Torchani

****Please update your PyTorch to latest nightly build!****

Changes

- Add support for indexing species with periodic table element index. (396, 399)
- To convert from the periodic table index to the 0, 1, 2, 3, ... index, checkout `torchani.SpeciesConverter` (396)
- To switch to the periodic table index for builtin models, set the argument `periodic_table_index=True` when constructing. (399)
- Submodules of `ANIModel` can now have a name. To use this feature, pass an `OrderedDict` instead of a `list` to its constructor. (398)
- `torchani.utils.hessian` is now supported by JIT. (397)
- Documentation improvements (400, 401, 402)

****Please update your PyTorch to latest nightly build!****

Highlights

- Python 2 support is removed (370, 390)
- Ignite helper is removed (354, 364)
- AEV cacher is removed (361)
- `EnergyShifter` now always use float64 as datatype (338, 347)
- The API for the ASE interface has been simplified (386)

Python 3

Previously we were supporting Python 2, which limits the language feature we could use. Now PyTorch has started dropping Python 2 support on their nightly builds. So TorchANI also dropped Python 2 support, which enables lots of new language features to improve our code quality:
- Use `` operator for matrix multiplication (371)
- Type annotation is now in Python 3 style (372, 373, 374, 375)

TorchScript Support

In TorchANI 1.0, we added TorchScript support. But due to bugs/lacking features in PyTorch, we had to make many workarounds, which introduce some problems. PyTorch has improved a lot since then, so we remove some of the workarounds to make TorchANI great again:
- Ensemble size is no longer hardcoded to 8 (352)
- `enumerate` is now correctly supported by JIT (358)
- Tensor factories like `new_zeros` are now correctly supported by JIT (353, 362)
- Subclassing `ModuleList` is now supported by JIT (385)
- Bugs on the type inference of `torch.arange` is now fixed (357)
- `__constants__` is deprecated by torch.jit (378)

Bug Fixes and Miscellaneous Improves
- Fix bugs on CUDA support (341, 350)
- Fix bug in discarding outlier energy conformers (334, 340)
- Mention what unit is used in docs (389)
- Fix the homepage URL in PyPI page (363)
- Modules now return a named tuple instead of a tuple (380)
- Support `nan` as a value in NeuroChem parser (383)
- Remove warning on don't use conda to install PyTorch, because this is no longer a problem (366)
- Allow passing `pbc` and `cell` to `torchani.nn.Sequential` (386)
- Code for analytical stress calculation has been improved (387)
- Use `torch.triu_indices` to simplify code (367, 368)

This is just a dummy release that triggers deployment. See for https://github.com/aiqm/torchani/releases/tag/1.0 changelog.

- TorchScript compatibility has been added to export TorchANI models through `torch.jit`. Users can now use C++ API for deployments. (303, 305, 306, 307, 308, 326, 327).
- Some APIs are changed due to the compatibility issue with TorchScript:
- `AEVComputer` input is changed, `cell` and `pbc` are now keyword arguments. (303)
- `Ensemble` is now hardcoded to have a size of 8. (307)
- `torchani.nn.Sequential` is added to include type annotations for JIT. (307)
- An example of how the models can be exported using PyTorch JIT has been provided (328).
- All the unit tests and checks have been moved to GitHub Actions. (309, 310, 313, 314, 317, 318, 319, 322, 323, 324)
- Added a script for profiling the training on NVIDIA GPUs using [Nsight](https://developer.nvidia.com/nsight-visual-studio-edition) System (#325)
- Bug fixed in the dimensions of `self_energies` for a dataset containing only one element (302)

- The package name of PyTorch has changed from `torch-nightly` to `torch`, we update it respectively (295, 294)
- Add new experimental `data` API that has much less memory usage and much better performance (284, 299)
- Example files now reproduce NeuroChem results after taking out the outlier energy conformers (287)
- Accelerate angular AEV computation and reduce memory cost (290)
- Remove all large files and stop using `git-lfs` (289)

- Support PyTorch new `torch.bool` datatype. (278)
**Warning: Boolean tensor is a breaking change introduced in PyTorch, TorchANI has to be updated to run on the latest PyTorch, otherwise it will produce wrong results.**
- Improve TorchANI to be more close to NeuroChem. Update examples respectively. Also, provide helper functions. (283, 282, 280, 279, 275, 261, 259, 255, 245, 263)
- Add example for energy/force training. (249, 240, 238, 233)
- Bug fixed in AdamW implementation. (261)
- Dataset related API has changed, see the new API doc for detail. Its implementations are also improved. (230, 231, 232, 236, 237, 250, 257, 272)
- Builtin models API has changed, and implementation improved. (252, 266)
- Fix a bug of not having `torchani.data` when `ignite` is not installed. (256)