CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

[0.20.6] - 2024-01-26

Added

• e3nn.where function
• Add optional mask argument in e3nn.flax.BatchNorm

Changed

• replace jnp.ndarray by jax.Array

[0.20.5] - 2024-01-05

Added

• e3nn.ones and e3nn.ones_like functions
• e3nn.equinox submodule

Fixed

• python 3.9 compatibility

[0.20.4] - 2023-12-24

Fixed

• Fix pyproject.toml, the documenation build was broken. Thanks to @SauravMaheshkar!

Added

• Support for 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] - 2023-11-17

Added

• e3nn.flax.BatchNorm
• e3nn.scatter_mean
• Add e3nn.utils.vmap also directly to e3nn module: e3nn.vmap

[0.20.2] - 2023-09-25

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)

[0.20.1] - 2023-09-13

Changed

• Add back the optimizations with the lazy ._chunks that was removed in 0.19.0

[0.20.0] - 2023-09-09

Added

• e3nn.Irreps.mul_gcd
• e3nn.IrrepsArray.extend_with_zeros to extend an array with zeros, can be useful for residual connections

Changed

• rewrite e3nn.tensor_square to be simpler (and faster?)
• use jax.scipy.special.lpmn_values to implement e3nn.legendre. Faster on GPU and supports reverse-mode differentiation.
• [BREAKING] Change the output format of e3nn.legendre!

Fixed

• Add back a lazy ._chunks in e3nn.IrrepsArray to fix issue #38

[0.19.3] - 2023-06-24

Fixed

• Fix missing support for zero flags in e3nn.elementwise_tensor_product

[0.19.2] - 2023-06-23

Changed

• [BREAKING] Move Instruction, FunctionalTensorProduct and FunctionalFullyConnectedTensorProduct into e3nn.legacy submodule
• Reimplement e3nn.tensor_product and e3nn.elementwise_tensor_product in a simpler way

[0.19.1] - 2023-06-22

Added

• e3nn.utils.vmap to propagate zero_flags in the vectorized function.

Changed

• Simplify the tetris examples

Fixed

• Example of what is fixed: assume x.ndim = 2, allow x[:, None] but prevent x[:, :, None] and x[..., None]

[0.19.0] - 2023-06-21

Changed

• [BREAKING] e3nn.flax.Linear and e3nn.haiku.Linear now don't output the impossible irreps anymore. To force the output of all irreps, use force_irreps_out = True. For instance e3nn.flax.Linear("0e + 1o")("0e") will now return "0e" instead of "0e + 1o".
• [BREAKING] e3nn.utils.assert_equivariant has the same signature as e3nn.utils.equivariance_test
• [BREAKING] Move as_irreps_array, zeros and zeros_like from e3nn.IrrepsArray to e3nn
• [BREAKING] Move IrrepsArray.from_list to e3nn.from_chunks
• [BREAKING] Rename IrrepsArray.list into IrrepsArray.chunks
• [BREAKING] Rename IrrepsArray.remove_nones into IrrepsArray.remove_zero_chunks
• e3nn.IrrepsArray has now only .array as data attribute.

Added

• e3nn.IrrepsArray.rechunk
• e3nn.IrrepsArray.zero_flags a tuple of bools that indicates which chunks are zero

[0.18.0] - 2023-06-19

Changed

• [BREAKING] Renamed e3nn.util in e3nn.utils

Added

• Irreps.set_mul(int) to set the multiplicity of all irreps
• Irreps.filter(lmax=int) to filter out irreps with l > lmax
• IrrepsArray.filter(lmax=int) to filter out irreps with l > lmax
• IrrepsArray.__radd__ and IrrepsArray.__rsub__ to support scalar + IrrepsArray and scalar - IrrepsArray
• 0 + IrrepsArray and 0 - IrrepsArray are now always accepted as special cases.
• Support for IrrepsArray / array
• Add utils as a submodule

Fixed

• e3nn.scatter operation handle indices with ndim > 1

[0.17.5] - 2023-05-10

Added

• e3nn.cross for completeness

Changed

• Optimize e3nn.reduced_symmetric_tensor_product_basis, especially for the keep_ir argument

[0.17.4] - 2023-05-02

Added

• LinearSHTP module implementing the optimized linear mixing of inputs tensor product with spherical harmonics
• D_from_axis_angle
• to_s2grid: quadrature="gausslegendre" by default
• soft_odd activation function for odd scalars
• more support of arrays implicitely converted into IrrepsArray as scalars (i.e. added few IrrepsArray.as_irreps_array)

Changed

• scalar_activation simpler to use with default activation functions (a bit like gate)

[0.17.3] - 2023-04-06

Changed

• e3nn.normalize_function now uses a deterministic (not pseudorandom) algorithm to compute the normalization factor.

