13b52bf
Summary:
This PR changes the implementation of C++ Conv{1,2,3}d layers to exactly match the Python version, and add F::conv{1,2,3}d functionals. For more thorough testing, I will rely on the parity test mechanism which uses values from `common_nn.py` to generate the inputs and options that we are interested in testing.
This PR is BC-breaking in the following way:
In `Conv{1,2,3}dOptions`:
- `with_bias` is renamed to `bias`.
- `input_channels` is renamed to `in_channels`.
- `output_channels` is renamed to `out_channels`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/28917
Differential Revision: D18471526
Pulled By: yf225
fbshipit-source-id: 7a33f60654ad93cc2e043245e7ff9e0ef9da15b3
Summary:
Add torch::nn::BatchNorm1d function/module support for the C++ API.
torch::nn::BatchNorm{2,3}d will be added after this PR is merged.
Related Issue: https://github.com/pytorch/pytorch/issues/25883
Reviewer: yf225
I would like to discuss about below items.
* Necessity of `num_batches_tracked` in `BatchNormImplBase`
* `num_batches_tracked` is needed to calculate `momentum` when we do not feed `momentum` argument in Python API. But in C++ API, `momentum` argument has a default value.
* `num_batches_tracked` is only used for counting up `BatchNorm1d::foward()` call. I think it is no necessary for user anymore.
* The design of `BatchNorm{1,2,3}dOptions`
* We have already `BatchNormOptions` used for deprecated `BatchNorm` module. However, it is hard to use it for `BatchNorm{1,2,3}dOptions` because of the arguments disagreement of each modules.
* In this PR, I introduce `BatchNormOptionsv2` template class for the `BatchNorm{1,2,3}dOptions`. But I'm not sure this design is good or not.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/28176
Differential Revision: D18196843
Pulled By: yf225
fbshipit-source-id: 667e2b5de4150d5776c41b9088c9e6c2ead24cd4
Summary:
added more variables to EmbeddingOptions and updated EmbeddingImpl reset, forward functions. Also added EmbeddingBag.
-----
This PR is BC-breaking in the following way:
Previously, `EmbeddingOptions` supports `count` and `dimension` as options arguments. After this PR, they are renamed to `num_embeddings` and `embedding_dim` respectively.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26358
Differential Revision: D17714337
Pulled By: yf225
fbshipit-source-id: f9f969c68e4bece106b92f8e2e02ac39c8455fb7
Summary:
Here is a PR adding ```ModuleList``` to ```modules.h``` so that it can be used by including ```torch/torch.h```.
yf225 edit: Closes https://github.com/pytorch/pytorch/issues/25293.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25346
Differential Revision: D17115013
Pulled By: yf225
fbshipit-source-id: 38a1848b9a8272fa411865dfc83b76d10c5789a0
