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e3nn-mlx 0.1.0
e3nn-mlx 0.1.0
  • User guide
    • Installation
    • Irreducible representations
    • Tensor products
    • Testing equivariance
    • Migrating from e3nn/PyTorch
    • Performance and automatic differentiation
  • Examples
    • First equivariant operation
    • Equivariant graph convolution
    • Point-cloud models
  • API reference
    • O(3) operations
      • e3nn_mlx.o3.Irrep
      • e3nn_mlx.o3.MulIrrep
      • e3nn_mlx.o3.Irreps
      • e3nn_mlx.o3.Linear
      • e3nn_mlx.o3.Norm
      • e3nn_mlx.o3.TensorProduct
      • e3nn_mlx.o3.FullyConnectedTensorProduct
      • e3nn_mlx.o3.FullTensorProduct
      • e3nn_mlx.o3.ElementwiseTensorProduct
      • e3nn_mlx.o3.TensorSquare
      • e3nn_mlx.o3.ReducedTensorProducts
      • e3nn_mlx.o3.spherical_harmonics
      • e3nn_mlx.o3.spherical_harmonics_alpha_beta
      • e3nn_mlx.o3.SphericalHarmonics
      • e3nn_mlx.o3.SphericalHarmonicsAlphaBeta
      • e3nn_mlx.o3.s2_grid
      • e3nn_mlx.o3.ToS2Grid
      • e3nn_mlx.o3.FromS2Grid
      • e3nn_mlx.o3.SO3Grid
      • e3nn_mlx.o3.rand_angles
      • e3nn_mlx.o3.rand_matrix
      • e3nn_mlx.o3.rand_quaternion
      • e3nn_mlx.o3.rand_axis_angle
      • e3nn_mlx.o3.angles_to_matrix
      • e3nn_mlx.o3.matrix_to_angles
      • e3nn_mlx.o3.axis_angle_to_matrix
      • e3nn_mlx.o3.matrix_to_axis_angle
      • e3nn_mlx.o3.quaternion_to_matrix
      • e3nn_mlx.o3.matrix_to_quaternion
      • e3nn_mlx.o3.compose_angles
      • e3nn_mlx.o3.compose_quaternion
      • e3nn_mlx.o3.compose_axis_angle
      • e3nn_mlx.o3.wigner_d
      • e3nn_mlx.o3.irreps_wigner_d
      • e3nn_mlx.o3.irreps_wigner_d_from_matrix
      • e3nn_mlx.o3.wigner_3j
    • Neural-network modules
      • e3nn_mlx.nn.Activation
      • e3nn_mlx.nn.BatchNorm
      • e3nn_mlx.nn.Dropout
      • e3nn_mlx.nn.Extract
      • e3nn_mlx.nn.ExtractIr
      • e3nn_mlx.nn.FullyConnectedNet
      • e3nn_mlx.nn.Gate
      • e3nn_mlx.nn.Identity
      • e3nn_mlx.nn.NormActivation
      • e3nn_mlx.nn.S2Activation
      • e3nn_mlx.nn.SO3Activation
    • Mathematical helpers
      • e3nn_mlx.math.soft_unit_step
      • e3nn_mlx.math.soft_one_hot_linspace
      • e3nn_mlx.math.smooth_cutoff
    • Graph operations
      • e3nn_mlx.radius_graph
      • e3nn_mlx.scatter_sum
    • Models
      • e3nn_mlx.models.gate_points_2102.Convolution
      • e3nn_mlx.models.gate_points_2102.Network
      • e3nn_mlx.models.v2106.Convolution
      • e3nn_mlx.models.v2106.MessagePassing
      • e3nn_mlx.models.v2106.SimpleNetwork
      • e3nn_mlx.models.v2106.NetworkForAGraphWithAttributes
    • Representation-aware arrays
      • e3nn_mlx.IrrepsArray
  • Development notes
    • Compatibility and numerical conventions
    • e3nn-style high-level API
    • Upstream tests/o3 compatibility matrix
    • Upstream tests/nn compatibility matrix
    • gate_points_2102 MLX model
    • Modular v2106 point models
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Representation-aware arraysΒΆ

IrrepsArray(irreps, array)

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