| .. _api_ref: |
|
|
| ############# |
| API reference |
| ############# |
|
|
| :mod:`neuralop`: Neural Operators in Python |
|
|
| .. automodule:: neuralop.models |
| :no-members: |
| :no-inherited-members: |
|
|
| .. _neuralop_models_ref: |
|
|
| ====== |
| Models |
| ====== |
|
|
| In :mod:`neuralop.models`, we provide neural operator models you can directly use on your applications. |
|
|
| .. _fno_api: |
|
|
| FNO |
| --- |
|
|
| We provide a general Fourier Neural Operator (FNO) that supports most usecases. |
|
|
| It works for any dimension, which is inferred based on `n_modes` |
| (a tuple with the number of modes to keep in the Fourier domain for each dimension.) |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| FNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _tfno_api: |
|
|
| Tensorized FNO (TFNO) |
| --------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| TFNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _sfno_api: |
|
|
| Spherical Fourier Neural Operators (SFNO) |
| ----------------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| SFNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _gino_api: |
|
|
| Geometry-Informed Neural Operators (GINO) |
| ----------------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| GINO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _local_no_api: |
|
|
| Local Neural Operators (LocalNO) |
| -------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| LocalNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _uno_api: |
|
|
| U-shaped Neural Operators (U-NO) |
| -------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| UNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _rno_api: |
|
|
| Recurrent Neural Operators (RNO) |
| -------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| RNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _otno_api: |
|
|
| Optimal Transport Neural Operators (OTNO) |
| ----------------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| OTNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _uqno_api: |
|
|
| Uncertainty Quantification Neural Operators (UQNO) |
| -------------------------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
| |
| UQNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _fnogno_api: |
|
|
| Fourier/Geometry Neural Operators (FNOGNO) |
| ------------------------------------------ |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
| |
| FNOGNO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _codano_api: |
|
|
| Codomain Attention Neural Operators (CODANO) |
| -------------------------------------------- |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
| |
| CODANO |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. raw:: html |
|
|
| <hr style="margin: 4em 0; border: none; border-top: 2px solid #e0e0e0;"> |
|
|
| .. _neuralop_layers_ref: |
|
|
| ====== |
| Layers |
| ====== |
|
|
| .. automodule:: neuralop.layers |
| :no-members: |
| :no-inherited-members: |
|
|
|
|
|
|
| In addition to the full architectures, we also provide |
| in :mod:`neuralop.layers` building blocks, |
| in the form of PyTorch layers, that you can use to build your own models: |
|
|
| .. _fno_blocks_api: |
|
|
| FNO Blocks |
| ---------- |
|
|
| .. automodule:: neuralop.layers.fno_block |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| FNOBlocks |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _rno_block_api: |
|
|
| RNO Blocks |
| ---------- |
|
|
| .. automodule:: neuralop.layers.rno_block |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| RNOBlock |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _spectral_conv_api: |
|
|
| Fourier Convolutions |
| -------------------- |
| .. automodule:: neuralop.layers.spectral_convolution |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| SpectralConv |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _spherical_conv_api: |
|
|
| Spherical Convolutions |
| ---------------------- |
|
|
| .. automodule:: neuralop.layers.spherical_convolution |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| SphericalConv |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
|
|
| .. _gno_api: |
|
|
| Graph convolutions and kernel integration |
| ----------------------------------------- |
|
|
| .. automodule:: neuralop.layers.gno_block |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| GNOBlock |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. automodule:: neuralop.layers.integral_transform |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| IntegralTransform |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _local_no_blocks_api: |
|
|
| Local NO Blocks |
| --------------- |
| .. automodule:: neuralop.layers.local_no_block |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| LocalNOBlocks |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _diff_conv_api: |
|
|
| Local Integral/Differential Convolutions |
| ---------------------------------------- |
|
|
| .. automodule:: neuralop.layers.differential_conv |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| FiniteDifferenceConvolution |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. _disco_conv_api: |
|
|
| Discrete-Continuous (DISCO) Convolutions |
| ---------------------------------------- |
|
|
| .. automodule:: neuralop.layers.discrete_continuous_convolution |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| DiscreteContinuousConv2d |
| DiscreteContinuousConvTranspose2d |
| EquidistantDiscreteContinuousConv2d |
| EquidistantDiscreteContinuousConvTranspose2d |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Codomain Attention (Transformer) Blocks |
| --------------------------------------- |
| .. automodule:: neuralop.layers.coda_layer |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| CODALayer |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Channel MLP |
| ----------- |
|
|
| .. automodule:: neuralop.layers.channel_mlp |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| ChannelMLP |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Embeddings |
| ---------- |
|
|
| Apply positional embeddings as additional channels on a function: |
|
|
| .. automodule:: neuralop.layers.embeddings |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| GridEmbeddingND |
| GridEmbedding2D |
| SinusoidalEmbedding |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Neighbor search |
| --------------- |
|
|
| Find neighborhoods on arbitrary coordinate meshes: |
|
|
| .. automodule:: neuralop.layers.neighbor_search |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| NeighborSearch |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| native_neighbor_search |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Domain Padding |
| -------------- |
|
|
| .. automodule:: neuralop.layers.padding |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| DomainPadding |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Skip Connections |
| ---------------- |
|
|
