diff --git a/.buildinfo b/.buildinfo deleted file mode 100644 index acbad833aa..0000000000 --- a/.buildinfo +++ /dev/null @@ -1,4 +0,0 @@ -# Sphinx build info version 1 -# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 21ab98e528573f73f1b5d8a9a8dc8e52 -tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt index 964b1c0dd6..5dbc9cda42 100644 --- a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt +++ b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt @@ -1,17 +1,17 @@ -2024-08-14 17:31:27 (INFO): Running in non-distributed local mode -2024-08-14 17:31:27 (INFO): Setting env PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True -2024-08-14 17:31:27 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem -2024-08-14 17:31:28 (INFO): amp: true +2024-09-13 23:27:40 (INFO): Running in local mode without elastic launch (single gpu only) +2024-09-13 23:27:40 (INFO): Setting env PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True +2024-09-13 23:27:40 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem +2024-09-13 23:27:41 (INFO): amp: false cmd: - checkpoint_dir: fine-tuning/checkpoints/2024-08-14-17-31-44-ft-oxides - commit: 8fb16d6 + checkpoint_dir: fine-tuning/checkpoints/2024-09-13-23-28-00-ft-oxides + commit: 7d40b20 identifier: ft-oxides - logs_dir: fine-tuning/logs/tensorboard/2024-08-14-17-31-44-ft-oxides + logs_dir: fine-tuning/logs/tensorboard/2024-09-13-23-28-00-ft-oxides print_every: 10 - results_dir: fine-tuning/results/2024-08-14-17-31-44-ft-oxides + results_dir: fine-tuning/results/2024-09-13-23-28-00-ft-oxides seed: 0 - timestamp_id: 2024-08-14-17-31-44-ft-oxides - version: 0.1.dev1+g8fb16d6 + timestamp_id: 2024-09-13-23-28-00-ft-oxides + version: 0.1.dev1+g7d40b20 dataset: a2g_args: r_energy: true @@ -97,7 +97,6 @@ model: sbf: name: legendre_outer symmetric_edge_symmetrization: false -noddp: false optim: batch_size: 4 clip_grad_norm: 10 @@ -142,93 +141,100 @@ val_dataset: format: ase_db src: val.db -2024-08-14 17:31:28 (INFO): Loading dataset: ase_db -2024-08-14 17:31:28 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('train.db')]' -2024-08-14 17:31:28 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. -2024-08-14 17:31:28 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. -2024-08-14 17:31:28 (INFO): rank: 0: Sampler created... -2024-08-14 17:31:28 (INFO): Created BalancedBatchSampler with sampler=, batch_size=4, drop_last=False -2024-08-14 17:31:28 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('val.db')]' -2024-08-14 17:31:28 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. -2024-08-14 17:31:28 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. -2024-08-14 17:31:28 (INFO): rank: 0: Sampler created... -2024-08-14 17:31:28 (INFO): Created BalancedBatchSampler with sampler=, batch_size=16, drop_last=False -2024-08-14 17:31:28 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('test.db')]' -2024-08-14 17:31:28 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. -2024-08-14 17:31:28 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. -2024-08-14 17:31:28 (INFO): rank: 0: Sampler created... -2024-08-14 17:31:28 (INFO): Created BalancedBatchSampler with sampler=, batch_size=16, drop_last=False -2024-08-14 17:31:28 (INFO): Loading model: gemnet_oc -2024-08-14 17:31:28 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization'] -2024-08-14 17:31:30 (INFO): Loaded GemNetOC with 38864438 parameters. -2024-08-14 17:31:30 (WARNING): log_summary for Tensorboard not supported -2024-08-14 17:31:30 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated. -2024-08-14 17:31:31 (INFO): Attemping to load user specified checkpoint at /tmp/fairchem_checkpoints/gnoc_oc22_oc20_all_s2ef.pt -2024-08-14 17:31:31 (INFO): Loading checkpoint from: /tmp/fairchem_checkpoints/gnoc_oc22_oc20_all_s2ef.pt -2024-08-14 17:31:31 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. +2024-09-13 23:27:41 (INFO): Loading model: gemnet_oc +2024-09-13 23:27:41 (WARNING): Unrecognized arguments: ['symmetric_edge_symmetrization'] +2024-09-13 23:27:43 (INFO): Loaded GemNetOC with 38864438 parameters. +2024-09-13 23:27:43 (WARNING): log_summary for Tensorboard not supported +2024-09-13 23:27:43 (INFO): Loading dataset: ase_db +2024-09-13 23:27:43 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('train.db')]' +2024-09-13 23:27:43 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. +2024-09-13 23:27:43 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. +2024-09-13 23:27:43 (INFO): rank: 0: Sampler created... +2024-09-13 23:27:43 (INFO): Created BalancedBatchSampler with sampler=, batch_size=4, drop_last=False +2024-09-13 23:27:43 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('val.db')]' +2024-09-13 23:27:43 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. +2024-09-13 23:27:43 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. +2024-09-13 23:27:43 (INFO): rank: 0: Sampler created... +2024-09-13 23:27:43 (INFO): Created BalancedBatchSampler with sampler=, batch_size=16, drop_last=False +2024-09-13 23:27:43 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('test.db')]' +2024-09-13 23:27:43 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. +2024-09-13 23:27:43 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. +2024-09-13 23:27:43 (INFO): rank: 0: Sampler created... +2024-09-13 23:27:43 (INFO): Created BalancedBatchSampler with sampler=, batch_size=16, drop_last=False +2024-09-13 23:27:43 (WARNING): Using `weight_decay` from `optim` instead of `optim.optimizer_params`.Please update your config to use `optim.optimizer_params.weight_decay`.`optim.weight_decay` will soon be deprecated. +2024-09-13 23:27:43 (INFO): Attemping to load user specified checkpoint at /tmp/fairchem_checkpoints/gnoc_oc22_oc20_all_s2ef.pt +2024-09-13 23:27:43 (INFO): Loading checkpoint from: /tmp/fairchem_checkpoints/gnoc_oc22_oc20_all_s2ef.pt +2024-09-13 23:27:44 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch_geometric/data/collate.py:145: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() storage = elem.storage()._new_shared(numel) /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch_geometric/data/collate.py:145: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() storage = elem.storage()._new_shared(numel) -2024-08-14 17:31:54 (INFO): energy_mae: 9.52e+00, forcesx_mae: 7.22e-02, forcesy_mae: 3.94e-02, forcesz_mae: 5.74e-02, forces_mae: 5.63e-02, forces_cosine_similarity: 1.39e-01, forces_magnitude_error: 1.11e-01, energy_forces_within_threshold: 0.00e+00, loss: 9.65e+00, lr: 5.00e-04, epoch: 1.69e-01, step: 1.00e+01 -2024-08-14 17:31:55 (INFO): Evaluating on val. +2024-09-13 23:28:07 (INFO): energy_mae: 9.48e+00, forcesx_mae: 7.26e-02, forcesy_mae: 3.95e-02, forcesz_mae: 5.74e-02, forces_mae: 5.65e-02, forces_cosine_similarity: 1.12e-01, forces_magnitude_error: 1.11e-01, energy_forces_within_threshold: 0.00e+00, loss: 9.61e+00, lr: 5.00e-04, epoch: 1.69e-01, step: 1.00e+01 +2024-09-13 23:28:08 (INFO): Evaluating on val. device 0: 0%| | 0/2 [00:00, batch_size=16, drop_last=False -2024-08-14 17:37:17 (INFO): Loading model: gemnet_t -2024-08-14 17:37:19 (INFO): Loaded GemNetT with 31671825 parameters. -2024-08-14 17:37:19 (WARNING): log_summary for Tensorboard not supported -2024-08-14 17:37:19 (INFO): Attemping to load user specified checkpoint at /tmp/fairchem_checkpoints/gndt_oc22_all_s2ef.pt -2024-08-14 17:37:19 (INFO): Loading checkpoint from: /tmp/fairchem_checkpoints/gndt_oc22_all_s2ef.pt -2024-08-14 17:37:20 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. -2024-08-14 17:37:20 (WARNING): Scale factor comment not found in model -2024-08-14 17:37:20 (INFO): Predicting on test. +2024-09-13 23:33:28 (INFO): Loading model: gemnet_t +2024-09-13 23:33:30 (INFO): Loaded GemNetT with 31671825 parameters. +2024-09-13 23:33:30 (WARNING): log_summary for Tensorboard not supported +2024-09-13 23:33:30 (WARNING): Could not find dataset metadata.npz files in '[PosixPath('data.db')]' +2024-09-13 23:33:30 (WARNING): Disabled BalancedBatchSampler because num_replicas=1. +2024-09-13 23:33:30 (WARNING): Failed to get data sizes, falling back to uniform partitioning. BalancedBatchSampler requires a dataset that has a metadata attributed with number of atoms. +2024-09-13 23:33:30 (INFO): rank: 0: Sampler created... +2024-09-13 23:33:30 (INFO): Created BalancedBatchSampler with sampler=, batch_size=16, drop_last=False +2024-09-13 23:33:30 (INFO): Attemping to load user specified checkpoint at /tmp/fairchem_checkpoints/gndt_oc22_all_s2ef.pt +2024-09-13 23:33:30 (INFO): Loading checkpoint from: /tmp/fairchem_checkpoints/gndt_oc22_all_s2ef.pt +2024-09-13 23:33:30 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. +2024-09-13 23:33:30 (WARNING): Scale factor comment not found in model +2024-09-13 23:33:30 (INFO): Predicting on test. device 0: 0%| | 0/3 [00:00 None @@ -67,9 +64,9 @@ Module Contents -.. py:function:: runner_wrapper(distributed: bool, config: dict) +.. py:function:: runner_wrapper(config: dict) -.. py:function:: main() +.. py:function:: main(args: argparse.Namespace | None = None, override_args: list[str] | None = None) Run the main fairchem program. diff --git a/_sources/autoapi/core/common/distutils/index.rst b/_sources/autoapi/core/common/distutils/index.rst index 0c279ef1fa..23f3bfc3a5 100644 --- a/_sources/autoapi/core/common/distutils/index.rst +++ b/_sources/autoapi/core/common/distutils/index.rst @@ -18,6 +18,7 @@ Attributes .. autoapisummary:: core.common.distutils.T + core.common.distutils.DISTRIBUTED_PORT Functions @@ -45,6 +46,10 @@ Module Contents .. py:data:: T +.. py:data:: DISTRIBUTED_PORT + :value: 13356 + + .. py:function:: os_environ_get_or_throw(x: str) -> str .. py:function:: setup(config) -> None diff --git a/_sources/autoapi/core/common/logger/index.rst b/_sources/autoapi/core/common/logger/index.rst index cd227b74a3..edbd8e8b9e 100644 --- a/_sources/autoapi/core/common/logger/index.rst +++ b/_sources/autoapi/core/common/logger/index.rst @@ -86,6 +86,9 @@ Module Contents .. py:attribute:: entity + .. py:attribute:: group + + .. py:method:: watch(model, log_freq: int = 1000) -> None Monitor parameters and gradients. diff --git a/_sources/autoapi/core/common/relaxation/ase_utils/index.rst b/_sources/autoapi/core/common/relaxation/ase_utils/index.rst index 23028b0932..a514269f97 100644 --- a/_sources/autoapi/core/common/relaxation/ase_utils/index.rst +++ b/_sources/autoapi/core/common/relaxation/ase_utils/index.rst @@ -60,6 +60,8 @@ Module Contents :value: ['energy', 'forces'] + Properties calculator can handle (energy, forces, ...) + .. py:attribute:: checkpoint :value: None diff --git a/_sources/autoapi/core/common/test_utils/index.rst b/_sources/autoapi/core/common/test_utils/index.rst index a41657e097..c54eab78fe 100644 --- a/_sources/autoapi/core/common/test_utils/index.rst +++ b/_sources/autoapi/core/common/test_utils/index.rst @@ -21,6 +21,7 @@ Functions core.common.test_utils.init_env_rank_and_launch_test core.common.test_utils.init_pg_and_rank_and_launch_test core.common.test_utils.spawn_multi_process + core.common.test_utils.init_local_distributed_process_group Module Contents @@ -89,3 +90,5 @@ Module Contents :returns: A list, l, where l[i] is the return value of test_method on rank i +.. py:function:: init_local_distributed_process_group(backend='nccl') + diff --git a/_sources/autoapi/core/common/transforms/index.rst b/_sources/autoapi/core/common/transforms/index.rst index c1d9af27ab..d361399b34 100644 --- a/_sources/autoapi/core/common/transforms/index.rst +++ b/_sources/autoapi/core/common/transforms/index.rst @@ -48,7 +48,4 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - diff --git a/_sources/autoapi/core/common/utils/index.rst b/_sources/autoapi/core/common/utils/index.rst index 1cc3c2c65e..5fa08a8ff4 100644 --- a/_sources/autoapi/core/common/utils/index.rst +++ b/_sources/autoapi/core/common/utils/index.rst @@ -18,6 +18,7 @@ Attributes .. autoapisummary:: core.common.utils.DEFAULT_ENV_VARS + core.common.utils.multitask_required_keys Classes @@ -50,6 +51,7 @@ Functions core.common.utils.dict_set_recursively core.common.utils.parse_value core.common.utils.create_dict_from_args + core.common.utils.find_relative_file_in_paths core.common.utils.load_config core.common.utils.build_config core.common.utils.create_grid @@ -74,6 +76,7 @@ Functions core.common.utils.irreps_sum core.common.utils.update_config core.common.utils.get_loss_module + core.common.utils.load_model_and_weights_from_checkpoint Module Contents @@ -97,6 +100,8 @@ Module Contents .. py:function:: save_checkpoint(state, checkpoint_dir: str = 'checkpoints/', checkpoint_file: str = 'checkpoint.pt') -> str +.. py:data:: multitask_required_keys + .. py:class:: Complete .. py:method:: __call__(data) @@ -164,9 +169,18 @@ Module Contents Keys in different dictionary levels are separated by sep. -.. py:function:: load_config(path: str, previous_includes: list | None = None) +.. py:function:: find_relative_file_in_paths(filename, include_paths) + +.. py:function:: load_config(path: str, files_previously_included: list | None = None, include_paths: list | None = None) + + Load a given config with any defined imports -.. py:function:: build_config(args, args_override) + When imports are present this is a recursive function called on imports. + To prevent any cyclic imports we keep track of already imported yml files + using files_previously_included + + +.. py:function:: build_config(args, args_override, include_paths=None) .. py:function:: create_grid(base_config, sweep_file: str) @@ -250,7 +264,7 @@ Module Contents .. py:function:: setup_env_vars() -> None -.. py:function:: new_trainer_context(*, config: dict[str, Any], distributed: bool = False) +.. py:function:: new_trainer_context(*, config: dict[str, Any]) .. py:function:: _resolve_scale_factor_submodule(model: torch.nn.Module, name: str) @@ -281,3 +295,5 @@ Module Contents .. py:function:: get_loss_module(loss_name) +.. py:function:: load_model_and_weights_from_checkpoint(checkpoint_path: str) -> torch.nn.Module + diff --git a/_sources/autoapi/core/datasets/_utils/index.rst b/_sources/autoapi/core/datasets/_utils/index.rst index 5a61a616c0..b7ddd7f910 100644 --- a/_sources/autoapi/core/datasets/_utils/index.rst +++ b/_sources/autoapi/core/datasets/_utils/index.rst @@ -23,11 +23,17 @@ Functions Module Contents --------------- -.. py:function:: rename_data_object_keys(data_object: torch_geometric.data.Data, key_mapping: dict[str, str]) -> torch_geometric.data.Data +.. py:function:: rename_data_object_keys(data_object: torch_geometric.data.Data, key_mapping: dict[str, str | list[str]]) -> torch_geometric.data.Data Rename data object keys :param data_object: data object :param key_mapping: dictionary specifying keys to rename and new names {prev_key: new_key} + :param new_key can be a list of new keys: + :param for example: + :param : + :param prev_key: energy + :param new_key: [common_energy, oc20_energy] + :param This is currently required when we use a single target/label for multiple tasks: diff --git a/_sources/autoapi/core/datasets/index.rst b/_sources/autoapi/core/datasets/index.rst index 34a7b2c572..1ee6ab1c7e 100644 --- a/_sources/autoapi/core/datasets/index.rst +++ b/_sources/autoapi/core/datasets/index.rst @@ -418,5 +418,5 @@ Package Contents .. py:method:: sample_property_metadata(num_samples: int = 100) -.. py:function:: data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False) -> torch_geometric.data.data.BaseData +.. py:function:: data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False, to_dict: bool = False) -> torch_geometric.data.data.BaseData | dict[str, torch.Tensor] diff --git a/_sources/autoapi/core/datasets/lmdb_dataset/index.rst b/_sources/autoapi/core/datasets/lmdb_dataset/index.rst index 838e0ee739..c20f5c658f 100644 --- a/_sources/autoapi/core/datasets/lmdb_dataset/index.rst +++ b/_sources/autoapi/core/datasets/lmdb_dataset/index.rst @@ -84,5 +84,5 @@ Module Contents .. py:method:: sample_property_metadata(num_samples: int = 100) -.. py:function:: data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False) -> torch_geometric.data.data.BaseData +.. py:function:: data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False, to_dict: bool = False) -> torch_geometric.data.data.BaseData | dict[str, torch.Tensor] diff --git a/_sources/autoapi/core/models/base/index.rst b/_sources/autoapi/core/models/base/index.rst index 2ac238368c..976cbccf70 100644 --- a/_sources/autoapi/core/models/base/index.rst +++ b/_sources/autoapi/core/models/base/index.rst @@ -21,7 +21,6 @@ Classes core.models.base.GraphModelMixin core.models.base.HeadInterface core.models.base.BackboneInterface - core.models.base.HydraInterface core.models.base.HydraModel @@ -92,6 +91,9 @@ Module Contents .. py:class:: HeadInterface + .. py:property:: use_amp + + .. py:method:: forward(data: torch_geometric.data.Batch, emb: dict[str, torch.Tensor]) -> dict[str, torch.Tensor] :abstractmethod: @@ -124,28 +126,9 @@ Module Contents -.. py:class:: HydraInterface - - Bases: :py:obj:`abc.ABC` - - - Helper class that provides a standard way to create an ABC using - inheritance. - - - .. py:method:: get_backbone() -> BackboneInterface - :abstractmethod: - - - - .. py:method:: get_heads() -> dict[str, HeadInterface] - :abstractmethod: +.. py:class:: HydraModel(backbone: dict | None = None, heads: dict | None = None, finetune_config: dict | None = None, otf_graph: bool = True, pass_through_head_outputs: bool = False) - - -.. py:class:: HydraModel(backbone: dict, heads: dict, otf_graph: bool = True) - - Bases: :py:obj:`torch.nn.Module`, :py:obj:`GraphModelMixin`, :py:obj:`HydraInterface` + Bases: :py:obj:`torch.nn.Module`, :py:obj:`GraphModelMixin` Base class for all neural network modules. @@ -180,31 +163,22 @@ Module Contents :vartype training: bool - .. py:attribute:: otf_graph - - - .. py:attribute:: backbone + .. py:attribute:: device + :value: None - .. py:attribute:: heads + .. py:attribute:: otf_graph - .. py:attribute:: backbone_model_name + .. py:attribute:: pass_through_head_outputs - .. py:attribute:: output_heads - :type: dict[str, HeadInterface] + .. py:attribute:: starting_model + :value: None - .. py:attribute:: head_names_sorted .. py:method:: forward(data: torch_geometric.data.Batch) - .. py:method:: get_backbone() -> BackboneInterface - - - .. py:method:: get_heads() -> dict[str, HeadInterface] - - diff --git a/_sources/autoapi/core/models/dimenet_plus_plus/index.rst b/_sources/autoapi/core/models/dimenet_plus_plus/index.rst index 562febb15a..f3d560ede3 100644 --- a/_sources/autoapi/core/models/dimenet_plus_plus/index.rst +++ b/_sources/autoapi/core/models/dimenet_plus_plus/index.rst @@ -445,4 +445,13 @@ Module Contents .. py:method:: forward(data: torch_geometric.data.batch.Batch) -> dict[str, torch.Tensor] + Backbone forward. + + :param data: Atomic systems as input + :type data: DataBatch + + :returns: **embedding** -- Return backbone embeddings for the given input + :rtype: dict[str->torch.Tensor] + + diff --git a/_sources/autoapi/core/models/equiformer_v2/equiformer_v2/index.rst b/_sources/autoapi/core/models/equiformer_v2/equiformer_v2/index.rst index 1752be4ca9..b925baefdf 100644 --- a/_sources/autoapi/core/models/equiformer_v2/equiformer_v2/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/equiformer_v2/index.rst @@ -18,12 +18,20 @@ Classes .. autoapisummary:: - core.models.equiformer_v2.equiformer_v2.EquiformerV2 core.models.equiformer_v2.equiformer_v2.EquiformerV2Backbone core.models.equiformer_v2.equiformer_v2.EquiformerV2EnergyHead core.models.equiformer_v2.equiformer_v2.EquiformerV2ForceHead +Functions +--------- + +.. autoapisummary:: + + core.models.equiformer_v2.equiformer_v2.eqv2_init_weights + core.models.equiformer_v2.equiformer_v2.eqv2_uniform_init_linear_weights + + Module Contents --------------- @@ -35,7 +43,11 @@ Module Contents :value: 23.395238876342773 -.. py:class:: EquiformerV2(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = True, max_neighbors: int = 500, max_radius: float = 5.0, max_num_elements: int = 90, num_layers: int = 12, sphere_channels: int = 128, attn_hidden_channels: int = 128, num_heads: int = 8, attn_alpha_channels: int = 32, attn_value_channels: int = 16, ffn_hidden_channels: int = 512, norm_type: str = 'rms_norm_sh', lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, grid_resolution: int | None = None, num_sphere_samples: int = 128, edge_channels: int = 128, use_atom_edge_embedding: bool = True, share_atom_edge_embedding: bool = False, use_m_share_rad: bool = False, distance_function: str = 'gaussian', num_distance_basis: int = 512, attn_activation: str = 'scaled_silu', use_s2_act_attn: bool = False, use_attn_renorm: bool = True, ffn_activation: str = 'scaled_silu', use_gate_act: bool = False, use_grid_mlp: bool = False, use_sep_s2_act: bool = True, alpha_drop: float = 0.1, drop_path_rate: float = 0.05, proj_drop: float = 0.0, weight_init: str = 'normal', enforce_max_neighbors_strictly: bool = True, avg_num_nodes: float | None = None, avg_degree: float | None = None, use_energy_lin_ref: bool | None = False, load_energy_lin_ref: bool | None = False) +.. py:function:: eqv2_init_weights(m, weight_init) + +.. py:function:: eqv2_uniform_init_linear_weights(m) + +.. py:class:: EquiformerV2Backbone(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = True, max_neighbors: int = 500, max_radius: float = 5.0, max_num_elements: int = 90, num_layers: int = 12, sphere_channels: int = 128, attn_hidden_channels: int = 128, num_heads: int = 8, attn_alpha_channels: int = 32, attn_value_channels: int = 16, ffn_hidden_channels: int = 512, norm_type: str = 'rms_norm_sh', lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, grid_resolution: int | None = None, num_sphere_samples: int = 128, edge_channels: int = 128, use_atom_edge_embedding: bool = True, share_atom_edge_embedding: bool = False, use_m_share_rad: bool = False, distance_function: str = 'gaussian', num_distance_basis: int = 512, attn_activation: str = 'scaled_silu', use_s2_act_attn: bool = False, use_attn_renorm: bool = True, ffn_activation: str = 'scaled_silu', use_gate_act: bool = False, use_grid_mlp: bool = False, use_sep_s2_act: bool = True, alpha_drop: float = 0.1, drop_path_rate: float = 0.05, proj_drop: float = 0.0, weight_init: str = 'normal', enforce_max_neighbors_strictly: bool = True, avg_num_nodes: float | None = None, avg_degree: float | None = None, use_energy_lin_ref: bool | None = False, load_energy_lin_ref: bool | None = False, activation_checkpoint: bool | None = False) Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.GraphModelMixin` @@ -128,6 +140,9 @@ Module Contents :type load_energy_lin_ref: bool + .. py:attribute:: activation_checkpoint + + .. py:attribute:: use_pbc @@ -296,7 +311,7 @@ Module Contents .. py:attribute:: norm - .. py:attribute:: energy_block + .. py:method:: forward(data: torch_geometric.data.batch.Batch) -> dict[str, torch.Tensor] .. py:method:: _init_gp_partitions(atomic_numbers_full, data_batch_full, edge_index, edge_distance, edge_distance_vec) @@ -307,146 +322,19 @@ Module Contents - .. py:method:: forward(data) - - .. py:method:: _init_edge_rot_mat(data, edge_index, edge_distance_vec) .. py:property:: num_params - .. py:method:: _init_weights(m) - - - .. py:method:: _uniform_init_rad_func_linear_weights(m) - - - .. py:method:: _uniform_init_linear_weights(m) - - .. py:method:: no_weight_decay() -> set Returns a list of parameters with no weight decay. -.. py:class:: EquiformerV2Backbone(*args, **kwargs) - - Bases: :py:obj:`EquiformerV2`, :py:obj:`fairchem.core.models.base.BackboneInterface` - - - Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation - - :param use_pbc: Use periodic boundary conditions - :type use_pbc: bool - :param use_pbc_single: Process batch PBC graphs one at a time - :type use_pbc_single: bool - :param regress_forces: Compute forces - :type regress_forces: bool - :param otf_graph: Compute graph On The Fly (OTF) - :type otf_graph: bool - :param max_neighbors: Maximum number of neighbors per atom - :type max_neighbors: int - :param max_radius: Maximum distance between nieghboring atoms in Angstroms - :type max_radius: float - :param max_num_elements: Maximum atomic number - :type max_num_elements: int - :param num_layers: Number of layers in the GNN - :type num_layers: int - :param sphere_channels: Number of spherical channels (one set per resolution) - :type sphere_channels: int - :param attn_hidden_channels: Number of hidden channels used during SO(2) graph attention - :type attn_hidden_channels: int - :param num_heads: Number of attention heads - :type num_heads: int - :param attn_alpha_head: Number of channels for alpha vector in each attention head - :type attn_alpha_head: int - :param attn_value_head: Number of channels for value vector in each attention head - :type attn_value_head: int - :param ffn_hidden_channels: Number of hidden channels used during feedforward network - :type ffn_hidden_channels: int - :param norm_type: Type of normalization layer (['layer_norm', 'layer_norm_sh', 'rms_norm_sh']) - :type norm_type: str - :param lmax_list: List of maximum degree of the spherical harmonics (1 to 10) - :type lmax_list: int - :param mmax_list: List of maximum order of the spherical harmonics (0 to lmax) - :type mmax_list: int - :param grid_resolution: Resolution of SO3_Grid - :type grid_resolution: int - :param num_sphere_samples: Number of samples used to approximate the integration of the sphere in the output blocks - :type num_sphere_samples: int - :param edge_channels: Number of channels for the edge invariant features - :type edge_channels: int - :param use_atom_edge_embedding: Whether to use atomic embedding along with relative distance for edge scalar features - :type use_atom_edge_embedding: bool - :param share_atom_edge_embedding: Whether to share `atom_edge_embedding` across all blocks - :type share_atom_edge_embedding: bool - :param use_m_share_rad: Whether all m components within a type-L vector of one channel share radial function weights - :type use_m_share_rad: bool - :param distance_function: Basis function used for distances - :type distance_function: "gaussian", "sigmoid", "linearsigmoid", "silu" - :param attn_activation: Type of activation function for SO(2) graph attention - :type attn_activation: str - :param use_s2_act_attn: Whether to use attention after S2 activation. Otherwise, use the same attention as Equiformer - :type use_s2_act_attn: bool - :param use_attn_renorm: Whether to re-normalize attention weights - :type use_attn_renorm: bool - :param ffn_activation: Type of activation function for feedforward network - :type ffn_activation: str - :param use_gate_act: If `True`, use gate activation. Otherwise, use S2 activation - :type use_gate_act: bool - :param use_grid_mlp: If `True`, use projecting to grids and performing MLPs for FFNs. - :type use_grid_mlp: bool - :param use_sep_s2_act: If `True`, use separable S2 activation when `use_gate_act` is False. - :type use_sep_s2_act: bool - :param alpha_drop: Dropout rate for attention weights - :type alpha_drop: float - :param drop_path_rate: Drop path rate - :type drop_path_rate: float - :param proj_drop: Dropout rate for outputs of attention and FFN in Transformer blocks - :type proj_drop: float - :param weight_init: ['normal', 'uniform'] initialization of weights of linear layers except those in radial functions - :type weight_init: str - :param enforce_max_neighbors_strictly: When edges are subselected based on the `max_neighbors` arg, arbitrarily select amongst equidistant / degenerate edges to have exactly the correct number. - :type enforce_max_neighbors_strictly: bool - :param avg_num_nodes: Average number of nodes per graph - :type avg_num_nodes: float - :param avg_degree: Average degree of nodes in the graph - :type avg_degree: float - :param use_energy_lin_ref: Whether to add the per-atom energy references during prediction. - During training and validation, this should be kept `False` since we use the `lin_ref` parameter in the OC22 dataloader to subtract the per-atom linear references from the energy targets. - During prediction (where we don't have energy targets), this can be set to `True` to add the per-atom linear references to the predicted energies. - :type use_energy_lin_ref: bool - :param load_energy_lin_ref: Whether to add nn.Parameters for the per-element energy references. - This additional flag is there to ensure compatibility when strict-loading checkpoints, since the `use_energy_lin_ref` flag can be either True or False even if the model is trained with linear references. - You can't have use_energy_lin_ref = True and load_energy_lin_ref = False, since the model will not have the parameters for the linear references. All other combinations are fine. - :type load_energy_lin_ref: bool - - - .. py:attribute:: energy_block - :value: None - - - - .. py:attribute:: force_block - :value: None - - - - .. py:method:: forward(data: torch_geometric.data.batch.Batch) -> dict[str, torch.Tensor] - - Backbone forward. - - :param data: Atomic systems as input - :type data: DataBatch - - :returns: **embedding** -- Return backbone embeddings for the given input - :rtype: dict[str->torch.Tensor] - - - -.. py:class:: EquiformerV2EnergyHead(backbone) +.. py:class:: EquiformerV2EnergyHead(backbone, reduce: str = 'sum') Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.HeadInterface` @@ -483,6 +371,9 @@ Module Contents :vartype training: bool + .. py:attribute:: reduce + + .. py:attribute:: avg_num_nodes @@ -540,6 +431,9 @@ Module Contents :vartype training: bool + .. py:attribute:: activation_checkpoint + + .. py:attribute:: force_block diff --git a/_sources/autoapi/core/models/equiformer_v2/equiformer_v2_deprecated/index.rst b/_sources/autoapi/core/models/equiformer_v2/equiformer_v2_deprecated/index.rst new file mode 100644 index 0000000000..94cb246c23 --- /dev/null +++ b/_sources/autoapi/core/models/equiformer_v2/equiformer_v2_deprecated/index.rst @@ -0,0 +1,332 @@ +core.models.equiformer_v2.equiformer_v2_deprecated +================================================== + +.. py:module:: core.models.equiformer_v2.equiformer_v2_deprecated + + +Attributes +---------- + +.. autoapisummary:: + + core.models.equiformer_v2.equiformer_v2_deprecated._AVG_NUM_NODES + core.models.equiformer_v2.equiformer_v2_deprecated._AVG_DEGREE + + +Classes +------- + +.. autoapisummary:: + + core.models.equiformer_v2.equiformer_v2_deprecated.EquiformerV2 + + +Module Contents +--------------- + +.. py:data:: _AVG_NUM_NODES + :value: 77.81317 + + +.. py:data:: _AVG_DEGREE + :value: 23.395238876342773 + + +.. py:class:: EquiformerV2(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = True, max_neighbors: int = 500, max_radius: float = 5.0, max_num_elements: int = 90, num_layers: int = 12, sphere_channels: int = 128, attn_hidden_channels: int = 128, num_heads: int = 8, attn_alpha_channels: int = 32, attn_value_channels: int = 16, ffn_hidden_channels: int = 512, norm_type: str = 'rms_norm_sh', lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, grid_resolution: int | None = None, num_sphere_samples: int = 128, edge_channels: int = 128, use_atom_edge_embedding: bool = True, share_atom_edge_embedding: bool = False, use_m_share_rad: bool = False, distance_function: str = 'gaussian', num_distance_basis: int = 512, attn_activation: str = 'scaled_silu', use_s2_act_attn: bool = False, use_attn_renorm: bool = True, ffn_activation: str = 'scaled_silu', use_gate_act: bool = False, use_grid_mlp: bool = False, use_sep_s2_act: bool = True, alpha_drop: float = 0.1, drop_path_rate: float = 0.05, proj_drop: float = 0.0, weight_init: str = 'normal', enforce_max_neighbors_strictly: bool = True, avg_num_nodes: float | None = None, avg_degree: float | None = None, use_energy_lin_ref: bool | None = False, load_energy_lin_ref: bool | None = False) + + Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.GraphModelMixin` + + + THIS CLASS HAS BEEN DEPRECATED! Please use "EquiformerV2BackboneAndHeads" + + Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation + + :param use_pbc: Use periodic boundary conditions + :type use_pbc: bool + :param use_pbc_single: Process batch PBC graphs one at a time + :type use_pbc_single: bool + :param regress_forces: Compute forces + :type regress_forces: bool + :param otf_graph: Compute graph On The Fly (OTF) + :type otf_graph: bool + :param max_neighbors: Maximum number of neighbors per atom + :type max_neighbors: int + :param max_radius: Maximum distance between nieghboring atoms in Angstroms + :type max_radius: float + :param max_num_elements: Maximum atomic number + :type max_num_elements: int + :param num_layers: Number of layers in the GNN + :type num_layers: int + :param sphere_channels: Number of spherical channels (one set per resolution) + :type sphere_channels: int + :param attn_hidden_channels: Number of hidden channels used during SO(2) graph attention + :type attn_hidden_channels: int + :param num_heads: Number of attention heads + :type num_heads: int + :param attn_alpha_head: Number of channels for alpha vector in each attention head + :type attn_alpha_head: int + :param attn_value_head: Number of channels for value vector in each attention head + :type attn_value_head: int + :param ffn_hidden_channels: Number of hidden channels used during feedforward network + :type ffn_hidden_channels: int + :param norm_type: Type of normalization layer (['layer_norm', 'layer_norm_sh', 'rms_norm_sh']) + :type norm_type: str + :param lmax_list: List of maximum degree of the spherical harmonics (1 to 10) + :type lmax_list: int + :param mmax_list: List of maximum order of the spherical harmonics (0 to lmax) + :type mmax_list: int + :param grid_resolution: Resolution of SO3_Grid + :type grid_resolution: int + :param num_sphere_samples: Number of samples used to approximate the integration of the sphere in the output blocks + :type num_sphere_samples: int + :param edge_channels: Number of channels for the edge invariant features + :type edge_channels: int + :param use_atom_edge_embedding: Whether to use atomic embedding along with relative distance for edge scalar features + :type use_atom_edge_embedding: bool + :param share_atom_edge_embedding: Whether to share `atom_edge_embedding` across all blocks + :type share_atom_edge_embedding: bool + :param use_m_share_rad: Whether all m components within a type-L vector of one channel share radial function weights + :type use_m_share_rad: bool + :param distance_function: Basis function used for distances + :type distance_function: "gaussian", "sigmoid", "linearsigmoid", "silu" + :param attn_activation: Type of activation function for SO(2) graph attention + :type attn_activation: str + :param use_s2_act_attn: Whether to use attention after S2 activation. Otherwise, use the same attention as Equiformer + :type use_s2_act_attn: bool + :param use_attn_renorm: Whether to re-normalize attention weights + :type use_attn_renorm: bool + :param ffn_activation: Type of activation function for feedforward network + :type ffn_activation: str + :param use_gate_act: If `True`, use gate activation. Otherwise, use S2 activation + :type use_gate_act: bool + :param use_grid_mlp: If `True`, use projecting to grids and performing MLPs for FFNs. + :type use_grid_mlp: bool + :param use_sep_s2_act: If `True`, use separable S2 activation when `use_gate_act` is False. + :type use_sep_s2_act: bool + :param alpha_drop: Dropout rate for attention weights + :type alpha_drop: float + :param drop_path_rate: Drop path rate + :type drop_path_rate: float + :param proj_drop: Dropout rate for outputs of attention and FFN in Transformer blocks + :type proj_drop: float + :param weight_init: ['normal', 'uniform'] initialization of weights of linear layers except those in radial functions + :type weight_init: str + :param enforce_max_neighbors_strictly: When edges are subselected based on the `max_neighbors` arg, arbitrarily select amongst equidistant / degenerate edges to have exactly the correct number. + :type enforce_max_neighbors_strictly: bool + :param avg_num_nodes: Average number of nodes per graph + :type avg_num_nodes: float + :param avg_degree: Average degree of nodes in the graph + :type avg_degree: float + :param use_energy_lin_ref: Whether to add the per-atom energy references during prediction. + During training and validation, this should be kept `False` since we use the `lin_ref` parameter in the OC22 dataloader to subtract the per-atom linear references from the energy targets. + During prediction (where we don't have energy targets), this can be set to `True` to add the per-atom linear references to the predicted energies. + :type use_energy_lin_ref: bool + :param load_energy_lin_ref: Whether to add nn.Parameters for the per-element energy references. + This additional flag is there to ensure compatibility when strict-loading checkpoints, since the `use_energy_lin_ref` flag can be either True or False even if the model is trained with linear references. + You can't have use_energy_lin_ref = True and load_energy_lin_ref = False, since the model will not have the parameters for the linear references. All other combinations are fine. + :type load_energy_lin_ref: bool + + + .. py:attribute:: use_pbc + + + .. py:attribute:: use_pbc_single + + + .. py:attribute:: regress_forces + + + .. py:attribute:: otf_graph + + + .. py:attribute:: max_neighbors + + + .. py:attribute:: max_radius + + + .. py:attribute:: cutoff + + + .. py:attribute:: max_num_elements + + + .. py:attribute:: num_layers + + + .. py:attribute:: sphere_channels + + + .. py:attribute:: attn_hidden_channels + + + .. py:attribute:: num_heads + + + .. py:attribute:: attn_alpha_channels + + + .. py:attribute:: attn_value_channels + + + .. py:attribute:: ffn_hidden_channels + + + .. py:attribute:: norm_type + + + .. py:attribute:: lmax_list + + + .. py:attribute:: mmax_list + + + .. py:attribute:: grid_resolution + + + .. py:attribute:: num_sphere_samples + + + .. py:attribute:: edge_channels + + + .. py:attribute:: use_atom_edge_embedding + + + .. py:attribute:: share_atom_edge_embedding + + + .. py:attribute:: use_m_share_rad + + + .. py:attribute:: distance_function + + + .. py:attribute:: num_distance_basis + + + .. py:attribute:: attn_activation + + + .. py:attribute:: use_s2_act_attn + + + .. py:attribute:: use_attn_renorm + + + .. py:attribute:: ffn_activation + + + .. py:attribute:: use_gate_act + + + .. py:attribute:: use_grid_mlp + + + .. py:attribute:: use_sep_s2_act + + + .. py:attribute:: alpha_drop + + + .. py:attribute:: drop_path_rate + + + .. py:attribute:: proj_drop + + + .. py:attribute:: avg_num_nodes + + + .. py:attribute:: avg_degree + + + .. py:attribute:: use_energy_lin_ref + + + .. py:attribute:: load_energy_lin_ref + + + .. py:attribute:: weight_init + + + .. py:attribute:: enforce_max_neighbors_strictly + + + .. py:attribute:: device + :value: 'cpu' + + + + .. py:attribute:: grad_forces + :value: False + + + + .. py:attribute:: num_resolutions + :type: int + + + .. py:attribute:: sphere_channels_all + :type: int + + + .. py:attribute:: sphere_embedding + + + .. py:attribute:: edge_channels_list + + + .. py:attribute:: SO3_rotation + + + .. py:attribute:: mappingReduced + + + .. py:attribute:: SO3_grid + + + .. py:attribute:: edge_degree_embedding + + + .. py:attribute:: blocks + + + .. py:attribute:: norm + + + .. py:attribute:: energy_block + + + .. py:method:: _init_gp_partitions(atomic_numbers_full, data_batch_full, edge_index, edge_distance, edge_distance_vec) + + Graph Parallel + This creates the required partial tensors for each rank given the full tensors. + The tensors are split on the dimension along the node index using node_partition. + + + + .. py:method:: forward(data) + + + .. py:method:: _init_edge_rot_mat(data, edge_index, edge_distance_vec) + + + .. py:property:: num_params + + + .. py:method:: _init_weights(m) + + + .. py:method:: _uniform_init_rad_func_linear_weights(m) + + + .. py:method:: _uniform_init_linear_weights(m) + + + .. py:method:: no_weight_decay() -> set + + Returns a list of parameters with no weight decay. + + + diff --git a/_sources/autoapi/core/models/equiformer_v2/eqv2_to_eqv2_hydra/index.rst b/_sources/autoapi/core/models/equiformer_v2/eqv2_to_eqv2_hydra/index.rst new file mode 100644 index 0000000000..d47c5c9ee1 --- /dev/null +++ b/_sources/autoapi/core/models/equiformer_v2/eqv2_to_eqv2_hydra/index.rst @@ -0,0 +1,19 @@ +core.models.equiformer_v2.eqv2_to_eqv2_hydra +============================================ + +.. py:module:: core.models.equiformer_v2.eqv2_to_eqv2_hydra + + +Functions +--------- + +.. autoapisummary:: + + core.models.equiformer_v2.eqv2_to_eqv2_hydra.convert_checkpoint_and_config_to_hydra + + +Module Contents +--------------- + +.. py:function:: convert_checkpoint_and_config_to_hydra(yaml_fn, checkpoint_fn, new_yaml_fn, new_checkpoint_fn) + diff --git a/_sources/autoapi/core/models/equiformer_v2/index.rst b/_sources/autoapi/core/models/equiformer_v2/index.rst index 452b29a995..452c7e846b 100644 --- a/_sources/autoapi/core/models/equiformer_v2/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/index.rst @@ -10,6 +10,7 @@ Subpackages .. toctree:: :maxdepth: 1 + /autoapi/core/models/equiformer_v2/prediction_heads/index /autoapi/core/models/equiformer_v2/trainers/index @@ -23,6 +24,8 @@ Submodules /autoapi/core/models/equiformer_v2/drop/index /autoapi/core/models/equiformer_v2/edge_rot_mat/index /autoapi/core/models/equiformer_v2/equiformer_v2/index + /autoapi/core/models/equiformer_v2/equiformer_v2_deprecated/index + /autoapi/core/models/equiformer_v2/eqv2_to_eqv2_hydra/index /autoapi/core/models/equiformer_v2/gaussian_rbf/index /autoapi/core/models/equiformer_v2/input_block/index /autoapi/core/models/equiformer_v2/layer_norm/index @@ -50,6 +53,8 @@ Package Contents Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.GraphModelMixin` + THIS CLASS HAS BEEN DEPRECATED! Please use "EquiformerV2BackboneAndHeads" + Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation :param use_pbc: Use periodic boundary conditions diff --git a/_sources/autoapi/core/models/equiformer_v2/layer_norm/index.rst b/_sources/autoapi/core/models/equiformer_v2/layer_norm/index.rst index f0c2a24a50..572d3af5dc 100644 --- a/_sources/autoapi/core/models/equiformer_v2/layer_norm/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/layer_norm/index.rst @@ -95,9 +95,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:method:: forward(node_input) @@ -138,9 +135,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:method:: forward(node_input) @@ -173,9 +167,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:method:: forward(node_input) @@ -218,9 +209,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:method:: forward(node_input) @@ -254,9 +242,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:method:: forward(node_input) diff --git a/_sources/autoapi/core/models/equiformer_v2/prediction_heads/index.rst b/_sources/autoapi/core/models/equiformer_v2/prediction_heads/index.rst new file mode 100644 index 0000000000..dc747b9a17 --- /dev/null +++ b/_sources/autoapi/core/models/equiformer_v2/prediction_heads/index.rst @@ -0,0 +1,77 @@ +core.models.equiformer_v2.prediction_heads +========================================== + +.. py:module:: core.models.equiformer_v2.prediction_heads + + +Submodules +---------- + +.. toctree:: + :maxdepth: 1 + + /autoapi/core/models/equiformer_v2/prediction_heads/rank2/index + + +Classes +------- + +.. autoapisummary:: + + core.models.equiformer_v2.prediction_heads.Rank2SymmetricTensorHead + + +Package Contents +---------------- + +.. py:class:: Rank2SymmetricTensorHead(backbone: fairchem.core.models.base.BackboneInterface, output_name: str, decompose: bool = False, edge_level_mlp: bool = False, num_mlp_layers: int = 2, use_source_target_embedding: bool = False, extensive: bool = False, avg_num_nodes: int = 1.0, default_norm_type: str = 'layer_norm_sh') + + Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.HeadInterface` + + + A rank 2 symmetric tensor prediction head. + + .. attribute:: ouput_name + + name of output prediction property (ie, stress) + + .. attribute:: sphharm_norm + + layer normalization for spherical harmonic edge weights + + .. attribute:: xedge_layer_norm + + embedding layer norm + + .. attribute:: block + + rank 2 equivariant symmetric tensor block + + + .. py:attribute:: output_name + + + .. py:attribute:: decompose + + + .. py:attribute:: use_source_target_embedding + + + .. py:attribute:: avg_num_nodes + + + .. py:attribute:: sphharm_norm + + + .. py:attribute:: xedge_layer_norm + + + .. py:method:: forward(data: dict[str, torch.Tensor] | torch.Tensor, emb: dict[str, torch.Tensor]) -> dict[str, torch.Tensor] + + :param data: data batch + :param emb: dictionary with embedding object and graph data + + Returns: dict of {output property name: predicted value} + + + diff --git a/_sources/autoapi/core/models/equiformer_v2/prediction_heads/rank2/index.rst b/_sources/autoapi/core/models/equiformer_v2/prediction_heads/rank2/index.rst new file mode 100644 index 0000000000..15963c22b0 --- /dev/null +++ b/_sources/autoapi/core/models/equiformer_v2/prediction_heads/rank2/index.rst @@ -0,0 +1,174 @@ +core.models.equiformer_v2.prediction_heads.rank2 +================================================ + +.. py:module:: core.models.equiformer_v2.prediction_heads.rank2 + +.. autoapi-nested-parse:: + + Copyright (c) Meta, Inc. and its affiliates. + + This source code is licensed under the MIT license found in the + LICENSE file in the root directory of this source tree. + + + +Classes +------- + +.. autoapisummary:: + + core.models.equiformer_v2.prediction_heads.rank2.Rank2Block + core.models.equiformer_v2.prediction_heads.rank2.Rank2DecompositionEdgeBlock + core.models.equiformer_v2.prediction_heads.rank2.Rank2SymmetricTensorHead + + +Module Contents +--------------- + +.. py:class:: Rank2Block(emb_size: int, num_layers: int = 2, edge_level: bool = False, extensive: bool = False) + + Bases: :py:obj:`torch.nn.Module` + + + Output block for predicting rank-2 tensors (stress, dielectric tensor). + Applies outer product between edges and computes node-wise or edge-wise MLP. + + :param emb_size: Size of edge embedding used to compute outer product + :type emb_size: int + :param num_layers: Number of layers of the MLP + :type num_layers: int + :param edge_level: If true apply MLP at edge level before pooling, otherwise use MLP at nodes after pooling + :type edge_level: bool + :param extensive: Whether to sum or average the outer products + :type extensive: bool + + + .. py:attribute:: edge_level + + + .. py:attribute:: emb_size + + + .. py:attribute:: extensive + + + .. py:attribute:: scalar_nonlinearity + + + .. py:attribute:: r2tensor_MLP + + + .. py:method:: forward(edge_distance_vec, x_edge, edge_index, data) + + :param edge_distance_vec: Tensor of shape (..., 3) + :type edge_distance_vec: torch.Tensor + :param x_edge: Tensor of shape (..., emb_size) + :type x_edge: torch.Tensor + :param edge_index: Tensor of shape (2, nEdges) + :type edge_index: torch.Tensor + :param data: LMDBDataset sample + + + +.. py:class:: Rank2DecompositionEdgeBlock(emb_size: int, num_layers: int = 2, edge_level: bool = False, extensive: bool = False) + + Bases: :py:obj:`torch.nn.Module` + + + Output block for predicting rank-2 tensors (stress, dielectric tensor, etc). + Decomposes a rank-2 symmetric tensor into irrep degree 0 and 2. + + :param emb_size: Size of edge embedding used to compute outer product + :type emb_size: int + :param num_layers: Number of layers of the MLP + :type num_layers: int + :param edge_level: If true apply MLP at edge level before pooling, otherwise use MLP at nodes after pooling + :type edge_level: bool + :param extensive: Whether to sum or average the outer products + :type extensive: bool + + + .. py:attribute:: emb_size + + + .. py:attribute:: edge_level + + + .. py:attribute:: extensive + + + .. py:attribute:: scalar_nonlinearity + + + .. py:attribute:: scalar_MLP + + + .. py:attribute:: irrep2_MLP + + + .. py:attribute:: change_mat + + + .. py:method:: forward(edge_distance_vec, x_edge, edge_index, data) + + :param edge_distance_vec: Tensor of shape (..., 3) + :type edge_distance_vec: torch.Tensor + :param x_edge: Tensor of shape (..., emb_size) + :type x_edge: torch.Tensor + :param edge_index: Tensor of shape (2, nEdges) + :type edge_index: torch.Tensor + :param data: LMDBDataset sample + + + +.. py:class:: Rank2SymmetricTensorHead(backbone: fairchem.core.models.base.BackboneInterface, output_name: str, decompose: bool = False, edge_level_mlp: bool = False, num_mlp_layers: int = 2, use_source_target_embedding: bool = False, extensive: bool = False, avg_num_nodes: int = 1.0, default_norm_type: str = 'layer_norm_sh') + + Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.HeadInterface` + + + A rank 2 symmetric tensor prediction head. + + .. attribute:: ouput_name + + name of output prediction property (ie, stress) + + .. attribute:: sphharm_norm + + layer normalization for spherical harmonic edge weights + + .. attribute:: xedge_layer_norm + + embedding layer norm + + .. attribute:: block + + rank 2 equivariant symmetric tensor block + + + .. py:attribute:: output_name + + + .. py:attribute:: decompose + + + .. py:attribute:: use_source_target_embedding + + + .. py:attribute:: avg_num_nodes + + + .. py:attribute:: sphharm_norm + + + .. py:attribute:: xedge_layer_norm + + + .. py:method:: forward(data: dict[str, torch.Tensor] | torch.Tensor, emb: dict[str, torch.Tensor]) -> dict[str, torch.Tensor] + + :param data: data batch + :param emb: dictionary with embedding object and graph data + + Returns: dict of {output property name: predicted value} + + + diff --git a/_sources/autoapi/core/models/equiformer_v2/radial_function/index.rst b/_sources/autoapi/core/models/equiformer_v2/radial_function/index.rst index 3e7f63a38c..adc0a3e233 100644 --- a/_sources/autoapi/core/models/equiformer_v2/radial_function/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/radial_function/index.rst @@ -27,6 +27,28 @@ Module Contents :value: [] + Return an iterator over all modules in the network. + + :Yields: *Module* -- a module in the network + + .. note:: + + Duplicate modules are returned only once. In the following + example, ``l`` will be returned only once. + + Example:: + + >>> l = nn.Linear(2, 2) + >>> net = nn.Sequential(l, l) + >>> for idx, m in enumerate(net.modules()): + ... print(idx, '->', m) + + 0 -> Sequential( + (0): Linear(in_features=2, out_features=2, bias=True) + (1): Linear(in_features=2, out_features=2, bias=True) + ) + 1 -> Linear(in_features=2, out_features=2, bias=True) + .. py:attribute:: input_channels diff --git a/_sources/autoapi/core/models/equiformer_v2/so3/index.rst b/_sources/autoapi/core/models/equiformer_v2/so3/index.rst index 8e628b2d13..aed875c146 100644 --- a/_sources/autoapi/core/models/equiformer_v2/so3/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/so3/index.rst @@ -111,9 +111,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:class:: SO3_Embedding(length: int, lmax_list: list[int], num_channels: int, device: torch.device, dtype: torch.dtype) @@ -317,9 +314,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:class:: SO3_LinearV2(in_features: int, out_features: int, lmax: int, bias: bool = True) @@ -384,7 +378,4 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - diff --git a/_sources/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.rst b/_sources/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.rst index 8e6b461486..196a4b0b02 100644 --- a/_sources/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.rst @@ -23,7 +23,7 @@ Classes Module Contents --------------- -.. py:class:: EquiformerV2EnergyTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier, timestamp_id=None, run_dir=None, is_debug=False, print_every=100, seed=None, logger='wandb', local_rank=0, amp=False, cpu=False, slurm=None, noddp=False, name='ocp', gp_gpus=None) +.. py:class:: EquiformerV2EnergyTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False) Bases: :py:obj:`fairchem.core.trainers.OCPTrainer` @@ -68,17 +68,12 @@ Module Contents :param logger: Type of logger to be used. (default: :obj:`wandb`) :type logger: str, optional - :param local_rank: Local rank of the process, only applicable for distributed training. - (default: :obj:`0`) - :type local_rank: int, optional :param amp: Run using automatic mixed precision. (default: :obj:`False`) :type amp: bool, optional :param slurm: Slurm configuration. Currently just for keeping track. (default: :obj:`{}`) :type slurm: dict - :param noddp: Run model without DDP. - :type noddp: bool, optional .. py:method:: load_extras() diff --git a/_sources/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.rst b/_sources/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.rst index 22c41789ff..fcde30d1e2 100644 --- a/_sources/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.rst +++ b/_sources/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.rst @@ -23,7 +23,7 @@ Classes Module Contents --------------- -.. py:class:: EquiformerV2ForcesTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier, timestamp_id=None, run_dir=None, is_debug=False, print_every=100, seed=None, logger='wandb', local_rank=0, amp=False, cpu=False, slurm=None, noddp=False, name='ocp', gp_gpus=None) +.. py:class:: EquiformerV2ForcesTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False) Bases: :py:obj:`fairchem.core.trainers.OCPTrainer` @@ -68,17 +68,12 @@ Module Contents :param logger: Type of logger to be used. (default: :obj:`wandb`) :type logger: str, optional - :param local_rank: Local rank of the process, only applicable for distributed training. - (default: :obj:`0`) - :type local_rank: int, optional :param amp: Run using automatic mixed precision. (default: :obj:`False`) :type amp: bool, optional :param slurm: Slurm configuration. Currently just for keeping track. (default: :obj:`{}`) :type slurm: dict - :param noddp: Run model without DDP. - :type noddp: bool, optional .. py:method:: load_extras() -> None diff --git a/_sources/autoapi/core/models/escn/escn/index.rst b/_sources/autoapi/core/models/escn/escn/index.rst index 3977626f37..88a24a439b 100644 --- a/_sources/autoapi/core/models/escn/escn/index.rst +++ b/_sources/autoapi/core/models/escn/escn/index.rst @@ -33,7 +33,7 @@ Classes Module Contents --------------- -.. py:class:: eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False) +.. py:class:: eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False, resolution: int | None = None) Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.GraphModelMixin` @@ -195,7 +195,7 @@ Module Contents -.. py:class:: eSCNBackbone(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False) +.. py:class:: eSCNBackbone(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False, resolution: int | None = None) Bases: :py:obj:`eSCN`, :py:obj:`fairchem.core.models.base.BackboneInterface` @@ -254,7 +254,7 @@ Module Contents -.. py:class:: eSCNEnergyHead(backbone) +.. py:class:: eSCNEnergyHead(backbone, reduce='sum') Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.HeadInterface` @@ -296,6 +296,9 @@ Module Contents + .. py:attribute:: reduce + + .. py:method:: forward(data: torch_geometric.data.batch.Batch, emb: dict[str, torch.Tensor]) -> dict[str, torch.Tensor] Head forward. diff --git a/_sources/autoapi/core/models/escn/escn_exportable/index.rst b/_sources/autoapi/core/models/escn/escn_exportable/index.rst new file mode 100644 index 0000000000..6032220b04 --- /dev/null +++ b/_sources/autoapi/core/models/escn/escn_exportable/index.rst @@ -0,0 +1,526 @@ +core.models.escn.escn_exportable +================================ + +.. py:module:: core.models.escn.escn_exportable + +.. autoapi-nested-parse:: + + Copyright (c) Meta, Inc. and its affiliates. + + This source code is licensed under the MIT license found in the + LICENSE file in the root directory of this source tree. + + + +Classes +------- + +.. autoapisummary:: + + core.models.escn.escn_exportable.eSCN + core.models.escn.escn_exportable.LayerBlock + core.models.escn.escn_exportable.MessageBlock + core.models.escn.escn_exportable.SO2Block + core.models.escn.escn_exportable.SO2Conv + core.models.escn.escn_exportable.EdgeBlock + core.models.escn.escn_exportable.EnergyBlock + core.models.escn.escn_exportable.ForceBlock + + +Module Contents +--------------- + +.. py:class:: eSCN(regress_forces: bool = True, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax: int = 4, mmax: int = 2, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, resolution: int | None = None) + + Bases: :py:obj:`torch.nn.Module` + + + Equivariant Spherical Channel Network + Paper: Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs + + + :param regress_forces: Compute forces + :type regress_forces: bool + :param cutoff: Maximum distance between nieghboring atoms in Angstroms + :type cutoff: float + :param max_num_elements: Maximum atomic number + :type max_num_elements: int + :param num_layers: Number of layers in the GNN + :type num_layers: int + :param lmax: maximum degree of the spherical harmonics (1 to 10) + :type lmax: int + :param mmax: maximum order of the spherical harmonics (0 to lmax) + :type mmax: int + :param sphere_channels: Number of spherical channels (one set per resolution) + :type sphere_channels: int + :param hidden_channels: Number of hidden units in message passing + :type hidden_channels: int + :param num_sphere_samples: Number of samples used to approximate the integration of the sphere in the output blocks + :type num_sphere_samples: int + :param edge_channels: Number of channels for the edge invariant features + :type edge_channels: int + :param distance_function: Basis function used for distances + :type distance_function: "gaussian", "sigmoid", "linearsigmoid", "silu" + :param basis_width_scalar: Width of distance basis function + :type basis_width_scalar: float + :param distance_resolution: Distance between distance basis functions in Angstroms + :type distance_resolution: float + + + .. py:attribute:: regress_forces + + + .. py:attribute:: cutoff + + + .. py:attribute:: max_num_elements + + + .. py:attribute:: hidden_channels + + + .. py:attribute:: num_layers + + + .. py:attribute:: num_sphere_samples + + + .. py:attribute:: sphere_channels + + + .. py:attribute:: edge_channels + + + .. py:attribute:: distance_resolution + + + .. py:attribute:: lmax + + + .. py:attribute:: mmax + + + .. py:attribute:: basis_width_scalar + + + .. py:attribute:: distance_function + + + .. py:attribute:: act + + + .. py:attribute:: sphere_embedding + + + .. py:attribute:: num_gaussians + + + .. py:attribute:: SO3_grid + + + .. py:attribute:: mappingReduced + + + .. py:attribute:: layer_blocks + + + .. py:attribute:: energy_block + + + .. py:attribute:: sphere_points + + + .. py:attribute:: sphharm_weights + :type: torch.nn.Parameter + + + .. py:method:: forward(data: dict[str, torch.Tensor]) -> dict[str, torch.Tensor] + + + .. py:method:: _init_edge_rot_mat(edge_index, edge_distance_vec) + + + .. py:property:: num_params + :type: int + + + +.. py:class:: LayerBlock(layer_idx: int, sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, distance_expansion, max_num_elements: int, SO3_grid: fairchem.core.models.escn.so3_exportable.SO3_Grid, act, mappingReduced) + + Bases: :py:obj:`torch.nn.Module` + + + Layer block: Perform one layer (message passing and aggregation) of the GNN + + :param layer_idx: Layer number + :type layer_idx: int + :param sphere_channels: Number of spherical channels + :type sphere_channels: int + :param hidden_channels: Number of hidden channels used during the SO(2) conv + :type hidden_channels: int + :param edge_channels: Size of invariant edge embedding + :type edge_channels: int + :param lmax: + :type lmax: int) degrees (l + :param mmax: orders (m) for each resolution + :type mmax: int + :param distance_expansion: Function used to compute distance embedding + :type distance_expansion: func + :param max_num_elements: Maximum number of atomic numbers + :type max_num_elements: int + :param SO3_grid: Class used to convert from grid the spherical harmonic representations + :type SO3_grid: SO3_grid + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: layer_idx + + + .. py:attribute:: act + + + .. py:attribute:: lmax + + + .. py:attribute:: mmax + + + .. py:attribute:: sphere_channels + + + .. py:attribute:: SO3_grid + + + .. py:attribute:: mappingReduced + + + .. py:attribute:: message_block + + + .. py:attribute:: fc1_sphere + + + .. py:attribute:: fc2_sphere + + + .. py:attribute:: fc3_sphere + + + .. py:method:: forward(x: torch.Tensor, atomic_numbers: torch.Tensor, edge_distance: torch.Tensor, edge_index: torch.Tensor, wigner: torch.Tensor) -> torch.Tensor + + +.. py:class:: MessageBlock(layer_idx: int, sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, distance_expansion, max_num_elements: int, SO3_grid: fairchem.core.models.escn.so3_exportable.SO3_Grid, act, mappingReduced) + + Bases: :py:obj:`torch.nn.Module` + + + Message block: Perform message passing + + :param layer_idx: Layer number + :type layer_idx: int + :param sphere_channels: Number of spherical channels + :type sphere_channels: int + :param hidden_channels: Number of hidden channels used during the SO(2) conv + :type hidden_channels: int + :param edge_channels: Size of invariant edge embedding + :type edge_channels: int + :param lmax: degrees (l) for each resolution + :type lmax: int + :param mmax: orders (m) for each resolution + :type mmax: int + :param distance_expansion: Function used to compute distance embedding + :type distance_expansion: func + :param max_num_elements: Maximum number of atomic numbers + :type max_num_elements: int + :param SO3_grid: Class used to convert from grid the spherical harmonic representations + :type SO3_grid: SO3_grid + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: layer_idx + + + .. py:attribute:: act + + + .. py:attribute:: hidden_channels + + + .. py:attribute:: sphere_channels + + + .. py:attribute:: SO3_grid + + + .. py:attribute:: lmax + + + .. py:attribute:: mmax + + + .. py:attribute:: edge_channels + + + .. py:attribute:: mappingReduced + + + .. py:attribute:: out_mask + + + .. py:attribute:: edge_block + + + .. py:attribute:: so2_block_source + + + .. py:attribute:: so2_block_target + + + .. py:method:: forward(x: torch.Tensor, atomic_numbers: torch.Tensor, edge_distance: torch.Tensor, edge_index: torch.Tensor, wigner: torch.Tensor) -> torch.Tensor + + +.. py:class:: SO2Block(sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, act, mappingReduced) + + Bases: :py:obj:`torch.nn.Module` + + + SO(2) Block: Perform SO(2) convolutions for all m (orders) + + :param sphere_channels: Number of spherical channels + :type sphere_channels: int + :param hidden_channels: Number of hidden channels used during the SO(2) conv + :type hidden_channels: int + :param edge_channels: Size of invariant edge embedding + :type edge_channels: int + :param lmax: degrees (l) for each resolution + :type lmax: int + :param mmax: orders (m) for each resolution + :type mmax: int + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: sphere_channels + + + .. py:attribute:: hidden_channels + + + .. py:attribute:: lmax + + + .. py:attribute:: mmax + + + .. py:attribute:: act + + + .. py:attribute:: mappingReduced + + + .. py:attribute:: num_channels_m0 + + + .. py:attribute:: fc1_dist0 + + + .. py:attribute:: fc1_m0 + + + .. py:attribute:: fc2_m0 + + + .. py:attribute:: so2_conv + + + .. py:method:: forward(x: torch.Tensor, x_edge: torch.Tensor) + + +.. py:class:: SO2Conv(m: int, sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, act) + + Bases: :py:obj:`torch.nn.Module` + + + SO(2) Conv: Perform an SO(2) convolution + + :param m: Order of the spherical harmonic coefficients + :type m: int + :param sphere_channels: Number of spherical channels + :type sphere_channels: int + :param hidden_channels: Number of hidden channels used during the SO(2) conv + :type hidden_channels: int + :param edge_channels: Size of invariant edge embedding + :type edge_channels: int + :param lmax: degrees (l) for each resolution + :type lmax: int + :param mmax: orders (m) for each resolution + :type mmax: int + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: hidden_channels + + + .. py:attribute:: lmax + + + .. py:attribute:: mmax + + + .. py:attribute:: sphere_channels + + + .. py:attribute:: m + + + .. py:attribute:: act + + + .. py:attribute:: num_coefficents + :value: 0 + + + + .. py:attribute:: num_channels + + + .. py:attribute:: fc1_dist + + + .. py:attribute:: fc1_r + + + .. py:attribute:: fc2_r + + + .. py:attribute:: fc1_i + + + .. py:attribute:: fc2_i + + + .. py:method:: forward(x_m, x_edge) -> torch.Tensor + + +.. py:class:: EdgeBlock(edge_channels, distance_expansion, max_num_elements, act) + + Bases: :py:obj:`torch.nn.Module` + + + Edge Block: Compute invariant edge representation from edge diatances and atomic numbers + + :param edge_channels: Size of invariant edge embedding + :type edge_channels: int + :param distance_expansion: Function used to compute distance embedding + :type distance_expansion: func + :param max_num_elements: Maximum number of atomic numbers + :type max_num_elements: int + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: in_channels + + + .. py:attribute:: distance_expansion + + + .. py:attribute:: act + + + .. py:attribute:: edge_channels + + + .. py:attribute:: max_num_elements + + + .. py:attribute:: fc1_dist + + + .. py:attribute:: source_embedding + + + .. py:attribute:: target_embedding + + + .. py:attribute:: fc1_edge_attr + + + .. py:method:: forward(edge_distance, source_element, target_element) + + +.. py:class:: EnergyBlock(num_channels: int, num_sphere_samples: int, act) + + Bases: :py:obj:`torch.nn.Module` + + + Energy Block: Output block computing the energy + + :param num_channels: Number of channels + :type num_channels: int + :param num_sphere_samples: Number of samples used to approximate the integral on the sphere + :type num_sphere_samples: int + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: num_channels + + + .. py:attribute:: num_sphere_samples + + + .. py:attribute:: act + + + .. py:attribute:: fc1 + + + .. py:attribute:: fc2 + + + .. py:attribute:: fc3 + + + .. py:method:: forward(x_pt) -> torch.Tensor + + +.. py:class:: ForceBlock(num_channels: int, num_sphere_samples: int, act) + + Bases: :py:obj:`torch.nn.Module` + + + Force Block: Output block computing the per atom forces + + :param num_channels: Number of channels + :type num_channels: int + :param num_sphere_samples: Number of samples used to approximate the integral on the sphere + :type num_sphere_samples: int + :param act: Non-linear activation function + :type act: function + + + .. py:attribute:: num_channels + + + .. py:attribute:: num_sphere_samples + + + .. py:attribute:: act + + + .. py:attribute:: fc1 + + + .. py:attribute:: fc2 + + + .. py:attribute:: fc3 + + + .. py:method:: forward(x_pt, sphere_points) -> torch.Tensor + + diff --git a/_sources/autoapi/core/models/escn/index.rst b/_sources/autoapi/core/models/escn/index.rst index 79744c19c4..4dd3c597bb 100644 --- a/_sources/autoapi/core/models/escn/index.rst +++ b/_sources/autoapi/core/models/escn/index.rst @@ -11,7 +11,9 @@ Submodules :maxdepth: 1 /autoapi/core/models/escn/escn/index + /autoapi/core/models/escn/escn_exportable/index /autoapi/core/models/escn/so3/index + /autoapi/core/models/escn/so3_exportable/index Classes @@ -25,7 +27,7 @@ Classes Package Contents ---------------- -.. py:class:: eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False) +.. py:class:: eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False, resolution: int | None = None) Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.GraphModelMixin` diff --git a/_sources/autoapi/core/models/escn/so3/index.rst b/_sources/autoapi/core/models/escn/so3/index.rst index 1e85e54c06..e9b5697c1d 100644 --- a/_sources/autoapi/core/models/escn/so3/index.rst +++ b/_sources/autoapi/core/models/escn/so3/index.rst @@ -206,7 +206,7 @@ Module Contents .. py:method:: _z_rot_mat(angle: torch.Tensor, lv: int) -> torch.Tensor -.. py:class:: SO3_Grid(lmax: int, mmax: int) +.. py:class:: SO3_Grid(lmax: int, mmax: int, resolution: int | None = None) Bases: :py:obj:`torch.nn.Module` diff --git a/_sources/autoapi/core/models/escn/so3_exportable/index.rst b/_sources/autoapi/core/models/escn/so3_exportable/index.rst new file mode 100644 index 0000000000..626920a3c6 --- /dev/null +++ b/_sources/autoapi/core/models/escn/so3_exportable/index.rst @@ -0,0 +1,171 @@ +core.models.escn.so3_exportable +=============================== + +.. py:module:: core.models.escn.so3_exportable + + +Attributes +---------- + +.. autoapisummary:: + + core.models.escn.so3_exportable.__Jd + + +Classes +------- + +.. autoapisummary:: + + core.models.escn.so3_exportable.CoefficientMapping + core.models.escn.so3_exportable.SO3_Grid + + +Functions +--------- + +.. autoapisummary:: + + core.models.escn.so3_exportable.get_jd + core.models.escn.so3_exportable.wigner_D + core.models.escn.so3_exportable._z_rot_mat + core.models.escn.so3_exportable.rotation_to_wigner + + +Module Contents +--------------- + +.. py:data:: __Jd + +.. py:function:: get_jd() -> torch.Tensor + +.. py:function:: wigner_D(lv: int, alpha: torch.Tensor, beta: torch.Tensor, gamma: torch.Tensor) -> torch.Tensor + +.. py:function:: _z_rot_mat(angle: torch.Tensor, lv: int) -> torch.Tensor + +.. py:function:: rotation_to_wigner(edge_rot_mat: torch.Tensor, start_lmax: int, end_lmax: int) -> torch.Tensor + +.. py:class:: CoefficientMapping(lmax_list, mmax_list) + + Bases: :py:obj:`torch.nn.Module` + + + Helper module for coefficients used to reshape l <--> m and to get coefficients of specific degree or order + + :param lmax_list (list: int): List of maximum degree of the spherical harmonics + :param mmax_list (list: int): List of maximum order of the spherical harmonics + :param use_rotate_inv_rescale: Whether to pre-compute inverse rotation rescale matrices + :type use_rotate_inv_rescale: bool + + + .. py:attribute:: lmax_list + + + .. py:attribute:: mmax_list + + + .. py:attribute:: num_resolutions + + + .. py:attribute:: l_harmonic + + + .. py:attribute:: m_harmonic + + + .. py:attribute:: m_complex + + + .. py:attribute:: res_size + + + .. py:attribute:: offset + :value: 0 + + + + .. py:attribute:: num_coefficients + + + .. py:attribute:: to_m + + + .. py:attribute:: m_size + + + .. py:method:: complex_idx(m, lmax, m_complex, l_harmonic) + + Add `m_complex` and `l_harmonic` to the input arguments + since we cannot use `self.m_complex`. + + + + .. py:method:: pre_compute_coefficient_idx() + + Pre-compute the results of `coefficient_idx()` and access them with `prepare_coefficient_idx()` + + + + .. py:method:: prepare_coefficient_idx() + + Construct a list of buffers + + + + .. py:method:: coefficient_idx(lmax: int, mmax: int) + + + .. py:method:: pre_compute_rotate_inv_rescale() + + + .. py:method:: __repr__() + + +.. py:class:: SO3_Grid(lmax: int, mmax: int, normalization: str = 'integral', resolution: int | None = None) + + Bases: :py:obj:`torch.nn.Module` + + + Helper functions for grid representation of the irreps + + :param lmax: Maximum degree of the spherical harmonics + :type lmax: int + :param mmax: Maximum order of the spherical harmonics + :type mmax: int + + + .. py:attribute:: lmax + + + .. py:attribute:: mmax + + + .. py:attribute:: lat_resolution + + + .. py:attribute:: mapping + + + .. py:attribute:: device + :value: 'cpu' + + + + .. py:attribute:: to_grid + + + .. py:attribute:: to_grid_mat + + + .. py:attribute:: from_grid + + + .. py:attribute:: from_grid_mat + + + .. py:method:: get_to_grid_mat(device=None) + + + .. py:method:: get_from_grid_mat(device=None) + + diff --git a/_sources/autoapi/core/models/finetune_hydra/index.rst b/_sources/autoapi/core/models/finetune_hydra/index.rst deleted file mode 100644 index 8703af0ec1..0000000000 --- a/_sources/autoapi/core/models/finetune_hydra/index.rst +++ /dev/null @@ -1,203 +0,0 @@ -core.models.finetune_hydra -========================== - -.. py:module:: core.models.finetune_hydra - - -Attributes ----------- - -.. autoapisummary:: - - core.models.finetune_hydra.FTHYDRA_NAME - - -Classes -------- - -.. autoapisummary:: - - core.models.finetune_hydra.FineTuneMode - core.models.finetune_hydra.FTConfig - core.models.finetune_hydra.FineTuneHydra - - -Functions ---------- - -.. autoapisummary:: - - core.models.finetune_hydra.get_model_config_from_checkpoint - core.models.finetune_hydra.load_hydra_model - - -Module Contents ---------------- - -.. py:data:: FTHYDRA_NAME - :value: 'finetune_hydra' - - -.. py:class:: FineTuneMode(*args, **kwds) - - Bases: :py:obj:`enum.Enum` - - - Create a collection of name/value pairs. - - Example enumeration: - - >>> class Color(Enum): - ... RED = 1 - ... BLUE = 2 - ... GREEN = 3 - - Access them by: - - - attribute access:: - - >>> Color.RED - - - - value lookup: - - >>> Color(1) - - - - name lookup: - - >>> Color['RED'] - - - Enumerations can be iterated over, and know how many members they have: - - >>> len(Color) - 3 - - >>> list(Color) - [, , ] - - Methods can be added to enumerations, and members can have their own - attributes -- see the documentation for details. - - - .. py:attribute:: DATA_ONLY - :value: 1 - - - - .. py:attribute:: RETAIN_BACKBONE_ONLY - :value: 2 - - - -.. py:function:: get_model_config_from_checkpoint(checkpoint_path: str) -> dict - -.. py:function:: load_hydra_model(checkpoint_path: str) -> fairchem.core.models.base.HydraInterface - -.. py:class:: FTConfig(config: dict) - - .. py:attribute:: FT_CONFIG_NAME - :value: 'finetune_config' - - - - .. py:attribute:: STARTING_CHECKPOINT - :value: 'starting_checkpoint' - - - - .. py:attribute:: STARTING_MODEL - :value: 'starting_model' - - - - .. py:attribute:: MODE - :value: 'mode' - - - - .. py:attribute:: HEADS - :value: 'heads' - - - - .. py:attribute:: config - - - .. py:attribute:: _mode - - - .. py:method:: load_model() -> torch.nn.Module - - - .. py:method:: get_standalone_config() -> dict - - - .. py:property:: mode - :type: FineTuneMode - - - - .. py:property:: head_config - :type: dict - - - -.. py:class:: FineTuneHydra(finetune_config: dict) - - Bases: :py:obj:`torch.nn.Module`, :py:obj:`fairchem.core.models.base.HydraInterface` - - - Base class for all neural network modules. - - Your models should also subclass this class. - - Modules can also contain other Modules, allowing to nest them in - a tree structure. You can assign the submodules as regular attributes:: - - import torch.nn as nn - import torch.nn.functional as F - - class Model(nn.Module): - def __init__(self): - super().