Added

• normalize_act option to e3nn.scalar_activation and e3nn.gate. We can now turn the normalization off if we want to.
• e3nn.norm_activation as a new activation function.

[0.17.2] - 2023-03-26

Fixed

• Fix NaN in the gradients of e3nn.xyz_to_angles. The gradients are now 0 when the input is on the poles.

[0.17.1] - 2023-03-15

Added

• e3nn.dot: compute the dot product between two IrrepsArray
• per_irrep argument to e3nn.norm: compute the norm of each irrep independently if per_irrep=True
• e3nn.tensor_product_with_spherical_harmonics from https://arxiv.org/pdf/2302.03655.pdf

Changed

• __repr__(Irreps()) has been changed from "" to "Irreps()"

Fixed

• spherical harmonics edge case when output_irreps=Irreps()

[0.17.0] - 2023-02-20

Added

• e3nn.SphericalSignal.sample to sample a point on the sphere
• e3nn.scatter_max

Changed

• [BREAKING] Removed e3nn.s2_sum_of_diracs in favor of e3nn.s2_dirac
• [BREAKING] e3nn.grad now regroups the output by default. It can be disabled with regroup_output=False

Fixed

• e3nn.SphericalSignal arithmetic operations
• e3nn.Irreps.D_from_angles computes (again!) the Wigner D matrices using the J matrices for L <= 11. This is faster and more accurate than using the expm.

[0.16.0] - 2023-02-01

Added

• e3nn.SphericalSignal class to represent signals on the sphere
• Signal on the Sphere section in the documentation
• e3nn.Irreps.D_from_log_coordinates
• rotation_angle_from_* functions
• e3nn.to_s2point function

Changed

• Wigner D matrices are computed from the log coordinates which makes 1 instead of 3 calls to expm.
• [BREAKING] e3nn.util.assert_output_dtype renamed to e3nn.util.assert_output_dtype_matches_input_dtype
• [BREAKING] Update experimental.point_convolution to use the last changes.
• [BREAKING] changed the e3nn.to_s2grid and e3nn.from_s2grid signature and default normalization.

Removed

• [BREAKING] All the haiku modules from the main module. They are now in the e3nn.haiku submodule.
• [BREAKING] e3nn.wigner_D in favor of e3nn.Irrep.D_from_*

Fixed

• Removed jax.jit decorator to Irreps.D_from_* that was causing a bug.

[0.15.0] - 2023-01-20

Added

• e3nn.s2grid_vectors and e3nn.pad_to_plot_on_s2grid to help plotting signals on the sphere
• e3nn.util.assert_output_dtype to check the output dtype of a function
• e3nn.s2_irreps is a function to create the irreps of the coefficients of a signal on the sphere
• e3nn.reduced_antisymmetric_tensor_product_basis to compute the basis of the reduced antisymmetric tensor product
• IrrepsArray * scalar is supported if the number of scalars matches the number of irreps

Changed

• Optimize the reduced_symmetric_tensor_product. It is now up to 100x faster than the previous implementation.
• e3nn.from_s2grid and e3nn.to_s2grid are now more flexible with input and output irreps, you can skip some l's and have them in any order
• [BREAKING] e3nn.from_s2grid requires and irreps argument instead of a lmax argument

Fixed

• Increase robusteness of e3nn.spherical_harmonics towards nan when normalize=True

[0.14.0] - 2022-12-16

Added

• IrrepsArray.astype to cast the underlying array
• e3nn.flax.MultiLayerPerceptron and e3nn.haiku.MultiLayerPerceptron
• e3nn.IrrepsArray.from_list(..., dtype)
• Add sparse tensor product as an option in e3nn.tensor_product and related functions. It sparsify the clebsch gordan coefficients. It has more inpact when fused=True. It is disabled by default because no improvement was observed in the benchmarks.
• Add log_coordinates along the other parameterizations of SO(3). e3nn.log_coordinates_to_matrix, e3nn.rand_log_coordinates, etc.

Fixed

• set dtype for all jnp.zeros(..., dtype) calls in the codebase
• set dtype for all jnp.ones(..., dtype) calls in the codebase

Removed

• [BREAKING] e3nn.full_tensor_product in favor of e3nn.tensor_product
• [BREAKING] e3nn.FunctionalTensorSquare in favor of e3nn.tensor_square
• [BREAKING] e3nn.TensorSquare in favor of e3nn.tensor_square
• [BREAKING] e3nn.IrrepsArray.cat in favor of e3nn.concatenate
• [BREAKING] e3nn.IrrepsArray.randn in favor of e3nn.normal
• [BREAKING] e3nn.Irreps.randn in favor of e3nn.normal
• [BREAKING] e3nn.Irreps.transform_by_* in favor of e3nn.IrrepsArray.transform_by_*

Changed

• moves BatchNorm and Dropout to e3nn.haiku submodule, will remove them from the main module in the future.
• move e3nn.haiku.FullyConnectedTensorProduct in haiku submodule. Undeprecate it because it's faster than e3nn.tensor_product followed by e3nn.Linear. This is because opteinsum optimizes the contraction of the two operations.

