E3nn-jax

Latest version: v0.20.7

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0.20.7

Added
- Support for custom instructions and initializers in e3nn.flax.Linear and e3nn.haiku.Linear.

Changed
- Fix documentation build errors.

0.20.6

Added
- `e3nn.where` function
- Add optional `mask` argument in `e3nn.flax.BatchNorm`

Changed
- replace `jnp.ndarray` by `jax.Array`

0.20.5

Added
- `e3nn.ones` and `e3nn.ones_like` functions
- `e3nn.equinox` submodule

Fixed
- python 3.9 compatibility

0.20.4

Fixed
- Fix `pyproject.toml`, the documentation build was broken. Thanks to SauravMaheshkar!

Added
- Support for [`s2fft`](https://github.com/astro-informatics/s2fft) in `e3nn.to_s2grid` and `e3nn.from_s2grid`, thanks to ameya98!
- Add a special case implementation for `e3nn.scatter_mean` when `map_back and nel is not None`.

0.20.3

Added
- `e3nn.flax.BatchNorm`
- `e3nn.scatter_mean`
- Add `e3nn.utils.vmap` also directly to `e3nn` module: `e3nn.vmap`

0.20.2

Added
- `with_bias` argument to `e3nn.haiku.MultiLayerPerceptron` and `e3nn.flax.MultiLayerPerceptron`

Fixed
- Improve compilation speed and stability of `s2grid` for large `lmax` (use `is_normalized=True` in `lpmn_values`)

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