__init__() - self.conv1 = nn.Conv2d(1, 20, 5) - self.conv2 = nn.Conv2d(20, 20, 5) - - def forward(self, x): - x = F.relu(self.conv1(x)) - return F.relu(self.conv2(x)) - - Submodules assigned in this way will be registered, and will have their - parameters converted too when you call :meth:`to`, etc. - - .. note:: - As per the example above, an ``__init__()`` call to the parent class - must be made before assignment on the child. - - :ivar training: Boolean represents whether this module is in training or - evaluation mode. - :vartype training: bool - - - .. py:attribute:: ft_config - - - .. py:attribute:: hydra_model - :type: fairchem.core.models.base.HydraInterface - - - .. py:attribute:: backbone - :type: fairchem.core.models.base.BackboneInterface - - - .. py:method:: forward(data: torch_geometric.data.Batch) - - - .. py:method:: get_backbone() -> fairchem.core.models.base.BackboneInterface - - - .. py:method:: get_heads() -> dict[str, fairchem.core.models.base.HeadInterface] - - diff --git a/_sources/autoapi/core/models/index.rst b/_sources/autoapi/core/models/index.rst index ba40934668..70d41039c5 100644 --- a/_sources/autoapi/core/models/index.rst +++ b/_sources/autoapi/core/models/index.rst @@ -28,7 +28,6 @@ Submodules /autoapi/core/models/base/index /autoapi/core/models/dimenet_plus_plus/index - /autoapi/core/models/finetune_hydra/index /autoapi/core/models/model_registry/index /autoapi/core/models/schnet/index diff --git a/_sources/autoapi/core/models/painn/index.rst b/_sources/autoapi/core/models/painn/index.rst index 0f7494b1f6..008af8b7c7 100644 --- a/_sources/autoapi/core/models/painn/index.rst +++ b/_sources/autoapi/core/models/painn/index.rst @@ -121,7 +121,4 @@ Package Contents .. py:method:: __repr__() -> str - Return repr(self). - - diff --git a/_sources/autoapi/core/models/painn/painn/index.rst b/_sources/autoapi/core/models/painn/painn/index.rst index 97247a9caf..f68462aa49 100644 --- a/_sources/autoapi/core/models/painn/painn/index.rst +++ b/_sources/autoapi/core/models/painn/painn/index.rst @@ -150,9 +150,6 @@ Module Contents .. py:method:: __repr__() -> str - Return repr(self). - - .. py:class:: PaiNNBackbone(hidden_channels: int = 512, num_layers: int = 6, num_rbf: int = 128, cutoff: float = 12.0, max_neighbors: int = 50, rbf: dict[str, str] | None = None, envelope: dict[str, str | int] | None = None, regress_forces: bool = True, direct_forces: bool = True, use_pbc: bool = True, use_pbc_single: bool = False, otf_graph: bool = True, num_elements: int = 83, scale_file: str | None = None) diff --git a/_sources/autoapi/core/modules/scaling/fit/index.rst b/_sources/autoapi/core/modules/scaling/fit/index.rst index 920d3cf169..30662cf24f 100644 --- a/_sources/autoapi/core/modules/scaling/fit/index.rst +++ b/_sources/autoapi/core/modules/scaling/fit/index.rst @@ -4,6 +4,14 @@ core.modules.scaling.fit .. py:module:: core.modules.scaling.fit +Attributes +---------- + +.. autoapisummary:: + + core.modules.scaling.fit.parser + + Functions --------- @@ -11,7 +19,7 @@ Functions core.modules.scaling.fit._prefilled_input core.modules.scaling.fit._train_batch - core.modules.scaling.fit.main + core.modules.scaling.fit.compute_scaling_factors Module Contents @@ -21,5 +29,7 @@ Module Contents .. py:function:: _train_batch(trainer: fairchem.core.trainers.base_trainer.BaseTrainer, batch) -> None -.. py:function:: main(*, num_batches: int = 16) -> None +.. py:function:: compute_scaling_factors(config, num_batches: int = 16) -> None + +.. py:data:: parser diff --git a/_sources/autoapi/core/preprocessing/atoms_to_graphs/index.rst b/_sources/autoapi/core/preprocessing/atoms_to_graphs/index.rst index 8fb3e41712..30268fa03a 100644 --- a/_sources/autoapi/core/preprocessing/atoms_to_graphs/index.rst +++ b/_sources/autoapi/core/preprocessing/atoms_to_graphs/index.rst @@ -198,6 +198,9 @@ Module Contents + .. py:method:: get_edge_distance_vec(pos, edge_index, cell, cell_offsets) + + .. py:method:: convert(atoms: ase.Atoms, sid=None) Convert a single atomic structure to a graph. diff --git a/_sources/autoapi/core/preprocessing/index.rst b/_sources/autoapi/core/preprocessing/index.rst index fc2b7c8172..704a3a11ae 100644 --- a/_sources/autoapi/core/preprocessing/index.rst +++ b/_sources/autoapi/core/preprocessing/index.rst @@ -192,6 +192,9 @@ Package Contents + .. py:method:: get_edge_distance_vec(pos, edge_index, cell, cell_offsets) + + .. py:method:: convert(atoms: ase.Atoms, sid=None) Convert a single atomic structure to a graph. diff --git a/_sources/autoapi/core/scripts/eqv2_to_hydra_eqv2/index.rst b/_sources/autoapi/core/scripts/eqv2_to_hydra_eqv2/index.rst new file mode 100644 index 0000000000..0e0f9c5dce --- /dev/null +++ b/_sources/autoapi/core/scripts/eqv2_to_hydra_eqv2/index.rst @@ -0,0 +1,19 @@ +core.scripts.eqv2_to_hydra_eqv2 +=============================== + +.. py:module:: core.scripts.eqv2_to_hydra_eqv2 + + +Attributes +---------- + +.. autoapisummary:: + + core.scripts.eqv2_to_hydra_eqv2.parser + + +Module Contents +--------------- + +.. py:data:: parser + diff --git a/_sources/autoapi/core/scripts/index.rst b/_sources/autoapi/core/scripts/index.rst index bd9c6ee940..083caf1d51 100644 --- a/_sources/autoapi/core/scripts/index.rst +++ b/_sources/autoapi/core/scripts/index.rst @@ -29,6 +29,7 @@ Submodules /autoapi/core/scripts/download_data/index /autoapi/core/scripts/download_large_files/index + /autoapi/core/scripts/eqv2_to_hydra_eqv2/index /autoapi/core/scripts/fit_normalizers/index /autoapi/core/scripts/fit_references/index /autoapi/core/scripts/gif_maker_parallelized/index diff --git a/_sources/autoapi/core/trainers/base_trainer/index.rst b/_sources/autoapi/core/trainers/base_trainer/index.rst index 1c31f43805..a996716536 100644 --- a/_sources/autoapi/core/trainers/base_trainer/index.rst +++ b/_sources/autoapi/core/trainers/base_trainer/index.rst @@ -23,7 +23,7 @@ Classes Module Contents --------------- -.. py:class:: BaseTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier: str, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', local_rank: int = 0, amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, noddp: bool = False, gp_gpus: int | None = None) +.. py:class:: BaseTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False) Bases: :py:obj:`abc.ABC` @@ -88,6 +88,16 @@ Module Contents + .. py:attribute:: best_val_metric + :value: None + + + + .. py:attribute:: primary_metric + :value: None + + + .. py:method:: train(disable_eval_tqdm: bool = False) -> None :abstractmethod: @@ -101,10 +111,12 @@ Module Contents - .. py:method:: load() -> None + .. py:method:: load(inference_only: bool) -> None .. py:method:: set_seed(seed) -> None + :staticmethod: + .. py:method:: load_seed_from_config() -> None @@ -137,7 +149,7 @@ Module Contents .. py:property:: _unwrapped_model - .. py:method:: load_checkpoint(checkpoint_path: str, checkpoint: dict | None = None) -> None + .. py:method:: load_checkpoint(checkpoint_path: str, checkpoint: dict | None = None, inference_only: bool | None = None) -> None .. py:method:: load_loss() -> None @@ -155,6 +167,9 @@ Module Contents .. py:method:: update_best(primary_metric, val_metrics, disable_eval_tqdm: bool = True) -> None + .. py:method:: _aggregate_metrics(metrics) + + .. py:method:: validate(split: str = 'val', disable_tqdm: bool = False) diff --git a/_sources/autoapi/core/trainers/index.rst b/_sources/autoapi/core/trainers/index.rst index 7bbddd4d7f..7299f5b840 100644 --- a/_sources/autoapi/core/trainers/index.rst +++ b/_sources/autoapi/core/trainers/index.rst @@ -26,7 +26,7 @@ Classes Package Contents ---------------- -.. py:class:: BaseTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier: str, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', local_rank: int = 0, amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, noddp: bool = False, gp_gpus: int | None = None) +.. py:class:: BaseTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False) Bases: :py:obj:`abc.ABC` @@ -91,6 +91,16 @@ Package Contents + .. py:attribute:: best_val_metric + :value: None + + + + .. py:attribute:: primary_metric + :value: None + + + .. py:method:: train(disable_eval_tqdm: bool = False) -> None :abstractmethod: @@ -104,10 +114,12 @@ Package Contents - .. py:method:: load() -> None + .. py:method:: load(inference_only: bool) -> None .. py:method:: set_seed(seed) -> None + :staticmethod: + .. py:method:: load_seed_from_config() -> None @@ -140,7 +152,7 @@ Package Contents .. py:property:: _unwrapped_model - .. py:method:: load_checkpoint(checkpoint_path: str, checkpoint: dict | None = None) -> None + .. py:method:: load_checkpoint(checkpoint_path: str, checkpoint: dict | None = None, inference_only: bool | None = None) -> None .. py:method:: load_loss() -> None @@ -158,6 +170,9 @@ Package Contents .. py:method:: update_best(primary_metric, val_metrics, disable_eval_tqdm: bool = True) -> None + .. py:method:: _aggregate_metrics(metrics) + + .. py:method:: validate(split: str = 'val', disable_tqdm: bool = False) @@ -167,7 +182,7 @@ Package Contents .. py:method:: save_results(predictions: dict[str, numpy.typing.NDArray], results_file: str | None, keys: collections.abc.Sequence[str] | None = None) -> None -.. py:class:: OCPTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier, timestamp_id=None, run_dir=None, is_debug=False, print_every=100, seed=None, logger='wandb', local_rank=0, amp=False, cpu=False, slurm=None, noddp=False, name='ocp', gp_gpus=None) +.. py:class:: OCPTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False) Bases: :py:obj:`fairchem.core.trainers.base_trainer.BaseTrainer` @@ -212,17 +227,12 @@ Package Contents :param logger: Type of logger to be used. (default: :obj:`wandb`) :type logger: str, optional - :param local_rank: Local rank of the process, only applicable for distributed training. - (default: :obj:`0`) - :type local_rank: int, optional :param amp: Run using automatic mixed precision. (default: :obj:`False`) :type amp: bool, optional :param slurm: Slurm configuration. Currently just for keeping track. (default: :obj:`{}`) :type slurm: dict - :param noddp: Run model without DDP. - :type noddp: bool, optional .. py:method:: train(disable_eval_tqdm: bool = False) -> None @@ -240,7 +250,7 @@ Package Contents .. py:method:: _forward(batch) - .. py:method:: _compute_loss(out, batch) + .. py:method:: _compute_loss(out, batch) -> torch.Tensor .. py:method:: _compute_metrics(out, batch, evaluator, metrics=None) diff --git a/_sources/autoapi/core/trainers/ocp_trainer/index.rst b/_sources/autoapi/core/trainers/ocp_trainer/index.rst index 0dffbab7d0..fb56f92e63 100644 --- a/_sources/autoapi/core/trainers/ocp_trainer/index.rst +++ b/_sources/autoapi/core/trainers/ocp_trainer/index.rst @@ -23,7 +23,7 @@ Classes Module Contents --------------- -.. py:class:: OCPTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier, timestamp_id=None, run_dir=None, is_debug=False, print_every=100, seed=None, logger='wandb', local_rank=0, amp=False, cpu=False, slurm=None, noddp=False, name='ocp', gp_gpus=None) +.. py:class:: OCPTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False) Bases: :py:obj:`fairchem.core.trainers.base_trainer.BaseTrainer` @@ -68,17 +68,12 @@ Module Contents :param logger: Type of logger to be used. (default: :obj:`wandb`) :type logger: str, optional - :param local_rank: Local rank of the process, only applicable for distributed training. - (default: :obj:`0`) - :type local_rank: int, optional :param amp: Run using automatic mixed precision. (default: :obj:`False`) :type amp: bool, optional :param slurm: Slurm configuration. Currently just for keeping track. (default: :obj:`{}`) :type slurm: dict - :param noddp: Run model without DDP. - :type noddp: bool, optional .. py:method:: train(disable_eval_tqdm: bool = False) -> None @@ -96,7 +91,7 @@ Module Contents .. py:method:: _forward(batch) - .. py:method:: _compute_loss(out, batch) + .. py:method:: _compute_loss(out, batch) -> torch.Tensor .. py:method:: _compute_metrics(out, batch, evaluator, metrics=None) diff --git a/_sources/autoapi/data/oc/core/adsorbate/index.rst b/_sources/autoapi/data/oc/core/adsorbate/index.rst index bd89aaa290..59be913be8 100644 --- a/_sources/autoapi/data/oc/core/adsorbate/index.rst +++ b/_sources/autoapi/data/oc/core/adsorbate/index.rst @@ -55,15 +55,9 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: _get_adsorbate_from_random(adsorbate_db) diff --git a/_sources/autoapi/data/oc/core/bulk/index.rst b/_sources/autoapi/data/oc/core/bulk/index.rst index f6a3614806..0e92b73af4 100644 --- a/_sources/autoapi/data/oc/core/bulk/index.rst +++ b/_sources/autoapi/data/oc/core/bulk/index.rst @@ -61,19 +61,10 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: __eq__(other) -> bool - Return self==value. - - diff --git a/_sources/autoapi/data/oc/core/index.rst b/_sources/autoapi/data/oc/core/index.rst index b63dc393c3..fac4008c55 100644 --- a/_sources/autoapi/data/oc/core/index.rst +++ b/_sources/autoapi/data/oc/core/index.rst @@ -70,15 +70,9 @@ Package Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: _get_adsorbate_from_random(adsorbate_db) @@ -300,21 +294,12 @@ Package Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: __eq__(other) -> bool - Return self==value. - - .. py:class:: InterfaceConfig(slab: fairchem.data.oc.core.slab.Slab, adsorbates: list[fairchem.data.oc.core.adsorbate.Adsorbate], solvent: fairchem.data.oc.core.solvent.Solvent, ions: list[fairchem.data.oc.core.ion.Ion] | None = None, num_sites: int = 100, num_configurations: int = 1, interstitial_gap: float = 0.1, vacuum_size: int = 15, solvent_interstitial_gap: float = 2, solvent_depth: float = 8, pbc_shift: float = 0.0, packmol_tolerance: float = 2, mode: str = 'random_site_heuristic_placement') @@ -462,9 +447,6 @@ Package Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: _load_ion(ion: dict) -> None @@ -567,7 +549,7 @@ Package Contents -.. py:class:: Slab(bulk=None, slab_atoms: ase.Atoms = None, millers: tuple | None = None, shift: float | None = None, top: bool | None = None, oriented_bulk: pymatgen.core.structure.Structure = None, min_ab: float = 0.8) +.. py:class:: Slab(bulk=None, slab_atoms: ase.Atoms = None, millers: tuple | None = None, shift: float | None = None, top: bool | None = None, oriented_bulk: pymatgen.core.structure.Structure = None, min_ab: float = 8.0) Initializes a slab object, i.e. a particular slab tiled along xyz, in one of 2 ways: @@ -643,21 +625,12 @@ Package Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: __eq__(other) - Return self==value. - - .. py:class:: Solvent(solvent_atoms: ase.Atoms = None, solvent_id_from_db: int | None = None, solvent_db_path: str | None = SOLVENT_PKL_PATH, solvent_density: float | None = None) @@ -693,9 +666,6 @@ Package Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: _load_solvent(solvent: dict) -> None diff --git a/_sources/autoapi/data/oc/core/ion/index.rst b/_sources/autoapi/data/oc/core/ion/index.rst index 261584bfab..fa5e17dfc6 100644 --- a/_sources/autoapi/data/oc/core/ion/index.rst +++ b/_sources/autoapi/data/oc/core/ion/index.rst @@ -40,9 +40,6 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: _load_ion(ion: dict) -> None diff --git a/_sources/autoapi/data/oc/core/slab/index.rst b/_sources/autoapi/data/oc/core/slab/index.rst index ed8ccddf37..846fe56d20 100644 --- a/_sources/autoapi/data/oc/core/slab/index.rst +++ b/_sources/autoapi/data/oc/core/slab/index.rst @@ -34,7 +34,7 @@ Functions Module Contents --------------- -.. py:class:: Slab(bulk=None, slab_atoms: ase.Atoms = None, millers: tuple | None = None, shift: float | None = None, top: bool | None = None, oriented_bulk: pymatgen.core.structure.Structure = None, min_ab: float = 0.8) +.. py:class:: Slab(bulk=None, slab_atoms: ase.Atoms = None, millers: tuple | None = None, shift: float | None = None, top: bool | None = None, oriented_bulk: pymatgen.core.structure.Structure = None, min_ab: float = 8.0) Initializes a slab object, i.e. a particular slab tiled along xyz, in one of 2 ways: @@ -110,21 +110,12 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: __eq__(other) - Return self==value. - - .. py:function:: tile_and_tag_atoms(unit_slab_struct: pymatgen.core.structure.Structure, bulk_atoms: ase.Atoms, min_ab: float = 8) diff --git a/_sources/autoapi/data/oc/core/solvent/index.rst b/_sources/autoapi/data/oc/core/solvent/index.rst index 71dcb0c200..1bde27e8e0 100644 --- a/_sources/autoapi/data/oc/core/solvent/index.rst +++ b/_sources/autoapi/data/oc/core/solvent/index.rst @@ -49,9 +49,6 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: _load_solvent(solvent: dict) -> None diff --git a/_sources/autoapi/data/oc/utils/geometry/index.rst b/_sources/autoapi/data/oc/utils/geometry/index.rst index 98868334b4..ea8797bd8f 100644 --- a/_sources/autoapi/data/oc/utils/geometry/index.rst +++ b/_sources/autoapi/data/oc/utils/geometry/index.rst @@ -158,9 +158,6 @@ Module Contents .. py:method:: __repr__() - Return repr(self). - - .. py:method:: packmol_structure(filename: str, number: int, side: str) diff --git a/_sources/autoapi/data/oc/utils/vasp/index.rst b/_sources/autoapi/data/oc/utils/vasp/index.rst index 8af6e8ab97..8ed52a6e7d 100644 --- a/_sources/autoapi/data/oc/utils/vasp/index.rst +++ b/_sources/autoapi/data/oc/utils/vasp/index.rst @@ -67,7 +67,7 @@ Module Contents :returns: k_pts A 3-tuple of integers indicating the k-point mesh to use -.. py:function:: write_vasp_input_files(atoms, outdir='.', vasp_flags=None) +.. py:function:: write_vasp_input_files(atoms, outdir='.', vasp_flags=None, pp_setups='minimal', pp_env='VASP_PP_PATH') Effectively goes through the same motions as the `run_vasp` function, except it only writes the input files instead of running. @@ -75,5 +75,7 @@ Module Contents :param atoms `ase.Atoms` object that we want to relax.: :param outdir A string indicating where you want to save the input files.: Defaults to '.' :param vasp_flags A dictionary of settings we want to pass to the `Vasp`: calculator. Defaults to a standerd set of values if `None` + :param pp_setups Pseudopotential setups to use - https: //gitlab.com/ase/ase/-/blob/master/ase/calculators/vasp/setups.py + :param pp_env Environment variable to read for pseudopotentials.: diff --git a/_sources/autoapi/data/oc/utils/vasp_flags/index.rst b/_sources/autoapi/data/oc/utils/vasp_flags/index.rst index e8115e8a1e..d45f392197 100644 --- a/_sources/autoapi/data/oc/utils/vasp_flags/index.rst +++ b/_sources/autoapi/data/oc/utils/vasp_flags/index.rst @@ -15,7 +15,6 @@ Attributes data.oc.utils.vasp_flags.SOLVENT_BULK_VASP_FLAGS data.oc.utils.vasp_flags.RELAX_FLAGS data.oc.utils.vasp_flags.MD_FLAGS - data.oc.utils.vasp_flags.ML_FLAGS Module Contents @@ -33,5 +32,3 @@ Module Contents .. py:data:: MD_FLAGS -.. py:data:: ML_FLAGS - diff --git a/_sources/autoapi/ocpapi/client/index.rst b/_sources/autoapi/ocpapi/client/index.rst index 7c67a7c936..04c353b5de 100644 --- a/_sources/autoapi/ocpapi/client/index.rst +++ b/_sources/autoapi/ocpapi/client/index.rst @@ -777,9 +777,6 @@ Package Contents .. py:method:: __str__() -> str - Return str(self). - - .. py:function:: get_results_ui_url(api_host: str, system_id: str) -> str | None diff --git a/_sources/autoapi/ocpapi/client/models/index.rst b/_sources/autoapi/ocpapi/client/models/index.rst index c70ce2cd28..fa71f77bb6 100644 --- a/_sources/autoapi/ocpapi/client/models/index.rst +++ b/_sources/autoapi/ocpapi/client/models/index.rst @@ -381,9 +381,6 @@ Module Contents .. py:method:: __str__() -> str - Return str(self). - - .. py:class:: AdsorbateSlabRelaxationResult diff --git a/_sources/autoapi/ocpapi/index.rst b/_sources/autoapi/ocpapi/index.rst index 81c2c334b2..a58201701a 100644 --- a/_sources/autoapi/ocpapi/index.rst +++ b/_sources/autoapi/ocpapi/index.rst @@ -819,9 +819,6 @@ Package Contents .. py:method:: __str__() -> str - Return str(self). - - .. py:function:: get_results_ui_url(api_host: str, system_id: str) -> str | None diff --git a/_sources/core/fine-tuning/fine-tuning-oxides.md b/_sources/core/fine-tuning/fine-tuning-oxides.md index 39c39cad40..7118038370 100644 --- a/_sources/core/fine-tuning/fine-tuning-oxides.md +++ b/_sources/core/fine-tuning/fine-tuning-oxides.md @@ -44,6 +44,10 @@ import numpy as np import matplotlib.pyplot as plt from ase import Atoms +from fairchem.core.scripts import download_large_files + +download_large_files.download_file_group("docs") + with open('supporting-information.json', 'rb') as f: d = json.loads(f.read()) @@ -258,7 +262,7 @@ You can follow how the training is going by opening a terminal and running You can also visit it in a browser at [train.txt](./train.txt). You have to periodically refresh the view to see updates though. -This can take up to 30 minutes for 80 epochs, so we only do a few here to see what happens. +This can take up to 30 minutes for 80 epochs, so we only do a few here to see what happens. If you have a gpu or multiple gpus, you should use the flag --num-gpus= and remove the --cpu flag. ```{code-cell} ipython3 :tags: [hide-output] @@ -267,7 +271,7 @@ import time from fairchem.core.common.tutorial_utils import fairchem_main t0 = time.time() -! python {fairchem_main()} --mode train --config-yml {yml} --checkpoint {checkpoint_path} --run-dir fine-tuning --identifier ft-oxides --amp > train.txt 2>&1 +! python {fairchem_main()} --mode train --config-yml {yml} --checkpoint {checkpoint_path} --run-dir fine-tuning --identifier ft-oxides --cpu > train.txt 2>&1 print(f'Elapsed time = {time.time() - t0:1.1f} seconds') ``` diff --git a/_sources/core/inference.md b/_sources/core/inference.md index 63ce484653..a0701cb09f 100644 --- a/_sources/core/inference.md +++ b/_sources/core/inference.md @@ -98,7 +98,7 @@ yml = generate_yml_config(checkpoint_path, 'config.yml', yml ``` -It is a good idea to redirect the output to a file. If the output gets too large here, the notebook may fail to save. Normally I would use a redirect like `2&>1`, but this does not work with the main.py method. An alternative here is to open a terminal and run it there. +It is a good idea to redirect the output to a file. If the output gets too large here, the notebook may fail to save. Normally I would use a redirect like `2&>1`, but this does not work with the main.py method. An alternative here is to open a terminal and run it there. If you have a gpu or multiple gpus, you should use the flag --num-gpus= and remove the --cpu flag. ```{code-cell} ipython3 %%capture inference @@ -106,7 +106,7 @@ import time from fairchem.core.common.tutorial_utils import fairchem_main t0 = time.time() -! python {fairchem_main()} --mode predict --config-yml {yml} --checkpoint {checkpoint_path} --amp +! python {fairchem_main()} --mode predict --config-yml {yml} --checkpoint {checkpoint_path} --cpu print(f'Elapsed time = {time.time() - t0:1.1f} seconds') ``` diff --git a/_sources/tutorials/advanced/fine-tuning-in-python.md b/_sources/tutorials/advanced/fine-tuning-in-python.md index 0eeb8e5485..035385e6a4 100644 --- a/_sources/tutorials/advanced/fine-tuning-in-python.md +++ b/_sources/tutorials/advanced/fine-tuning-in-python.md @@ -119,7 +119,7 @@ parser = flags.get_parser() args, args_override = parser.parse_known_args(["--mode=train", "--config-yml=config.yml", f"--checkpoint={checkpoint_path}", - "--amp"]) + "--cpu"]) args, args_override ``` diff --git a/autoapi/adsorbml/2023_neurips_challenge/challenge_eval/index.html b/autoapi/adsorbml/2023_neurips_challenge/challenge_eval/index.html index 02a876122e..9c2e5103d1 100644 --- a/autoapi/adsorbml/2023_neurips_challenge/challenge_eval/index.html +++ b/autoapi/adsorbml/2023_neurips_challenge/challenge_eval/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/adsorbml/scripts/dense_eval/index.html b/autoapi/adsorbml/scripts/dense_eval/index.html index 464a2f805b..47b93552b4 100644 --- a/autoapi/adsorbml/scripts/dense_eval/index.html +++ b/autoapi/adsorbml/scripts/dense_eval/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/adsorbml/scripts/process_mlrs/index.html b/autoapi/adsorbml/scripts/process_mlrs/index.html index 41689c90a7..776d93dd78 100644 --- a/autoapi/adsorbml/scripts/process_mlrs/index.html +++ b/autoapi/adsorbml/scripts/process_mlrs/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/adsorbml/scripts/utils/index.html b/autoapi/adsorbml/scripts/utils/index.html index 98a5adaf74..a422fc7f01 100644 --- a/autoapi/adsorbml/scripts/utils/index.html +++ b/autoapi/adsorbml/scripts/utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/adsorbml/scripts/write_top_k_vasp/index.html b/autoapi/adsorbml/scripts/write_top_k_vasp/index.html index 9a416750da..fe3b4cf7f5 100644 --- a/autoapi/adsorbml/scripts/write_top_k_vasp/index.html +++ b/autoapi/adsorbml/scripts/write_top_k_vasp/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/core/autoframe/index.html b/autoapi/cattsunami/core/autoframe/index.html index ebfbefef93..f008f5808a 100644 --- a/autoapi/cattsunami/core/autoframe/index.html +++ b/autoapi/cattsunami/core/autoframe/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/core/index.html b/autoapi/cattsunami/core/index.html index d7ffce33da..568fcbece2 100644 --- a/autoapi/cattsunami/core/index.html +++ b/autoapi/cattsunami/core/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/core/ocpneb/index.html b/autoapi/cattsunami/core/ocpneb/index.html index c20fc37d44..1c75400ac7 100644 --- a/autoapi/cattsunami/core/ocpneb/index.html +++ b/autoapi/cattsunami/core/ocpneb/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/core/reaction/index.html b/autoapi/cattsunami/core/reaction/index.html index b71a6a4870..f201b81de2 100644 --- a/autoapi/cattsunami/core/reaction/index.html +++ b/autoapi/cattsunami/core/reaction/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/databases/index.html b/autoapi/cattsunami/databases/index.html index 4753c72371..8d17096bc7 100644 --- a/autoapi/cattsunami/databases/index.html +++ b/autoapi/cattsunami/databases/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/index.html b/autoapi/cattsunami/index.html index 9112443659..fbbfb9ba6f 100644 --- a/autoapi/cattsunami/index.html +++ b/autoapi/cattsunami/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/cattsunami/run_validation/run_validation/index.html b/autoapi/cattsunami/run_validation/run_validation/index.html index 0c1fa6381a..7c4f42fcb1 100644 --- a/autoapi/cattsunami/run_validation/run_validation/index.html +++ b/autoapi/cattsunami/run_validation/run_validation/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/_cli/index.html b/autoapi/core/_cli/index.html index f25266ee3a..1d8b2ec4f1 100644 --- a/autoapi/core/_cli/index.html +++ b/autoapi/core/_cli/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -630,7 +630,6 @@