[0.13.1] - 2022-12-14

Added

• e3nn.scatter_sum to replace e3nn.index_add. e3nn.index_add is deprecated.
• add flax and haiku submodules. Plan to migrate all modules to flax and haiku in the future.
• Implement e3nn.flax.Linear and move e3nn.Linear in e3nn.haiku.Linear.

[0.13.0] - 2022-12-07

Changed

• [BREAKING] 3 * e3nn.Irreps("0e + 1o") now returns 3x0e + 3x1o instead of 1x0e + 1x1o + 1x0e + 1x1o + 1x0e + 1x1o
• [BREAKING] in Linear, renamed num_weights to num_indexed_weights because it was confusing.

Added

• e3nn.Irreps("3x0e + 6x1o") // 3 returns 1x0e + 2x1o

Fixed

• s2grid is now jitable

[0.12.0] - 2022-11-16

Added

• e3nn.Irreps.regroup and e3nn.IrrepsArray.regroup to regroup irreps. Equivalent to sort followed by simplify.
• add regroup_output parameter to e3nn.tensor_product and e3nn.tensor_square to regroup the output irreps.

Changed

• e3nn.IrrepsArray.convert is now private (e3nn.IrrepsArray._convert) because it's recommended to other methods instead.
• breaking change use input.regroup() in e3nn.Linear which can change the structure of the parameters dictionary.
• breaking change regroup_output is True by default in e3nn.tensor_product and e3nn.tensor_square.
• To facilitate debugging, if not key is provided to e3nn.normal it will use the hash of the irreps.
• breaking change changed normalization of e3nn.tensor_square in the case of normalized_input=True

Removed

• Deprecate e3nn.TensorSquare

[0.11.1] - 2022-11-13

Added

• e3nn.Linear now supports integer "weights" inputs.
• e3nn.Linear now supports name argument.
• Add .dtype to IrrepsArray to get the dtype of the underlying array.

Changed

• e3nn.MultiLayerPerceptron names its layers linear_0, linear_1, etc.

[0.11.0] - 2022-11-08

Added

• s2grid: e3nn.from_s2grid and e3nn.to_s2grid thanks to @songk42 for the contribution
• argument max_order: int to function reduced_tensor_product_basis to be able to limit the polynomial order of the basis
• MultiLayerPerceptron accepts IrrepsArray as input and output
• e3nn.Linear accepts optional weights as arguments that will be internally mixed with the free parameters. Very usefyul to implement the depthwise convolution

Changed

• breaking change e3nn.normal has a new argument to get normalized vectors.
• breaking change e3nn.tensor_square now distinguishes between normalization=norm and normalized_input=True.

[0.10.1] - 2022-10-24

Added

• e3nn.SymmetricTensorProduct operation: a parameterized version of x + x^2 + x^3 + ....
• e3nn.soft_envelope a smooth C^inf envelope radial function.
• e3nn.tensor_square

[0.10.0] - 2022-10-05

Added

• Irrep.generators and Irreps.generators functions to get the generators of the representations.
• e3nn.bessel function
• slice_by_mul, slice_by_dim and slice_by_chunk functions to Irreps and IrrepsArray

Changed

• breaking change e3nn.soft_one_hot_linspace does not support bessel anymore. Use e3nn.bessel instead.
• e3nn.gate is now more flexible of the input format, see examples in the docstring.

Removed

• breaking change IrrepsArray.split

[0.9.2] - 2022-09-29

Fixed

• fix IrrepsArray.zeros().at[...].add

[0.9.1] - 2022-09-27

Added

• e3nn.reduced_symmetric_tensor_product_basis(irreps: Irreps, order: int)
• e3nn.IrrepsArray.filtered(keep: List[Irrep])
• e3nn.reduced_tensor_product_basis(formula_or_irreps_list: Union[str, List[e3nn.Irreps]], ...)
• IrrepsArray.at[i].set(v) and IrrepsArray.at[i].add(v)
• add Irreps.is_scalar

[0.9.0] - 2022-09-04

Added

• Simple irreps indexing of IrrepsArray: like x[..., "10x0e"] but not x[..., "0e + 1e"]
• e3nn.concatenate, e3nn.mean, e3nn.sum
• e3nn.norm for IrrepsArray
• e3nn.tensor_product
• e3nn.normal
• Better support of + - * / operators for IrrepsArray
• Add new operator e3nn.grad: it takes an IrrepsArray -> IrrepsArray function and returns a IrrepsArray -> IrrepsArray function
• Add support of operator IrrepsArray ** scalar
• Add support of x[..., 3:6] for IrrepsArray
• Add e3nn.reduced_tensor_product_basis
• Add e3nn.stack