| .. automodule:: neuralop.layers.skip_connections |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| skip_connection |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Normalization Layers |
| -------------------- |
|
|
| .. automodule:: neuralop.layers.normalization_layers |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| AdaIN |
| InstanceNorm |
| BatchNorm |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Complex-value Support |
| --------------------- |
|
|
| .. automodule:: neuralop.layers.complex |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| ComplexValued |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. raw:: html |
|
|
| <hr style="margin: 4em 0; border: none; border-top: 2px solid #e0e0e0;"> |
|
|
|
|
| ================= |
| Model Dispatching |
| ================= |
| We provide a utility function to create model instances from a configuration. |
| It has the advantage of doing some checks on the parameters it receives. |
|
|
| .. automodule:: neuralop.models.base_model |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| get_model |
| available_models |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. raw:: html |
|
|
| <hr style="margin: 4em 0; border: none; border-top: 2px solid #e0e0e0;"> |
|
|
| ======== |
| Training |
| ======== |
| We provide functionality that automates the boilerplate code associated with |
| training a machine learning model to minimize a loss function on a dataset: |
|
|
| .. automodule:: neuralop.training |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| Trainer |
| IncrementalFNOTrainer |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Optimizers |
| ---------- |
|
|
| .. automodule:: neuralop.training.tensorgrad |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| TensorGRaD |
| TensorGRaDProjector |
| UnstructuredSparseProjector |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| fno_tensorgrad_param_groups |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Training Utilities |
| ------------------ |
|
|
| .. automodule:: neuralop.training.torch_setup |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| setup |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Multi-Grid Patching |
| ------------------- |
|
|
| .. automodule:: neuralop.training.patching |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| MultigridPatching2D |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. raw:: html |
|
|
| <hr style="margin: 4em 0; border: none; border-top: 2px solid #e0e0e0;"> |
|
|
| ============== |
| Loss Functions |
| ============== |
|
|
| Data Losses |
| ----------- |
|
|
| .. automodule:: neuralop.losses.data_losses |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| LpLoss |
| H1Loss |
| HdivLoss |
| PointwiseQuantileLoss |
| MSELoss |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Equation Losses |
| --------------- |
|
|
| Physics-informed loss functions: |
|
|
| .. automodule:: neuralop.losses.equation_losses |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| BurgersEqnLoss |
| ICLoss |
| PoissonInteriorLoss |
| PoissonBoundaryLoss |
| PoissonEqnLoss |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Meta Losses |
| ----------- |
|
|
| Meta-losses for weighting composite loss functions. |
|
|
| .. automodule:: neuralop.losses.meta_losses |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| WeightedSumLoss |
| Relobralo |
| SoftAdapt |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Differentiation |
| --------------- |
|
|
| Numerical differentiation utilities: |
|
|
| .. automodule:: neuralop.losses.differentiation |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| FourierDiff |
| FiniteDiff |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| non_uniform_fd |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Spectral Projection |
| ------------------- |
|
|
| Spectral projection utilities for enforcing physical constraints: |
|
|
| .. automodule:: neuralop.layers.spectral_projection |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| spectral_projection_divergence_free |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. raw:: html |
|
|
| <hr style="margin: 4em 0; border: none; border-top: 2px solid #e0e0e0;"> |
|
|
| ==== |
| Data |
| ==== |
|
|
| In `neuralop.data`, we provide APIs for standardizing PDE datasets (`.datasets`) and transforming raw data into model inputs (`.transforms`). |
|
|
| Datasets |
| -------- |
|
|
| We ship a small dataset for testing: |
|
|
| .. automodule:: neuralop.data.datasets |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| load_darcy_flow_small |
|
|
| We provide downloadable datasets for Darcy-Flow, Navier-Stokes, and Car-CFD. |
|
|
| .. automodule:: neuralop.data.datasets.darcy |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| DarcyDataset |
|
|
|
|
| .. automodule:: neuralop.data.datasets.navier_stokes |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| NavierStokesDataset |
|
|
|
|
| .. automodule:: neuralop.data.datasets.car_cfd_dataset |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| CarCFDDataset |
|
|
| .. _burgers_dataset_api: |
|
|
| .. automodule:: neuralop.data.datasets.burgers |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| Burgers1dTimeDataset |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| load_mini_burgers_1dtime |
|
|
|
|
| .. note:: |
| Additional datasets are available with optional dependencies: |
| |
| * **The Well Datasets**: Large-scale collection of diverse physics simulations |
| (requires `the_well` package) |
| * **Spherical Shallow Water Equations**: For spherical coordinate systems |
| (requires `torch_harmonics` package) |
| |
| These datasets are conditionally imported and may not be available |
| depending on your installation. |
|
|
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| DataProcessors |
| -------------- |
|
|
| Much like PyTorch's `Torchvision.Datasets` module, our `data` module also includes |
| utilities to transform data from its raw form into the form expected by models and |
| loss functions: |
|
|
| .. automodule:: neuralop.data.transforms.data_processors |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| DefaultDataProcessor |
| MGPatchingDataProcessor |
| IncrementalDataProcessor |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| Normalizers |
| ----------- |
|
|
| Data normalization utilities: |
|
|
| .. automodule:: neuralop.data.transforms.normalizers |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: class.rst |
|
|
| UnitGaussianNormalizer |
| DictUnitGaussianNormalizer |
|
|
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
|
|
| .. raw:: html |
|
|
| <hr style="margin: 4em 0; border: none; border-top: 2px solid #e0e0e0;"> |
|
|
| ================= |
| Utility Functions |
| ================= |
|
|
| .. automodule:: neuralop.utils |
| :no-members: |
| :no-inherited-members: |
|
|
| .. autosummary:: |
| :toctree: generated |
| :template: function.rst |
|
|
| count_model_params |
| count_tensor_params |
| spectrum_2d |
| compute_rank |
| compute_stable_rank |
| compute_explained_variance |
|
|