    Contents

  • Module Contents @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/hpo_utils/index.html b/autoapi/core/common/hpo_utils/index.html index 4ddd4e3ac4..27cc843086 100644 --- a/autoapi/core/common/hpo_utils/index.html +++ b/autoapi/core/common/hpo_utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/index.html b/autoapi/core/common/index.html index 96b234dcd4..7e216b8490 100644 --- a/autoapi/core/common/index.html +++ b/autoapi/core/common/index.html @@ -337,7 +337,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -360,6 +359,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/logger/index.html b/autoapi/core/common/logger/index.html index e16fc7fc01..0efc8641a2 100644 --- a/autoapi/core/common/logger/index.html +++ b/autoapi/core/common/logger/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -640,6 +640,7 @@

    Contents

  • WandBLogger @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/relaxation/ase_utils/index.html b/autoapi/core/common/relaxation/ase_utils/index.html index a5fe780389..2c61b9e80b 100644 --- a/autoapi/core/common/relaxation/ase_utils/index.html +++ b/autoapi/core/common/relaxation/ase_utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -705,7 +705,8 @@

    Module Contents
    implemented_properties: ClassVar[list[str]] = ['energy', 'forces']#
    -
    +

    Properties calculator can handle (energy, forces, …)

    +
    diff --git a/autoapi/core/common/relaxation/index.html b/autoapi/core/common/relaxation/index.html index f75e02d68e..dd8b713738 100644 --- a/autoapi/core/common/relaxation/index.html +++ b/autoapi/core/common/relaxation/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/relaxation/ml_relaxation/index.html b/autoapi/core/common/relaxation/ml_relaxation/index.html index 761ad89e37..64fbd8c517 100644 --- a/autoapi/core/common/relaxation/ml_relaxation/index.html +++ b/autoapi/core/common/relaxation/ml_relaxation/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/relaxation/optimizers/index.html b/autoapi/core/common/relaxation/optimizers/index.html index 8b5528e544..93cf9d3ee5 100644 --- a/autoapi/core/common/relaxation/optimizers/index.html +++ b/autoapi/core/common/relaxation/optimizers/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/relaxation/optimizers/lbfgs_torch/index.html b/autoapi/core/common/relaxation/optimizers/lbfgs_torch/index.html index 83e3caf19d..6bb4d219e4 100644 --- a/autoapi/core/common/relaxation/optimizers/lbfgs_torch/index.html +++ b/autoapi/core/common/relaxation/optimizers/lbfgs_torch/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/slurm/index.html b/autoapi/core/common/slurm/index.html index 518ef62b7d..a039255454 100644 --- a/autoapi/core/common/slurm/index.html +++ b/autoapi/core/common/slurm/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/test_utils/index.html b/autoapi/core/common/test_utils/index.html index 08b5ba6279..c938682164 100644 --- a/autoapi/core/common/test_utils/index.html +++ b/autoapi/core/common/test_utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -643,6 +643,7 @@

    Contents

  • init_env_rank_and_launch_test()
  • init_pg_and_rank_and_launch_test()
  • spawn_multi_process()
    • +
  • init_local_distributed_process_group()
    • @@ -685,6 +686,9 @@

    Functions

    spawn_multi_process(→ list[Any])

    Spawn single node, multi-rank function.

    +

    init_local_distributed_process_group([backend])

    +

    + @@ -771,6 +775,11 @@

    Module Contents +
    +core.common.test_utils.init_local_distributed_process_group(backend='nccl')#
    +

    + @@ -856,6 +865,7 @@

    Module Contentsinit_env_rank_and_launch_test()
  • init_pg_and_rank_and_launch_test()
  • spawn_multi_process()
    • +
  • init_local_distributed_process_group()
    • diff --git a/autoapi/core/common/transforms/index.html b/autoapi/core/common/transforms/index.html index 3d316064fe..15a6929e68 100644 --- a/autoapi/core/common/transforms/index.html +++ b/autoapi/core/common/transforms/index.html @@ -337,7 +337,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -360,6 +359,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -701,8 +701,7 @@

    Module Contents
    __repr__() → str#
    -

    Return repr(self).

    -
    +
    diff --git a/autoapi/core/common/tutorial_utils/index.html b/autoapi/core/common/tutorial_utils/index.html index b7f04232b3..e83783bb97 100644 --- a/autoapi/core/common/tutorial_utils/index.html +++ b/autoapi/core/common/tutorial_utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/typing/index.html b/autoapi/core/common/typing/index.html index cb13364b92..7b2ee146d1 100644 --- a/autoapi/core/common/typing/index.html +++ b/autoapi/core/common/typing/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/common/utils/index.html b/autoapi/core/common/utils/index.html index ceb91d84df..720b797af8 100644 --- a/autoapi/core/common/utils/index.html +++ b/autoapi/core/common/utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -636,6 +636,7 @@

    Contents

  • pyg2_data_transform()
  • save_checkpoint()
    • +
  • multitask_required_keys
  • Complete @@ -653,6 +654,7 @@

    Contents

  • dict_set_recursively()
  • parse_value()
  • create_dict_from_args()
    • +
  • find_relative_file_in_paths()
  • load_config()
  • build_config()
  • create_grid()
    • @@ -683,6 +685,7 @@

    Contents

  • irreps_sum()
  • update_config()
  • get_loss_module()
    • +
  • load_model_and_weights_from_checkpoint()
    • @@ -708,6 +711,9 @@

    Attributes

    DEFAULT_ENV_VARS

    +

    multitask_required_keys

    +

    + @@ -778,76 +784,82 @@

    Functions

    create_dict_from_args(args[, sep])

    Create a (nested) dictionary from console arguments.

    -

    load_config(path[, previous_includes])

    +

    find_relative_file_in_paths(filename, include_paths)

    -

    build_config(args, args_override)

    +

    load_config(path[, files_previously_included, ...])

    +

    Load a given config with any defined imports

    + +

    build_config(args, args_override[, include_paths])

    -

    create_grid(base_config, sweep_file)

    +

    create_grid(base_config, sweep_file)

    -

    save_experiment_log(args, jobs, configs)

    +

    save_experiment_log(args, jobs, configs)

    -

    get_pbc_distances(pos, edge_index, cell, cell_offsets, ...)

    +

    get_pbc_distances(pos, edge_index, cell, cell_offsets, ...)

    -

    radius_graph_pbc(data, radius, max_num_neighbors_threshold)

    +

    radius_graph_pbc(data, radius, max_num_neighbors_threshold)

    -

    get_max_neighbors_mask(natoms, index, atom_distance, ...)

    +

    get_max_neighbors_mask(natoms, index, atom_distance, ...)

    Give a mask that filters out edges so that each atom has at most

    -

    get_pruned_edge_idx(→ torch.Tensor)

    +

    get_pruned_edge_idx(→ torch.Tensor)

    -

    merge_dicts(dict1, dict2)

    +

    merge_dicts(dict1, dict2)

    Recursively merge two dictionaries.

    -

    setup_logging(→ None)

    +

    setup_logging(→ None)

    -

    compute_neighbors(data, edge_index)

    +

    compute_neighbors(data, edge_index)

    -

    check_traj_files(→ bool)

    +

    check_traj_files(→ bool)

    -

    setup_env_vars(→ None)

    +

    setup_env_vars(→ None)

    -

    new_trainer_context(*, config[, distributed])

    +

    new_trainer_context(*, config)

    -

    _resolve_scale_factor_submodule(model, name)

    +

    _resolve_scale_factor_submodule(model, name)

    -

    _report_incompat_keys(→ tuple[list[str], list[str]])

    +

    _report_incompat_keys(→ tuple[list[str], list[str]])

    -

    match_state_dict(→ dict)

    +

    match_state_dict(→ dict)

    -

    load_state_dict(→ tuple[list[str], list[str]])

    +

    load_state_dict(→ tuple[list[str], list[str]])

    -

    scatter_det(*args, **kwargs)

    +

    scatter_det(*args, **kwargs)

    -

    get_commit_hash()

    +

    get_commit_hash()

    -

    cg_change_mat(→ torch.tensor)

    +

    cg_change_mat(→ torch.tensor)

    -

    irreps_sum(→ int)

    +

    irreps_sum(→ int)

    Returns the sum of the dimensions of the irreps up to the specified angular momentum.