Removed

• IrrepsArray.cat is now deprecated and replaced by e3nn.concatenate
• e3nn.full_tensor_product is now deprecated and replaced by e3nn.tensor_product
• e3nn.FullyConnectedTensorProduct is now deprecated in favor of e3nn.tensor_product and e3nn.Linear
• breaking change remove IrrepsArray.from_any
• breaking change remove option optimize_einsums, (it is now always True)

Changed

• breaking change rewrite the equivariance_error and assert_equivariant functions

[0.8.0] - 2022-08-11

Changed

• breaking change change the ordering of Irrep. Now it matches with Irrep.iterator.
• breaking change Irrep("1e") == "1e" and Irreps("1e + 2e") == "1e + 2e" are now True.
• breaking change Linear simplify the irreps_out which might cause reshape of the parameters.
• index_add supports IrrepArray

Added

• broadcast for Linear
• argument channel_out to Linear for convenience
• Irreps can be created from a MulIrrep
• "0e" + Irreps("1e") is now supported
• "0e" + Irrep("1e") is now supported
• map_back argument to index_add
• IrrepsArray.split(list of irreps)
• poly_envelope function

[0.7.0] - 2022-08-03

Changed

• breaking change rename IrrepsData into IrrepsArray
• breaking change IrrepsArray.shape is now equal to contiguous.shape (instead of contiguous.shape[:-1])
• breaking change IrrepsArray * array requires array.shape[-1] to be 1 or array to be a scalar
• breaking change IrrepsArray.contiguous is renamed in IrrepsArray.array
• breaking change IrrepsArray.new is renamed in IrrepsArray.from_any
• spherical_harmonics normalization is now set to component like everything else.

Removed

• breaking change IrrepsArray.from_contiguous is removed. Use IrrepsArray(irreps, array) instead.

Added

• add e3nn.config to set global defaults parameters
• __getindex__ to IrrepsData
• gradient_normalization argument that can be element or path
• path_normalization can be a number between 0 and 1
• add nearest interpolation for zoom, default is linear
• implement custom_jvp for spherical harmonics

[0.6.3] - 2022-06-29

Added

• Docker image

[0.6.2] - 2022-06-29

Added

• add the sh function that does not use IrrepsData as input/output
• legendre algorithm to compute spherical harmonics
• add flag algorithm to specify the algorithm to use for computing spherical harmonics, use legendre for large L.
• experimental.voxel_convolution: add optional dynamic steps (not static for jit)

[0.6.1] - 2022-06-09

Changed

• fix a bug in experimental.voxel_convolution constructor

[0.6.0] - 2022-06-09

Added

• Function matrix to FunctionalLinear
• experimental.voxel_convolution: padding and add self-connection into the convolution kernel
• experimental.voxel_pooling: add output_size argument to the zoom function
• IrrepsData: list attribute is now lazily initialized
• experimental.voxel_convolution: add possibility to have different radial functions depenfing on the spherical harmonic degree

Changed

• Behavior of eps in BatchNorm. Now input / sqrt((1 - eps) * norm^2 + eps) instead of input / sqrt(norm^2 + eps)
• Optimized spherical_harmonics by decomposing the order in powers of 2. It is supposed to improve stability because less operations are performed for high orders. It improves the performance when computing a single order.
• Optimized spherical_harmonics by using dense matrix multiplication instead of sparse matrix multiplication.

[0.5.0] - 2022-05-24

Added

• add loop argument to radius_graph

Changed

• use dataclasses.dataclass instead of custom dataclass
• Get Clebsch-Gordan coefficients from qutip and a change of basis
• Add start_zero and end_zero arguments to function soft_one_hot_linspace

[0.4.3] - 2022-03-26

Added

• IrrepsData can be given as argument of spherical_harmonics
• added broadcasting of IrrepsData, elementwise_tensor_product, FullyConnectedTensorProduct, full_tensor_product

Changed

• BatchNorm supports None
• BatchNorm supports change default value of eps from 1e-5 to 1e-4
• gate change default odd activation to (1 - exp(x^2)) * x

[0.4.2] - 2022-03-23

Changed

• gate list of activations argument is now optional
• experimental.transformer.Transformer simplified interface using IrrepsData and swap two arguments order

[0.4.1] - 2022-03-21

Added

• IrrepsData.repeat_irreps_by_last_axis
• IrrepsData.repeat_mul_by_last_axis
• IrrepsData.factor_mul_to_last_axis
• add axis argument to IrrepsData.cat
• IrrepsData.remove_nones
• IrrepsData.ones

Changed

• experimental.point_convolution.Convolution simplified interface using IrrepsData

[0.4.0] - 2022-03-19

Added

• Changelog