TorchANI 1.1

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)