    -

    update_config(base_config)

    +

    update_config(base_config)

    Configs created prior to FAIRChem/OCP 2.0 are organized a little different than they

    -

    get_loss_module(loss_name)

    +

    get_loss_module(loss_name)

    +

    + +

    load_model_and_weights_from_checkpoint(→ torch.nn.Module)

    @@ -884,6 +896,11 @@

    Module Contentscore.common.utils.save_checkpoint(state, checkpoint_dir: str = 'checkpoints/', checkpoint_file: str = 'checkpoint.pt') → str#
    +
    +
    +core.common.utils.multitask_required_keys#
    +
    +
    class core.common.utils.Complete#
    @@ -987,13 +1004,22 @@

    Module Contents -
    -core.common.utils.load_config(path: str, previous_includes: list | None = None)#
    +
    +core.common.utils.find_relative_file_in_paths(filename, include_paths)#

    +
    +
    +core.common.utils.load_config(path: str, files_previously_included: list | None = None, include_paths: list | None = None)#
    +

    Load a given config with any defined imports

    +

    When imports are present this is a recursive function called on imports. +To prevent any cyclic imports we keep track of already imported yml files +using files_previously_included

    +
    +
    -core.common.utils.build_config(args, args_override)#
    +core.common.utils.build_config(args, args_override, include_paths=None)#
    @@ -1114,7 +1140,7 @@

    Module Contents
    -core.common.utils.new_trainer_context(*, config: dict[str, Any], distributed: bool = False)#
    +core.common.utils.new_trainer_context(*, config: dict[str, Any])#

    @@ -1175,6 +1201,11 @@

    Module Contentscore.common.utils.get_loss_module(loss_name)#

    +
    +
    +core.common.utils.load_model_and_weights_from_checkpoint(checkpoint_path: str) → torch.nn.Module#
    +
    + @@ -1253,6 +1284,7 @@

    Module Contentspyg2_data_transform()
  • save_checkpoint()
    • +
  • multitask_required_keys
  • Complete @@ -1270,6 +1302,7 @@

    Module Contentsdict_set_recursively()

  • parse_value()
  • create_dict_from_args()
    • +
  • find_relative_file_in_paths()
  • load_config()
  • build_config()
  • create_grid()
    • @@ -1300,6 +1333,7 @@

    Module Contentsirreps_sum()
  • update_config()
  • get_loss_module()
    • +
  • load_model_and_weights_from_checkpoint()
    • diff --git a/autoapi/core/datasets/_utils/index.html b/autoapi/core/datasets/_utils/index.html index 8b5f353acc..76bc033706 100644 --- a/autoapi/core/datasets/_utils/index.html +++ b/autoapi/core/datasets/_utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -661,16 +661,22 @@

    Functions#

    -core.datasets._utils.rename_data_object_keys(data_object: torch_geometric.data.Data, key_mapping: dict[str, str]) → torch_geometric.data.Data#
    +core.datasets._utils.rename_data_object_keys(data_object: torch_geometric.data.Data, key_mapping: dict[str, str | list[str]]) → torch_geometric.data.Data#

    Rename data object keys

    Parameters:

    • data_object – data object

    • key_mapping – dictionary specifying keys to rename and new names {prev_key: new_key}

      • +

    • keys (new_key can be a list of new)

      • +

    • example (for)

    +

    :param : +:param prev_key: energy +:param new_key: [common_energy, oc20_energy] +:param This is currently required when we use a single target/label for multiple tasks:

    diff --git a/autoapi/core/datasets/ase_datasets/index.html b/autoapi/core/datasets/ase_datasets/index.html index c176dbdf50..780f352486 100644 --- a/autoapi/core/datasets/ase_datasets/index.html +++ b/autoapi/core/datasets/ase_datasets/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/base_dataset/index.html b/autoapi/core/datasets/base_dataset/index.html index f1b8279a46..b91de6c60d 100644 --- a/autoapi/core/datasets/base_dataset/index.html +++ b/autoapi/core/datasets/base_dataset/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/embeddings/atomic_radii/index.html b/autoapi/core/datasets/embeddings/atomic_radii/index.html index 3504e0598f..babef30d05 100644 --- a/autoapi/core/datasets/embeddings/atomic_radii/index.html +++ b/autoapi/core/datasets/embeddings/atomic_radii/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/embeddings/continuous_embeddings/index.html b/autoapi/core/datasets/embeddings/continuous_embeddings/index.html index 8acf015b01..fcf586a146 100644 --- a/autoapi/core/datasets/embeddings/continuous_embeddings/index.html +++ b/autoapi/core/datasets/embeddings/continuous_embeddings/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/embeddings/index.html b/autoapi/core/datasets/embeddings/index.html index 47d481042f..73968777ae 100644 --- a/autoapi/core/datasets/embeddings/index.html +++ b/autoapi/core/datasets/embeddings/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/embeddings/khot_embeddings/index.html b/autoapi/core/datasets/embeddings/khot_embeddings/index.html index c49468b88f..7bdef56e16 100644 --- a/autoapi/core/datasets/embeddings/khot_embeddings/index.html +++ b/autoapi/core/datasets/embeddings/khot_embeddings/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/embeddings/qmof_khot_embeddings/index.html b/autoapi/core/datasets/embeddings/qmof_khot_embeddings/index.html index e85a65affd..4eefa16c7f 100644 --- a/autoapi/core/datasets/embeddings/qmof_khot_embeddings/index.html +++ b/autoapi/core/datasets/embeddings/qmof_khot_embeddings/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/index.html b/autoapi/core/datasets/index.html index 1c6942acf0..1326a5703c 100644 --- a/autoapi/core/datasets/index.html +++ b/autoapi/core/datasets/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -752,7 +752,7 @@

    Functions

    create_dataset(→ Subset)

    Create a dataset from a config dictionary

    -

    data_list_collater(→ torch_geometric.data.data.BaseData)

    +

    data_list_collater(...)

    @@ -1186,7 +1186,7 @@

    Package Contents
    -core.datasets.data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False) → torch_geometric.data.data.BaseData#
    +core.datasets.data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False, to_dict: bool = False) → torch_geometric.data.data.BaseData | dict[str, torch.Tensor]#
    diff --git a/autoapi/core/datasets/lmdb_database/index.html b/autoapi/core/datasets/lmdb_database/index.html index 42064b9495..00af806e9c 100644 --- a/autoapi/core/datasets/lmdb_database/index.html +++ b/autoapi/core/datasets/lmdb_database/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/lmdb_dataset/index.html b/autoapi/core/datasets/lmdb_dataset/index.html index 774d2aa0b7..75824f76a3 100644 --- a/autoapi/core/datasets/lmdb_dataset/index.html +++ b/autoapi/core/datasets/lmdb_dataset/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -686,7 +686,7 @@

    Classes#<

    Functions#

    - + @@ -759,7 +759,7 @@

    Module Contents
    -core.datasets.lmdb_dataset.data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False) → torch_geometric.data.data.BaseData#
    +core.datasets.lmdb_dataset.data_list_collater(data_list: list[torch_geometric.data.data.BaseData], otf_graph: bool = False, to_dict: bool = False) → torch_geometric.data.data.BaseData | dict[str, torch.Tensor]#
    diff --git a/autoapi/core/datasets/oc22_lmdb_dataset/index.html b/autoapi/core/datasets/oc22_lmdb_dataset/index.html index c45f9b274c..311e386d59 100644 --- a/autoapi/core/datasets/oc22_lmdb_dataset/index.html +++ b/autoapi/core/datasets/oc22_lmdb_dataset/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/datasets/target_metadata_guesser/index.html b/autoapi/core/datasets/target_metadata_guesser/index.html index 9745473960..a6d2fc60e6 100644 --- a/autoapi/core/datasets/target_metadata_guesser/index.html +++ b/autoapi/core/datasets/target_metadata_guesser/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/index.html b/autoapi/core/index.html index 0f3d247d50..868e74135b 100644 --- a/autoapi/core/index.html +++ b/autoapi/core/index.html @@ -337,7 +337,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -360,6 +359,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/base/index.html b/autoapi/core/models/base/index.html index 3da66c8b12..91a92d67df 100644 --- a/autoapi/core/models/base/index.html +++ b/autoapi/core/models/base/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -646,6 +646,7 @@

    Contents

  • HeadInterface
    • @@ -653,21 +654,12 @@

    Contents

  • BackboneInterface.forward()
    • -
  • HydraInterface -
  • HydraModel
    • @@ -704,10 +696,7 @@

    Classes#<

    - - - - + @@ -792,7 +781,12 @@

    Module Contents
    class core.models.base.HeadInterface#
    -
    +
    +
    +property use_amp#
    +
    + +
    abstract forward(data: torch_geometric.data.Batch, emb: dict[str, torch.Tensor]) → dict[str, torch.Tensor]#

    Head forward.

    @@ -836,28 +830,10 @@

    Module Contents -
    -class core.models.base.HydraInterface#
    -

    Bases: abc.ABC

    -

    Helper class that provides a standard way to create an ABC using -inheritance.

    -
    -
    -abstract get_backbone() → BackboneInterface#
    -
    - -
    -
    -abstract get_heads() → dict[str, HeadInterface]#
    -
    - -

    -
    -class core.models.base.HydraModel(backbone: dict, heads: dict, otf_graph: bool = True)#
    -

    Bases: torch.nn.Module, GraphModelMixin, HydraInterface

    +class core.models.base.HydraModel(backbone: dict | None = None, heads: dict | None = None, finetune_config: dict | None = None, otf_graph: bool = True, pass_through_head_outputs: bool = False)# +

    Bases: torch.nn.Module, GraphModelMixin

    Base class for all neural network modules.

    Your models should also subclass this class.

    Modules can also contain other Modules, allowing to nest them in @@ -890,33 +866,23 @@

    Module Contents -
    -otf_graph#
    -

    - -
    -
    -backbone#
    +
    +device = None#
    -
    -heads#
    -
    - -
    -
    -backbone_model_name#
    +
    +otf_graph#
    -
    -output_heads: dict[str, HeadInterface]#
    +
    +pass_through_head_outputs#
    -
    -head_names_sorted#
    +
    +starting_model = None#
    @@ -924,16 +890,6 @@

    Module Contentsforward(data: torch_geometric.data.Batch)#

    -
    -
    -get_backbone() → BackboneInterface#
    -
    - -
    -
    -get_heads() → dict[str, HeadInterface]#
    -
    -
    @@ -1024,6 +980,7 @@

    Module ContentsHeadInterface @@ -1031,21 +988,12 @@

    Module ContentsBackboneInterface.forward() -
  • HydraInterface -
  • HydraModel
    • diff --git a/autoapi/core/models/dimenet_plus_plus/index.html b/autoapi/core/models/dimenet_plus_plus/index.html index b441c78a6e..df2462e052 100644 --- a/autoapi/core/models/dimenet_plus_plus/index.html +++ b/autoapi/core/models/dimenet_plus_plus/index.html @@ -61,7 +61,7 @@ - + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -1220,7 +1220,19 @@

    Module Contents
    forward(data: torch_geometric.data.batch.Batch) → dict[str, torch.Tensor]#
    -
    +

    Backbone forward.

    +
    +
    Parameters:
    +

    data (DataBatch) – Atomic systems as input

    +
    +
    Returns:
    +

    embedding – Return backbone embeddings for the given input

    +
    +
    Return type:
    +

    dict[str->torch.Tensor]

    +
    +
    +

    @@ -1267,11 +1279,11 @@

    Module Contents

    next

    -

    core.models.finetune_hydra

    +

    core.models.model_registry

     diff --git a/autoapi/core/models/equiformer_v2/activation/index.html b/autoapi/core/models/equiformer_v2/activation/index.html index 32a67b37db..1b78262339 100644 --- a/autoapi/core/models/equiformer_v2/activation/index.html +++ b/autoapi/core/models/equiformer_v2/activation/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/drop/index.html b/autoapi/core/models/equiformer_v2/drop/index.html index e86d6c394e..7143f162a6 100644 --- a/autoapi/core/models/equiformer_v2/drop/index.html +++ b/autoapi/core/models/equiformer_v2/drop/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/edge_rot_mat/index.html b/autoapi/core/models/equiformer_v2/edge_rot_mat/index.html index 16b704b25b..ab727bd157 100644 --- a/autoapi/core/models/equiformer_v2/edge_rot_mat/index.html +++ b/autoapi/core/models/equiformer_v2/edge_rot_mat/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/equiformer_v2/index.html b/autoapi/core/models/equiformer_v2/equiformer_v2/index.html index 4c1cd7b31c..afa927ea08 100644 --- a/autoapi/core/models/equiformer_v2/equiformer_v2/index.html +++ b/autoapi/core/models/equiformer_v2/equiformer_v2/index.html @@ -61,7 +61,7 @@ - + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -627,88 +627,84 @@

    Contents

    data_list_collater(→ torch_geometric.data.data.BaseData)

    data_list_collater(...)

    BackboneInterface

    HydraInterface

    Helper class that provides a standard way to create an ABC using

    HydraModel

    HydraModel

    Base class for all neural network modules.
    - - - - + - + - +

    EquiformerV2

    Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation

    EquiformerV2Backbone

    EquiformerV2Backbone

    Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation

    EquiformerV2EnergyHead

    EquiformerV2EnergyHead

    Base class for all neural network modules.

    EquiformerV2ForceHead

    EquiformerV2ForceHead

    Base class for all neural network modules.
    +
    +

    Functions#

    +
    + + + + + + + + +

    eqv2_init_weights(m, weight_init)

    eqv2_uniform_init_linear_weights(m)

    +
    +

    Module Contents#

    @@ -774,9 +781,19 @@

    Module Contentscore.models.equiformer_v2.equiformer_v2._AVG_DEGREE = 23.395238876342773#

    +
    +
    +core.models.equiformer_v2.equiformer_v2.eqv2_init_weights(m, weight_init)#
    +
    + +
    +
    +core.models.equiformer_v2.equiformer_v2.eqv2_uniform_init_linear_weights(m)#
    +
    +
    -
    -class core.models.equiformer_v2.equiformer_v2.EquiformerV2(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = True, max_neighbors: int = 500, max_radius: float = 5.0, max_num_elements: int = 90, num_layers: int = 12, sphere_channels: int = 128, attn_hidden_channels: int = 128, num_heads: int = 8, attn_alpha_channels: int = 32, attn_value_channels: int = 16, ffn_hidden_channels: int = 512, norm_type: str = 'rms_norm_sh', lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, grid_resolution: int | None = None, num_sphere_samples: int = 128, edge_channels: int = 128, use_atom_edge_embedding: bool = True, share_atom_edge_embedding: bool = False, use_m_share_rad: bool = False, distance_function: str = 'gaussian', num_distance_basis: int = 512, attn_activation: str = 'scaled_silu', use_s2_act_attn: bool = False, use_attn_renorm: bool = True, ffn_activation: str = 'scaled_silu', use_gate_act: bool = False, use_grid_mlp: bool = False, use_sep_s2_act: bool = True, alpha_drop: float = 0.1, drop_path_rate: float = 0.05, proj_drop: float = 0.0, weight_init: str = 'normal', enforce_max_neighbors_strictly: bool = True, avg_num_nodes: float | None = None, avg_degree: float | None = None, use_energy_lin_ref: bool | None = False, load_energy_lin_ref: bool | None = False)#
    +
    +class core.models.equiformer_v2.equiformer_v2.EquiformerV2Backbone(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = True, max_neighbors: int = 500, max_radius: float = 5.0, max_num_elements: int = 90, num_layers: int = 12, sphere_channels: int = 128, attn_hidden_channels: int = 128, num_heads: int = 8, attn_alpha_channels: int = 32, attn_value_channels: int = 16, ffn_hidden_channels: int = 512, norm_type: str = 'rms_norm_sh', lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, grid_resolution: int | None = None, num_sphere_samples: int = 128, edge_channels: int = 128, use_atom_edge_embedding: bool = True, share_atom_edge_embedding: bool = False, use_m_share_rad: bool = False, distance_function: str = 'gaussian', num_distance_basis: int = 512, attn_activation: str = 'scaled_silu', use_s2_act_attn: bool = False, use_attn_renorm: bool = True, ffn_activation: str = 'scaled_silu', use_gate_act: bool = False, use_grid_mlp: bool = False, use_sep_s2_act: bool = True, alpha_drop: float = 0.1, drop_path_rate: float = 0.05, proj_drop: float = 0.0, weight_init: str = 'normal', enforce_max_neighbors_strictly: bool = True, avg_num_nodes: float | None = None, avg_degree: float | None = None, use_energy_lin_ref: bool | None = False, load_energy_lin_ref: bool | None = False, activation_checkpoint: bool | None = False)#

    Bases: torch.nn.Module, fairchem.core.models.base.GraphModelMixin

    Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation

    @@ -830,413 +847,314 @@

    Module Contents -
    -use_pbc#
    +
    +activation_checkpoint#

    -
    -use_pbc_single#
    +
    +use_pbc#
    -
    -regress_forces#
    +
    +use_pbc_single#
    -
    -otf_graph#
    +
    +regress_forces#
    -
    -max_neighbors#
    +
    +otf_graph#
    -
    -max_radius#
    +
    +max_neighbors#
    -
    -cutoff#
    +
    +max_radius#
    -
    -max_num_elements#
    +
    +cutoff#
    -
    -num_layers#
    +
    +max_num_elements#
    -
    -sphere_channels#
    +
    +num_layers#
    -
    -attn_hidden_channels#
    +
    +sphere_channels#
    -
    -num_heads#
    +
    +attn_hidden_channels#
    -
    -attn_alpha_channels#
    +
    +num_heads#
    -
    -attn_value_channels#
    +
    +attn_alpha_channels#
    -
    -ffn_hidden_channels#
    +
    +attn_value_channels#
    -
    -norm_type#
    +
    +ffn_hidden_channels#
    -
    -lmax_list#
    +
    +norm_type#
    -
    -mmax_list#
    +
    +lmax_list#
    -
    -grid_resolution#
    +
    +mmax_list#
    -
    -num_sphere_samples#
    +
    +grid_resolution#
    -
    -edge_channels#
    +
    +num_sphere_samples#
    -
    -use_atom_edge_embedding#
    +
    +edge_channels#
    -
    -share_atom_edge_embedding#
    +
    +use_atom_edge_embedding#
    -
    -use_m_share_rad#
    +
    +share_atom_edge_embedding#
    -
    -distance_function#
    +
    +use_m_share_rad#
    -
    -num_distance_basis#
    +
    +distance_function#
    -
    -attn_activation#
    +
    +num_distance_basis#
    -
    -use_s2_act_attn#
    +
    +attn_activation#
    -
    -use_attn_renorm#
    +
    +use_s2_act_attn#
    -
    -ffn_activation#
    +
    +use_attn_renorm#
    -
    -use_gate_act#
    +
    +ffn_activation#
    -
    -use_grid_mlp#
    +
    +use_gate_act#
    -
    -use_sep_s2_act#
    +
    +use_grid_mlp#
    -
    -alpha_drop#
    +
    +use_sep_s2_act#
    -
    -drop_path_rate#
    +
    +alpha_drop#
    -
    -proj_drop#
    +
    +drop_path_rate#
    -
    -avg_num_nodes#
    +
    +proj_drop#
    -
    -avg_degree#
    +
    +avg_num_nodes#
    -
    -use_energy_lin_ref#
    +
    +avg_degree#
    -
    -load_energy_lin_ref#
    +
    +use_energy_lin_ref#
    -
    -weight_init#
    +
    +load_energy_lin_ref#
    -
    -enforce_max_neighbors_strictly#
    +
    +weight_init#
    -
    -device = 'cpu'#
    +
    +enforce_max_neighbors_strictly#
    -
    -grad_forces = False#
    +
    +device = 'cpu'#
    -
    -num_resolutions: int#
    +
    +grad_forces = False#
    -
    -sphere_channels_all: int#
    +
    +num_resolutions: int#
    -
    -sphere_embedding#
    +
    +sphere_channels_all: int#
    -
    -edge_channels_list#
    +
    +sphere_embedding#
    -
    -SO3_rotation#
    +
    +edge_channels_list#
    -
    -mappingReduced#
    +
    +SO3_rotation#
    -
    -SO3_grid#
    +
    +mappingReduced#
    -
    -edge_degree_embedding#
    +
    +SO3_grid#
    -
    -blocks#
    +
    +edge_degree_embedding#
    -
    -norm#
    +
    +blocks#
    -
    -energy_block#
    +
    +norm#
    -
    -_init_gp_partitions(atomic_numbers_full, data_batch_full, edge_index, edge_distance, edge_distance_vec)#
    +
    +forward(data: torch_geometric.data.batch.Batch) → dict[str, torch.Tensor]#
    +
    + +
    +
    +_init_gp_partitions(atomic_numbers_full, data_batch_full, edge_index, edge_distance, edge_distance_vec)#

    Graph Parallel This creates the required partial tensors for each rank given the full tensors. The tensors are split on the dimension along the node index using node_partition.

    -
    -forward(data)#
    -
    - -
    -
    -_init_edge_rot_mat(data, edge_index, edge_distance_vec)#
    +
    +_init_edge_rot_mat(data, edge_index, edge_distance_vec)#
    -
    -property num_params#
    -
    - -
    -
    -_init_weights(m)#
    +
    +property num_params#
    -
    -_uniform_init_rad_func_linear_weights(m)#
    -
    - -
    -
    -_uniform_init_linear_weights(m)#
    -
    - -
    -
    -no_weight_decay() → set#
    +
    +no_weight_decay() → set#

    Returns a list of parameters with no weight decay.

    -
    -
    -class core.models.equiformer_v2.equiformer_v2.EquiformerV2Backbone(*args, **kwargs)#
    -

    Bases: EquiformerV2, fairchem.core.models.base.BackboneInterface

    -

    Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation

    -
    -
    Parameters:
    -
      -

    • use_pbc (bool) – Use periodic boundary conditions

      • -

    • use_pbc_single (bool) – Process batch PBC graphs one at a time

      • -

    • regress_forces (bool) – Compute forces

      • -

    • otf_graph (bool) – Compute graph On The Fly (OTF)

      • -

    • max_neighbors (int) – Maximum number of neighbors per atom

      • -

    • max_radius (float) – Maximum distance between nieghboring atoms in Angstroms

      • -

    • max_num_elements (int) – Maximum atomic number

      • -

    • num_layers (int) – Number of layers in the GNN

      • -

    • sphere_channels (int) – Number of spherical channels (one set per resolution)

      • -

    • attn_hidden_channels (int) – Number of hidden channels used during SO(2) graph attention

      • -

    • num_heads (int) – Number of attention heads

      • -

    • attn_alpha_head (int) – Number of channels for alpha vector in each attention head

      • -

    • attn_value_head (int) – Number of channels for value vector in each attention head

      • -

    • ffn_hidden_channels (int) – Number of hidden channels used during feedforward network

      • -

    • norm_type (str) – Type of normalization layer ([‘layer_norm’, ‘layer_norm_sh’, ‘rms_norm_sh’])

      • -

    • lmax_list (int) – List of maximum degree of the spherical harmonics (1 to 10)

      • -

    • mmax_list (int) – List of maximum order of the spherical harmonics (0 to lmax)

      • -

    • grid_resolution (int) – Resolution of SO3_Grid

      • -

    • num_sphere_samples (int) – Number of samples used to approximate the integration of the sphere in the output blocks

      • -

    • edge_channels (int) – Number of channels for the edge invariant features

      • -

    • use_atom_edge_embedding (bool) – Whether to use atomic embedding along with relative distance for edge scalar features

      • -

    • share_atom_edge_embedding (bool) – Whether to share atom_edge_embedding across all blocks

      • -

    • use_m_share_rad (bool) – Whether all m components within a type-L vector of one channel share radial function weights

      • -

    • distance_function ("gaussian", "sigmoid", "linearsigmoid", "silu") – Basis function used for distances

      • -

    • attn_activation (str) – Type of activation function for SO(2) graph attention

      • -

    • use_s2_act_attn (bool) – Whether to use attention after S2 activation. Otherwise, use the same attention as Equiformer

      • -

    • use_attn_renorm (bool) – Whether to re-normalize attention weights

      • -

    • ffn_activation (str) – Type of activation function for feedforward network

      • -

    • use_gate_act (bool) – If True, use gate activation. Otherwise, use S2 activation

      • -

    • use_grid_mlp (bool) – If True, use projecting to grids and performing MLPs for FFNs.

      • -

    • use_sep_s2_act (bool) – If True, use separable S2 activation when use_gate_act is False.

      • -

    • alpha_drop (float) – Dropout rate for attention weights

      • -

    • drop_path_rate (float) – Drop path rate

      • -

    • proj_drop (float) – Dropout rate for outputs of attention and FFN in Transformer blocks

      • -

    • weight_init (str) – [‘normal’, ‘uniform’] initialization of weights of linear layers except those in radial functions

      • -

    • enforce_max_neighbors_strictly (bool) – When edges are subselected based on the max_neighbors arg, arbitrarily select amongst equidistant / degenerate edges to have exactly the correct number.

      • -

    • avg_num_nodes (float) – Average number of nodes per graph

      • -

    • avg_degree (float) – Average degree of nodes in the graph

      • -

    • use_energy_lin_ref (bool) – Whether to add the per-atom energy references during prediction. -During training and validation, this should be kept False since we use the lin_ref parameter in the OC22 dataloader to subtract the per-atom linear references from the energy targets. -During prediction (where we don’t have energy targets), this can be set to True to add the per-atom linear references to the predicted energies.

      • -

    • load_energy_lin_ref (bool) – Whether to add nn.Parameters for the per-element energy references. -This additional flag is there to ensure compatibility when strict-loading checkpoints, since the use_energy_lin_ref flag can be either True or False even if the model is trained with linear references. -You can’t have use_energy_lin_ref = True and load_energy_lin_ref = False, since the model will not have the parameters for the linear references. All other combinations are fine.

      • -
    -
    -
    -
    -
    -energy_block = None#
    -
    - -
    -
    -force_block = None#
    -
    - -
    -
    -forward(data: torch_geometric.data.batch.Batch) → dict[str, torch.Tensor]#
    -

    Backbone forward.

    -
    -
    Parameters:
    -

    data (DataBatch) – Atomic systems as input

    -
    -
    Returns:
    -

    embedding – Return backbone embeddings for the given input

    -
    -
    Return type:
    -

    dict[str->torch.Tensor]

    -
    -
    -
    - -
    -
    -class core.models.equiformer_v2.equiformer_v2.EquiformerV2EnergyHead(backbone)#
    +class core.models.equiformer_v2.equiformer_v2.EquiformerV2EnergyHead(backbone, reduce: str = 'sum')#

    Bases: torch.nn.Module, fairchem.core.models.base.HeadInterface

    Base class for all neural network modules.

    Your models should also subclass this class.

    @@ -1269,6 +1187,11 @@

    Module Contents +
    +reduce#
    +

    +
    avg_num_nodes#
    @@ -1336,6 +1259,11 @@

    Module Contents +
    +activation_checkpoint#
    +

    +
    force_block#
    @@ -1406,11 +1334,11 @@

    Module Contents

    next

    -

    core.models.equiformer_v2.gaussian_rbf

    +

    core.models.equiformer_v2.equiformer_v2_deprecated

     @@ -1432,88 +1360,84 @@

    Module Contents
  • Attributes
  • Classes
    • +
  • Functions
  • Module Contents @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -823,12 +823,12 @@

    Module Contents

    previous

    -

    core.models.equiformer_v2.equiformer_v2

    +

    core.models.equiformer_v2.eqv2_to_eqv2_hydra

     DOCUMENTATION_OPTIONS.pagename = 'autoapi/core/models/equiformer_v2/index'; - + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -714,6 +714,7 @@

    Contents

    Subpackages#

    @@ -726,6 +727,8 @@

    Submodulescore.models.equiformer_v2.drop
  • core.models.equiformer_v2.edge_rot_mat
  • core.models.equiformer_v2.equiformer_v2
    • +
  • core.models.equiformer_v2.equiformer_v2_deprecated
    • +
  • core.models.equiformer_v2.eqv2_to_eqv2_hydra
  • core.models.equiformer_v2.gaussian_rbf
  • core.models.equiformer_v2.input_block
  • core.models.equiformer_v2.layer_norm
    • @@ -743,7 +746,7 @@

    Classes#<
    - +

    EquiformerV2

    Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation

    THIS CLASS HAS BEEN DEPRECATED! Please use "EquiformerV2BackboneAndHeads"
    @@ -755,6 +758,7 @@

    Package Contents class core.models.equiformer_v2.EquiformerV2(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = True, max_neighbors: int = 500, max_radius: float = 5.0, max_num_elements: int = 90, num_layers: int = 12, sphere_channels: int = 128, attn_hidden_channels: int = 128, num_heads: int = 8, attn_alpha_channels: int = 32, attn_value_channels: int = 16, ffn_hidden_channels: int = 512, norm_type: str = 'rms_norm_sh', lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, grid_resolution: int | None = None, num_sphere_samples: int = 128, edge_channels: int = 128, use_atom_edge_embedding: bool = True, share_atom_edge_embedding: bool = False, use_m_share_rad: bool = False, distance_function: str = 'gaussian', num_distance_basis: int = 512, attn_activation: str = 'scaled_silu', use_s2_act_attn: bool = False, use_attn_renorm: bool = True, ffn_activation: str = 'scaled_silu', use_gate_act: bool = False, use_grid_mlp: bool = False, use_sep_s2_act: bool = True, alpha_drop: float = 0.1, drop_path_rate: float = 0.05, proj_drop: float = 0.0, weight_init: str = 'normal', enforce_max_neighbors_strictly: bool = True, avg_num_nodes: float | None = None, avg_degree: float | None = None, use_energy_lin_ref: bool | None = False, load_energy_lin_ref: bool | None = False)#

    Bases: torch.nn.Module, fairchem.core.models.base.GraphModelMixin

    +

    THIS CLASS HAS BEEN DEPRECATED! Please use “EquiformerV2BackboneAndHeads”

    Equiformer with graph attention built upon SO(2) convolution and feedforward network built upon S2 activation

    Parameters:
    @@ -1170,11 +1174,11 @@

    Package Contents

    next

    -

    core.models.equiformer_v2.trainers

    +

    core.models.equiformer_v2.prediction_heads

     diff --git a/autoapi/core/models/equiformer_v2/input_block/index.html b/autoapi/core/models/equiformer_v2/input_block/index.html index 73e6920dea..e3ec893211 100644 --- a/autoapi/core/models/equiformer_v2/input_block/index.html +++ b/autoapi/core/models/equiformer_v2/input_block/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
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    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/layer_norm/index.html b/autoapi/core/models/equiformer_v2/layer_norm/index.html index a74d250cf0..4322a07a24 100644 --- a/autoapi/core/models/equiformer_v2/layer_norm/index.html +++ b/autoapi/core/models/equiformer_v2/layer_norm/index.html @@ -335,7 +335,6 @@
  • core.models.utils
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    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -816,8 +816,7 @@

    Module Contents
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    Module Contents
    __repr__() → str#
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    Return repr(self).

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    +
    diff --git a/autoapi/core/models/equiformer_v2/module_list/index.html b/autoapi/core/models/equiformer_v2/module_list/index.html index 6116fcce21..ed1493b423 100644 --- a/autoapi/core/models/equiformer_v2/module_list/index.html +++ b/autoapi/core/models/equiformer_v2/module_list/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/prediction_heads/index.html b/autoapi/core/models/equiformer_v2/prediction_heads/index.html new file mode 100644 index 0000000000..bda89be960 --- /dev/null +++ b/autoapi/core/models/equiformer_v2/prediction_heads/index.html @@ -0,0 +1,896 @@ + + + + + + + + + + + core.models.equiformer_v2.prediction_heads + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    core.models.equiformer_v2.prediction_heads

    + +
    + +
    +
    + + + + +
    + +
    +

    core.models.equiformer_v2.prediction_heads#

    +
    +

    Submodules#

    +
    + +
    +
    +
    +

    Classes#

    +
    + + + + + +

    Rank2SymmetricTensorHead

    A rank 2 symmetric tensor prediction head.

    +
    +
    +
    +

    Package Contents#

    +
    +
    +class core.models.equiformer_v2.prediction_heads.Rank2SymmetricTensorHead(backbone: fairchem.core.models.base.BackboneInterface, output_name: str, decompose: bool = False, edge_level_mlp: bool = False, num_mlp_layers: int = 2, use_source_target_embedding: bool = False, extensive: bool = False, avg_num_nodes: int = 1.0, default_norm_type: str = 'layer_norm_sh')#
    +

    Bases: torch.nn.Module, fairchem.core.models.base.HeadInterface

    +

    A rank 2 symmetric tensor prediction head.

    +
    +
    +ouput_name#
    +

    name of output prediction property (ie, stress)

    +
    + +
    +
    +sphharm_norm#
    +

    layer normalization for spherical harmonic edge weights

    +
    + +
    +
    +xedge_layer_norm#
    +

    embedding layer norm

    +
    + +
    +
    +block#
    +

    rank 2 equivariant symmetric tensor block

    +
    + +
    +
    +output_name#
    +
    + +
    +
    +decompose#
    +
    + +
    +
    +use_source_target_embedding#
    +
    + +
    +
    +avg_num_nodes#
    +
    + +
    +
    +sphharm_norm#
    +
    + +
    +
    +xedge_layer_norm#
    +
    + +
    +
    +forward(data: dict[str, torch.Tensor] | torch.Tensor, emb: dict[str, torch.Tensor]) → dict[str, torch.Tensor]#
    +
    +
    Parameters:
    +
      +

    • data – data batch

      • +

    • emb – dictionary with embedding object and graph data

      • +
    +
    +
    +

    Returns: dict of {output property name: predicted value}

    +
    + +
    + +
    +
    + + + + +
    + + + + + + + + +
    + + + +
    + + +
    +
    + Contents +
    +
    + +
    + + +
    +
    + +
    + +
    + +

    +By FAIR Chemistry & Collaborators +

    + +
    + +
    + + +

    + + © Copyright 2024. +
    + +

    + +
    + +
    + +
    + +
    + +
    + +
    +
    + + +
    +
    +
    + + + + + +
    +
    + + \ No newline at end of file diff --git a/autoapi/core/models/equiformer_v2/prediction_heads/rank2/index.html b/autoapi/core/models/equiformer_v2/prediction_heads/rank2/index.html new file mode 100644 index 0000000000..796b9ca850 --- /dev/null +++ b/autoapi/core/models/equiformer_v2/prediction_heads/rank2/index.html @@ -0,0 +1,1061 @@ + + + + + + + + + + + core.models.equiformer_v2.prediction_heads.rank2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    core.models.equiformer_v2.prediction_heads.rank2

    + +
    + +
    +
    + + + + +
    + +
    +

    core.models.equiformer_v2.prediction_heads.rank2#

    +

    Copyright (c) Meta, Inc. and its affiliates.

    +

    This source code is licensed under the MIT license found in the +LICENSE file in the root directory of this source tree.

    +
    +

    Classes#

    +
    + + + + + + + + + + + +

    Rank2Block

    Output block for predicting rank-2 tensors (stress, dielectric tensor).

    Rank2DecompositionEdgeBlock

    Output block for predicting rank-2 tensors (stress, dielectric tensor, etc).

    Rank2SymmetricTensorHead

    A rank 2 symmetric tensor prediction head.

    +
    +
    +
    +

    Module Contents#

    +
    +
    +class core.models.equiformer_v2.prediction_heads.rank2.Rank2Block(emb_size: int, num_layers: int = 2, edge_level: bool = False, extensive: bool = False)#
    +

    Bases: torch.nn.Module

    +

    Output block for predicting rank-2 tensors (stress, dielectric tensor). +Applies outer product between edges and computes node-wise or edge-wise MLP.

    +
    +
    Parameters:
    +
      +

    • emb_size (int) – Size of edge embedding used to compute outer product

      • +

    • num_layers (int) – Number of layers of the MLP

      • +

    • edge_level (bool) – If true apply MLP at edge level before pooling, otherwise use MLP at nodes after pooling

      • +

    • extensive (bool) – Whether to sum or average the outer products

      • +
    +
    +
    +
    +
    +edge_level#
    +
    + +
    +
    +emb_size#
    +
    + +
    +
    +extensive#
    +
    + +
    +
    +scalar_nonlinearity#
    +
    + +
    +
    +r2tensor_MLP#
    +
    + +
    +
    +forward(edge_distance_vec, x_edge, edge_index, data)#
    +
    +
    Parameters:
    +
      +

    • edge_distance_vec (torch.Tensor) – Tensor of shape (…, 3)

      • +

    • x_edge (torch.Tensor) – Tensor of shape (…, emb_size)

      • +

    • edge_index (torch.Tensor) – Tensor of shape (2, nEdges)

      • +

    • data – LMDBDataset sample

      • +
    +
    +
    +
    + +
    + +
    +
    +class core.models.equiformer_v2.prediction_heads.rank2.Rank2DecompositionEdgeBlock(emb_size: int, num_layers: int = 2, edge_level: bool = False, extensive: bool = False)#
    +

    Bases: torch.nn.Module

    +

    Output block for predicting rank-2 tensors (stress, dielectric tensor, etc). +Decomposes a rank-2 symmetric tensor into irrep degree 0 and 2.

    +
    +
    Parameters:
    +
      +

    • emb_size (int) – Size of edge embedding used to compute outer product

      • +

    • num_layers (int) – Number of layers of the MLP

      • +

    • edge_level (bool) – If true apply MLP at edge level before pooling, otherwise use MLP at nodes after pooling

      • +

    • extensive (bool) – Whether to sum or average the outer products

      • +
    +
    +
    +
    +
    +emb_size#
    +
    + +
    +
    +edge_level#
    +
    + +
    +
    +extensive#
    +
    + +
    +
    +scalar_nonlinearity#
    +
    + +
    +
    +scalar_MLP#
    +
    + +
    +
    +irrep2_MLP#
    +
    + +
    +
    +change_mat#
    +
    + +
    +
    +forward(edge_distance_vec, x_edge, edge_index, data)#
    +
    +
    Parameters:
    +
      +

    • edge_distance_vec (torch.Tensor) – Tensor of shape (…, 3)

      • +

    • x_edge (torch.Tensor) – Tensor of shape (…, emb_size)

      • +

    • edge_index (torch.Tensor) – Tensor of shape (2, nEdges)

      • +

    • data – LMDBDataset sample

      • +
    +
    +
    +
    + +
    + +
    +
    +class core.models.equiformer_v2.prediction_heads.rank2.Rank2SymmetricTensorHead(backbone: fairchem.core.models.base.BackboneInterface, output_name: str, decompose: bool = False, edge_level_mlp: bool = False, num_mlp_layers: int = 2, use_source_target_embedding: bool = False, extensive: bool = False, avg_num_nodes: int = 1.0, default_norm_type: str = 'layer_norm_sh')#
    +

    Bases: torch.nn.Module, fairchem.core.models.base.HeadInterface

    +

    A rank 2 symmetric tensor prediction head.

    +
    +
    +ouput_name#
    +

    name of output prediction property (ie, stress)

    +
    + +
    +
    +sphharm_norm#
    +

    layer normalization for spherical harmonic edge weights

    +
    + +
    +
    +xedge_layer_norm#
    +

    embedding layer norm

    +
    + +
    +
    +block#
    +

    rank 2 equivariant symmetric tensor block

    +
    + +
    +
    +output_name#
    +
    + +
    +
    +decompose#
    +
    + +
    +
    +use_source_target_embedding#
    +
    + +
    +
    +avg_num_nodes#
    +
    + +
    +
    +sphharm_norm#
    +
    + +
    +
    +xedge_layer_norm#
    +
    + +
    +
    +forward(data: dict[str, torch.Tensor] | torch.Tensor, emb: dict[str, torch.Tensor]) → dict[str, torch.Tensor]#
    +
    +
    Parameters:
    +
      +

    • data – data batch

      • +

    • emb – dictionary with embedding object and graph data

      • +
    +
    +
    +

    Returns: dict of {output property name: predicted value}

    +
    + +
    + +
    +
    + + + + +
    + + + + + + + + +
    + + + +
    + + +
    +
    + Contents +
    +
    + +
    + + +
    +
    + +
    + +
    + +

    +By FAIR Chemistry & Collaborators +

    + +
    + +
    + + +

    + + © Copyright 2024. +
    + +

    + +
    + +
    + +
    + +
    + +
    + +
    +
    + + +
    +
    +
    + + + + + +
    +
    + + \ No newline at end of file diff --git a/autoapi/core/models/equiformer_v2/radial_function/index.html b/autoapi/core/models/equiformer_v2/radial_function/index.html index 807f9f80d7..4583b51f72 100644 --- a/autoapi/core/models/equiformer_v2/radial_function/index.html +++ b/autoapi/core/models/equiformer_v2/radial_function/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -670,7 +670,31 @@

    Module Contents
    modules = []#
    -

    +

    Return an iterator over all modules in the network.

    +
    +
    Yields:
    +

    Module – a module in the network

    +
    +
    +
    +

    Note

    +

    Duplicate modules are returned only once. In the following +example, l will be returned only once.

    +
    +

    Example:

    +
    >>> l = nn.Linear(2, 2)
+>>> net = nn.Sequential(l, l)
+>>> for idx, m in enumerate(net.modules()):
+...     print(idx, '->', m)
+
+0 -> Sequential(
+  (0): Linear(in_features=2, out_features=2, bias=True)
+  (1): Linear(in_features=2, out_features=2, bias=True)
+)
+1 -> Linear(in_features=2, out_features=2, bias=True)
+
    +
    +
    diff --git a/autoapi/core/models/equiformer_v2/so2_ops/index.html b/autoapi/core/models/equiformer_v2/so2_ops/index.html index dbb9801c20..f018107cbc 100644 --- a/autoapi/core/models/equiformer_v2/so2_ops/index.html +++ b/autoapi/core/models/equiformer_v2/so2_ops/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/so3/index.html b/autoapi/core/models/equiformer_v2/so3/index.html index c0f5d9b2b6..92b27dd2be 100644 --- a/autoapi/core/models/equiformer_v2/so3/index.html +++ b/autoapi/core/models/equiformer_v2/so3/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -863,8 +863,7 @@

    Module Contents
    __repr__() → str#
    -

    Return repr(self).

    -

    +
    @@ -1155,8 +1154,7 @@

    Module Contents
    __repr__() → str#
    -

    Return repr(self).

    -
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    @@ -1238,8 +1236,7 @@

    Module Contents
    __repr__() → str#
    -

    Return repr(self).

    -
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    diff --git a/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.html b/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.html index ab6910eca3..e67d87ab95 100644 --- a/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.html +++ b/autoapi/core/models/equiformer_v2/trainers/energy_trainer/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -664,7 +664,7 @@

    Classes#<

    Module Contents#

    -class core.models.equiformer_v2.trainers.energy_trainer.EquiformerV2EnergyTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier, timestamp_id=None, run_dir=None, is_debug=False, print_every=100, seed=None, logger='wandb', local_rank=0, amp=False, cpu=False, slurm=None, noddp=False, name='ocp', gp_gpus=None)#
    +class core.models.equiformer_v2.trainers.energy_trainer.EquiformerV2EnergyTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False)#

    Bases: fairchem.core.trainers.OCPTrainer

    Trainer class for the Structure to Energy & Force (S2EF) and Initial State to Relaxed State (IS2RS) tasks.

    @@ -695,13 +695,10 @@

    Module ContentsNone)

  • logger (str, optional) – Type of logger to be used. (default: wandb)

    • -

  • local_rank (int, optional) – Local rank of the process, only applicable for distributed training. -(default: 0)

  • amp (bool, optional) – Run using automatic mixed precision. (default: False)

  • slurm (dict) – Slurm configuration. Currently just for keeping track. (default: {})

    • -

  • noddp (bool, optional) – Run model without DDP.

    • diff --git a/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.html b/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.html index b60ad72fad..ab4b315921 100644 --- a/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.html +++ b/autoapi/core/models/equiformer_v2/trainers/forces_trainer/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -664,7 +664,7 @@

    Classes#<

    Module Contents#

    -class core.models.equiformer_v2.trainers.forces_trainer.EquiformerV2ForcesTrainer(task, model, outputs, dataset, optimizer, loss_functions, evaluation_metrics, identifier, timestamp_id=None, run_dir=None, is_debug=False, print_every=100, seed=None, logger='wandb', local_rank=0, amp=False, cpu=False, slurm=None, noddp=False, name='ocp', gp_gpus=None)#
    +class core.models.equiformer_v2.trainers.forces_trainer.EquiformerV2ForcesTrainer(task: dict[str, str | Any], model: dict[str, Any], outputs: dict[str, str | int], dataset: dict[str, str | float], optimizer: dict[str, str | float], loss_functions: dict[str, str | float], evaluation_metrics: dict[str, str], identifier: str, local_rank: int, timestamp_id: str | None = None, run_dir: str | None = None, is_debug: bool = False, print_every: int = 100, seed: int | None = None, logger: str = 'wandb', amp: bool = False, cpu: bool = False, name: str = 'ocp', slurm=None, gp_gpus: int | None = None, inference_only: bool = False)#

    Bases: fairchem.core.trainers.OCPTrainer

    Trainer class for the Structure to Energy & Force (S2EF) and Initial State to Relaxed State (IS2RS) tasks.

    @@ -695,13 +695,10 @@

    Module ContentsNone)

  • logger (str, optional) – Type of logger to be used. (default: wandb)

    • -

  • local_rank (int, optional) – Local rank of the process, only applicable for distributed training. -(default: 0)

  • amp (bool, optional) – Run using automatic mixed precision. (default: False)

  • slurm (dict) – Slurm configuration. Currently just for keeping track. (default: {})

    • -

  • noddp (bool, optional) – Run model without DDP.

    • diff --git a/autoapi/core/models/equiformer_v2/trainers/index.html b/autoapi/core/models/equiformer_v2/trainers/index.html index eaf4cef4ef..3bc1c8931b 100644 --- a/autoapi/core/models/equiformer_v2/trainers/index.html +++ b/autoapi/core/models/equiformer_v2/trainers/index.html @@ -62,7 +62,7 @@ - + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -682,12 +682,12 @@

    Submodules

    previous

    -

    core.models.equiformer_v2

    +

    core.models.equiformer_v2.prediction_heads.rank2

     core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/transformer_block/index.html b/autoapi/core/models/equiformer_v2/transformer_block/index.html index 0c03314379..972226bd37 100644 --- a/autoapi/core/models/equiformer_v2/transformer_block/index.html +++ b/autoapi/core/models/equiformer_v2/transformer_block/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/equiformer_v2/wigner/index.html b/autoapi/core/models/equiformer_v2/wigner/index.html index f10818b2db..91af1dc13e 100644 --- a/autoapi/core/models/equiformer_v2/wigner/index.html +++ b/autoapi/core/models/equiformer_v2/wigner/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/escn/escn/index.html b/autoapi/core/models/escn/escn/index.html index 0e531258aa..ce61eba00d 100644 --- a/autoapi/core/models/escn/escn/index.html +++ b/autoapi/core/models/escn/escn/index.html @@ -61,7 +61,7 @@ - + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -670,6 +670,7 @@

    Contents

  • eSCNEnergyHead
    • @@ -838,7 +839,7 @@

    Classes#<

    Module Contents#

    -class core.models.escn.escn.eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False)#
    +class core.models.escn.escn.eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False, resolution: int | None = None)#

    Bases: torch.nn.Module, fairchem.core.models.base.GraphModelMixin

    Equivariant Spherical Channel Network Paper: Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

    @@ -1040,7 +1041,7 @@

    Module Contents
    -class core.models.escn.escn.eSCNBackbone(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False)#
    +class core.models.escn.escn.eSCNBackbone(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False, resolution: int | None = None)#

    Bases: eSCN, fairchem.core.models.base.BackboneInterface

    Equivariant Spherical Channel Network Paper: Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

    @@ -1089,7 +1090,7 @@

    Module Contents
    -class core.models.escn.escn.eSCNEnergyHead(backbone)#
    +class core.models.escn.escn.eSCNEnergyHead(backbone, reduce='sum')#

    Bases: torch.nn.Module, fairchem.core.models.base.HeadInterface

    Base class for all neural network modules.

    Your models should also subclass this class.

    @@ -1127,6 +1128,11 @@

    Module Contentsenergy_block = None#

    +
    +
    +reduce#
    +
    +
    forward(data: torch_geometric.data.batch.Batch, emb: dict[str, torch.Tensor]) → dict[str, torch.Tensor]#
    @@ -1768,11 +1774,11 @@

    Module Contents

    next

    -

    core.models.escn.so3

    +

    core.models.escn.escn_exportable

     @@ -1837,6 +1843,7 @@

    Module ContentseSCNEnergyHead diff --git a/autoapi/core/models/escn/escn_exportable/index.html b/autoapi/core/models/escn/escn_exportable/index.html new file mode 100644 index 0000000000..60f251ccbb --- /dev/null +++ b/autoapi/core/models/escn/escn_exportable/index.html @@ -0,0 +1,1723 @@ + + + + + + + + + + + core.models.escn.escn_exportable + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    core.models.escn.escn_exportable

    + +
    +
    + +
    +

    Contents

    +
    + +
    +
    +
    + + + + +
    + +
    +

    core.models.escn.escn_exportable#

    +

    Copyright (c) Meta, Inc. and its affiliates.

    +

    This source code is licensed under the MIT license found in the +LICENSE file in the root directory of this source tree.

    +
    +

    Classes#

    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + +

    eSCN

    Equivariant Spherical Channel Network

    LayerBlock

    Layer block: Perform one layer (message passing and aggregation) of the GNN

    MessageBlock

    Message block: Perform message passing

    SO2Block

    SO(2) Block: Perform SO(2) convolutions for all m (orders)

    SO2Conv

    SO(2) Conv: Perform an SO(2) convolution

    EdgeBlock

    Edge Block: Compute invariant edge representation from edge diatances and atomic numbers

    EnergyBlock

    Energy Block: Output block computing the energy

    ForceBlock

    Force Block: Output block computing the per atom forces

    +
    +
    +
    +

    Module Contents#

    +
    +
    +class core.models.escn.escn_exportable.eSCN(regress_forces: bool = True, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax: int = 4, mmax: int = 2, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, resolution: int | None = None)#
    +

    Bases: torch.nn.Module

    +

    Equivariant Spherical Channel Network +Paper: Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

    +
    +
    Parameters:
    +
      +

    • regress_forces (bool) – Compute forces

      • +

    • cutoff (float) – Maximum distance between nieghboring atoms in Angstroms

      • +

    • max_num_elements (int) – Maximum atomic number

      • +

    • num_layers (int) – Number of layers in the GNN

      • +

    • lmax (int) – maximum degree of the spherical harmonics (1 to 10)

      • +

    • mmax (int) – maximum order of the spherical harmonics (0 to lmax)

      • +

    • sphere_channels (int) – Number of spherical channels (one set per resolution)

      • +

    • hidden_channels (int) – Number of hidden units in message passing

      • +

    • num_sphere_samples (int) – Number of samples used to approximate the integration of the sphere in the output blocks

      • +

    • edge_channels (int) – Number of channels for the edge invariant features

      • +

    • distance_function ("gaussian", "sigmoid", "linearsigmoid", "silu") – Basis function used for distances

      • +

    • basis_width_scalar (float) – Width of distance basis function

      • +

    • distance_resolution (float) – Distance between distance basis functions in Angstroms

      • +
    +
    +
    +
    +
    +regress_forces#
    +
    + +
    +
    +cutoff#
    +
    + +
    +
    +max_num_elements#
    +
    + +
    +
    +hidden_channels#
    +
    + +
    +
    +num_layers#
    +
    + +
    +
    +num_sphere_samples#
    +
    + +
    +
    +sphere_channels#
    +
    + +
    +
    +edge_channels#
    +
    + +
    +
    +distance_resolution#
    +
    + +
    +
    +lmax#
    +
    + +
    +
    +mmax#
    +
    + +
    +
    +basis_width_scalar#
    +
    + +
    +
    +distance_function#
    +
    + +
    +
    +act#
    +
    + +
    +
    +sphere_embedding#
    +
    + +
    +
    +num_gaussians#
    +
    + +
    +
    +SO3_grid#
    +
    + +
    +
    +mappingReduced#
    +
    + +
    +
    +layer_blocks#
    +
    + +
    +
    +energy_block#
    +
    + +
    +
    +sphere_points#
    +
    + +
    +
    +sphharm_weights: torch.nn.Parameter#
    +
    + +
    +
    +forward(data: dict[str, torch.Tensor]) → dict[str, torch.Tensor]#
    +
    + +
    +
    +_init_edge_rot_mat(edge_index, edge_distance_vec)#
    +
    + +
    +
    +property num_params: int#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.LayerBlock(layer_idx: int, sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, distance_expansion, max_num_elements: int, SO3_grid: fairchem.core.models.escn.so3_exportable.SO3_Grid, act, mappingReduced)#
    +

    Bases: torch.nn.Module

    +

    Layer block: Perform one layer (message passing and aggregation) of the GNN

    +
    +
    Parameters:
    +
      +

    • layer_idx (int) – Layer number

      • +

    • sphere_channels (int) – Number of spherical channels

      • +

    • hidden_channels (int) – Number of hidden channels used during the SO(2) conv

      • +

    • edge_channels (int) – Size of invariant edge embedding

      • +

    • lmax (int) degrees (l)

      • +

    • mmax (int) – orders (m) for each resolution

      • +

    • distance_expansion (func) – Function used to compute distance embedding

      • +

    • max_num_elements (int) – Maximum number of atomic numbers

      • +

    • SO3_grid (SO3_grid) – Class used to convert from grid the spherical harmonic representations

      • +

    • act (function) – Non-linear activation function

      • +
    +
    +
    +
    +
    +layer_idx#
    +
    + +
    +
    +act#
    +
    + +
    +
    +lmax#
    +
    + +
    +
    +mmax#
    +
    + +
    +
    +sphere_channels#
    +
    + +
    +
    +SO3_grid#
    +
    + +
    +
    +mappingReduced#
    +
    + +
    +
    +message_block#
    +
    + +
    +
    +fc1_sphere#
    +
    + +
    +
    +fc2_sphere#
    +
    + +
    +
    +fc3_sphere#
    +
    + +
    +
    +forward(x: torch.Tensor, atomic_numbers: torch.Tensor, edge_distance: torch.Tensor, edge_index: torch.Tensor, wigner: torch.Tensor) → torch.Tensor#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.MessageBlock(layer_idx: int, sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, distance_expansion, max_num_elements: int, SO3_grid: fairchem.core.models.escn.so3_exportable.SO3_Grid, act, mappingReduced)#
    +

    Bases: torch.nn.Module

    +

    Message block: Perform message passing

    +
    +
    Parameters:
    +
      +

    • layer_idx (int) – Layer number

      • +

    • sphere_channels (int) – Number of spherical channels

      • +

    • hidden_channels (int) – Number of hidden channels used during the SO(2) conv

      • +

    • edge_channels (int) – Size of invariant edge embedding

      • +

    • lmax (int) – degrees (l) for each resolution

      • +

    • mmax (int) – orders (m) for each resolution

      • +

    • distance_expansion (func) – Function used to compute distance embedding

      • +

    • max_num_elements (int) – Maximum number of atomic numbers

      • +

    • SO3_grid (SO3_grid) – Class used to convert from grid the spherical harmonic representations

      • +

    • act (function) – Non-linear activation function

      • +
    +
    +
    +
    +
    +layer_idx#
    +
    + +
    +
    +act#
    +
    + +
    +
    +hidden_channels#
    +
    + +
    +
    +sphere_channels#
    +
    + +
    +
    +SO3_grid#
    +
    + +
    +
    +lmax#
    +
    + +
    +
    +mmax#
    +
    + +
    +
    +edge_channels#
    +
    + +
    +
    +mappingReduced#
    +
    + +
    +
    +out_mask#
    +
    + +
    +
    +edge_block#
    +
    + +
    +
    +so2_block_source#
    +
    + +
    +
    +so2_block_target#
    +
    + +
    +
    +forward(x: torch.Tensor, atomic_numbers: torch.Tensor, edge_distance: torch.Tensor, edge_index: torch.Tensor, wigner: torch.Tensor) → torch.Tensor#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.SO2Block(sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, act, mappingReduced)#
    +

    Bases: torch.nn.Module

    +

    SO(2) Block: Perform SO(2) convolutions for all m (orders)

    +
    +
    Parameters:
    +
      +

    • sphere_channels (int) – Number of spherical channels

      • +

    • hidden_channels (int) – Number of hidden channels used during the SO(2) conv

      • +

    • edge_channels (int) – Size of invariant edge embedding

      • +

    • lmax (int) – degrees (l) for each resolution

      • +

    • mmax (int) – orders (m) for each resolution

      • +

    • act (function) – Non-linear activation function

      • +
    +
    +
    +
    +
    +sphere_channels#
    +
    + +
    +
    +hidden_channels#
    +
    + +
    +
    +lmax#
    +
    + +
    +
    +mmax#
    +
    + +
    +
    +act#
    +
    + +
    +
    +mappingReduced#
    +
    + +
    +
    +num_channels_m0#
    +
    + +
    +
    +fc1_dist0#
    +
    + +
    +
    +fc1_m0#
    +
    + +
    +
    +fc2_m0#
    +
    + +
    +
    +so2_conv#
    +
    + +
    +
    +forward(x: torch.Tensor, x_edge: torch.Tensor)#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.SO2Conv(m: int, sphere_channels: int, hidden_channels: int, edge_channels: int, lmax: int, mmax: int, act)#
    +

    Bases: torch.nn.Module

    +

    SO(2) Conv: Perform an SO(2) convolution

    +
    +
    Parameters:
    +
      +

    • m (int) – Order of the spherical harmonic coefficients

      • +

    • sphere_channels (int) – Number of spherical channels

      • +

    • hidden_channels (int) – Number of hidden channels used during the SO(2) conv

      • +

    • edge_channels (int) – Size of invariant edge embedding

      • +

    • lmax (int) – degrees (l) for each resolution

      • +

    • mmax (int) – orders (m) for each resolution

      • +

    • act (function) – Non-linear activation function

      • +
    +
    +
    +
    +
    +hidden_channels#
    +
    + +
    +
    +lmax#
    +
    + +
    +
    +mmax#
    +
    + +
    +
    +sphere_channels#
    +
    + +
    +
    +m#
    +
    + +
    +
    +act#
    +
    + +
    +
    +num_coefficents = 0#
    +
    + +
    +
    +num_channels#
    +
    + +
    +
    +fc1_dist#
    +
    + +
    +
    +fc1_r#
    +
    + +
    +
    +fc2_r#
    +
    + +
    +
    +fc1_i#
    +
    + +
    +
    +fc2_i#
    +
    + +
    +
    +forward(x_m, x_edge) → torch.Tensor#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.EdgeBlock(edge_channels, distance_expansion, max_num_elements, act)#
    +

    Bases: torch.nn.Module

    +

    Edge Block: Compute invariant edge representation from edge diatances and atomic numbers

    +
    +
    Parameters:
    +
      +

    • edge_channels (int) – Size of invariant edge embedding

      • +

    • distance_expansion (func) – Function used to compute distance embedding

      • +

    • max_num_elements (int) – Maximum number of atomic numbers

      • +

    • act (function) – Non-linear activation function

      • +
    +
    +
    +
    +
    +in_channels#
    +
    + +
    +
    +distance_expansion#
    +
    + +
    +
    +act#
    +
    + +
    +
    +edge_channels#
    +
    + +
    +
    +max_num_elements#
    +
    + +
    +
    +fc1_dist#
    +
    + +
    +
    +source_embedding#
    +
    + +
    +
    +target_embedding#
    +
    + +
    +
    +fc1_edge_attr#
    +
    + +
    +
    +forward(edge_distance, source_element, target_element)#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.EnergyBlock(num_channels: int, num_sphere_samples: int, act)#
    +

    Bases: torch.nn.Module

    +

    Energy Block: Output block computing the energy

    +
    +
    Parameters:
    +
      +

    • num_channels (int) – Number of channels

      • +

    • num_sphere_samples (int) – Number of samples used to approximate the integral on the sphere

      • +

    • act (function) – Non-linear activation function

      • +
    +
    +
    +
    +
    +num_channels#
    +
    + +
    +
    +num_sphere_samples#
    +
    + +
    +
    +act#
    +
    + +
    +
    +fc1#
    +
    + +
    +
    +fc2#
    +
    + +
    +
    +fc3#
    +
    + +
    +
    +forward(x_pt) → torch.Tensor#
    +
    + +
    + +
    +
    +class core.models.escn.escn_exportable.ForceBlock(num_channels: int, num_sphere_samples: int, act)#
    +

    Bases: torch.nn.Module

    +

    Force Block: Output block computing the per atom forces

    +
    +
    Parameters:
    +
      +

    • num_channels (int) – Number of channels

      • +

    • num_sphere_samples (int) – Number of samples used to approximate the integral on the sphere

      • +

    • act (function) – Non-linear activation function

      • +
    +
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    +
    +
    +num_channels#
    +
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    +num_sphere_samples#
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    +act#
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    +fc1#
    +
    + +
    +
    +fc2#
    +
    + +
    +
    +fc3#
    +
    + +
    +
    +forward(x_pt, sphere_points) → torch.Tensor#
    +
    + +
    + +
    +
    + + + + +
    + + + + + + + + +
    + + + +
    + + +
    +
    + Contents +
    +
    + +
    + + +
    +
    + +
    + +
    + +

    +By FAIR Chemistry & Collaborators +

    + +
    + +
    + + +

    + + © Copyright 2024. +
    + +

    + +
    + +
    + +
    + +
    + +
    + +
    +
    + + +
    +
    +
    + + + + + +
    +
    + + \ No newline at end of file diff --git a/autoapi/core/models/escn/index.html b/autoapi/core/models/escn/index.html index 7d752de651..702ee28014 100644 --- a/autoapi/core/models/escn/index.html +++ b/autoapi/core/models/escn/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -685,7 +685,9 @@

    Submodules

    @@ -704,7 +706,7 @@

    Classes#<

    Package Contents#

    -class core.models.escn.eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False)#
    +class core.models.escn.eSCN(use_pbc: bool = True, use_pbc_single: bool = False, regress_forces: bool = True, otf_graph: bool = False, max_neighbors: int = 40, cutoff: float = 8.0, max_num_elements: int = 90, num_layers: int = 8, lmax_list: list[int] | None = None, mmax_list: list[int] | None = None, sphere_channels: int = 128, hidden_channels: int = 256, edge_channels: int = 128, num_sphere_samples: int = 128, distance_function: str = 'gaussian', basis_width_scalar: float = 1.0, distance_resolution: float = 0.02, show_timing_info: bool = False, resolution: int | None = None)#

    Bases: torch.nn.Module, fairchem.core.models.base.GraphModelMixin

    Equivariant Spherical Channel Network Paper: Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

    diff --git a/autoapi/core/models/escn/so3/index.html b/autoapi/core/models/escn/so3/index.html index 33e41c6cf9..1f7723600c 100644 --- a/autoapi/core/models/escn/so3/index.html +++ b/autoapi/core/models/escn/so3/index.html @@ -61,8 +61,8 @@ - - + + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -1014,7 +1014,7 @@

    Module Contents
    -class core.models.escn.so3.SO3_Grid(lmax: int, mmax: int)#
    +class core.models.escn.so3.SO3_Grid(lmax: int, mmax: int, resolution: int | None = None)#

    Bases: torch.nn.Module

    Helper functions for grid representation of the irreps

    @@ -1106,20 +1106,20 @@

    Module Contents

    previous

    -

    core.models.escn.escn

    +

    core.models.escn.escn_exportable

    next

    -

    core.models.gemnet

    +

    core.models.escn.so3_exportable

     diff --git a/autoapi/core/models/escn/so3_exportable/index.html b/autoapi/core/models/escn/so3_exportable/index.html new file mode 100644 index 0000000000..350284e87b --- /dev/null +++ b/autoapi/core/models/escn/so3_exportable/index.html @@ -0,0 +1,1099 @@ + + + + + + + + + + + core.models.escn.so3_exportable + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    core.models.escn.so3_exportable

    + +
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    + + + + +
    + +
    +

    core.models.escn.so3_exportable#

    +
    +

    Attributes#

    +
    + + + + + +

    __Jd

    +
    +
    +
    +

    Classes#

    +
    + + + + + + + + +

    CoefficientMapping

    Helper module for coefficients used to reshape l <--> m and to get coefficients of specific degree or order

    SO3_Grid

    Helper functions for grid representation of the irreps

    +
    +
    +
    +

    Functions#

    +
    + + + + + + + + + + + + + + +

    get_jd(→ torch.Tensor)

    wigner_D(→ torch.Tensor)

    _z_rot_mat(→ torch.Tensor)

    rotation_to_wigner(→ torch.Tensor)

    +
    +
    +
    +

    Module Contents#

    +
    +
    +core.models.escn.so3_exportable.__Jd#
    +
    + +
    +
    +core.models.escn.so3_exportable.get_jd() → torch.Tensor#
    +
    + +
    +
    +core.models.escn.so3_exportable.wigner_D(lv: int, alpha: torch.Tensor, beta: torch.Tensor, gamma: torch.Tensor) → torch.Tensor#
    +
    + +
    +
    +core.models.escn.so3_exportable._z_rot_mat(angle: torch.Tensor, lv: int) → torch.Tensor#
    +
    + +
    +
    +core.models.escn.so3_exportable.rotation_to_wigner(edge_rot_mat: torch.Tensor, start_lmax: int, end_lmax: int) → torch.Tensor#
    +
    + +
    +
    +class core.models.escn.so3_exportable.CoefficientMapping(lmax_list, mmax_list)#
    +

    Bases: torch.nn.Module

    +

    Helper module for coefficients used to reshape l <–> m and to get coefficients of specific degree or order

    +
    +
    Parameters:
    +
      +

    • (list (mmax_list) – int): List of maximum degree of the spherical harmonics

      • +

    • (list – int): List of maximum order of the spherical harmonics

      • +

    • use_rotate_inv_rescale (bool) – Whether to pre-compute inverse rotation rescale matrices

      • +
    +
    +
    +
    +
    +lmax_list#
    +
    + +
    +
    +mmax_list#
    +
    + +
    +
    +num_resolutions#
    +
    + +
    +
    +l_harmonic#
    +
    + +
    +
    +m_harmonic#
    +
    + +
    +
    +m_complex#
    +
    + +
    +
    +res_size#
    +
    + +
    +
    +offset = 0#
    +
    + +
    +
    +num_coefficients#
    +
    + +
    +
    +to_m#
    +
    + +
    +
    +m_size#
    +
    + +
    +
    +complex_idx(m, lmax, m_complex, l_harmonic)#
    +

    Add m_complex and l_harmonic to the input arguments +since we cannot use self.m_complex.

    +
    + +
    +
    +pre_compute_coefficient_idx()#
    +

    Pre-compute the results of coefficient_idx() and access them with prepare_coefficient_idx()

    +
    + +
    +
    +prepare_coefficient_idx()#
    +

    Construct a list of buffers

    +
    + +
    +
    +coefficient_idx(lmax: int, mmax: int)#
    +
    + +
    +
    +pre_compute_rotate_inv_rescale()#
    +
    + +
    +
    +__repr__()#
    +
    + +
    + +
    +
    +class core.models.escn.so3_exportable.SO3_Grid(lmax: int, mmax: int, normalization: str = 'integral', resolution: int | None = None)#
    +

    Bases: torch.nn.Module

    +

    Helper functions for grid representation of the irreps

    +
    +
    Parameters:
    +
      +

    • lmax (int) – Maximum degree of the spherical harmonics

      • +

    • mmax (int) – Maximum order of the spherical harmonics

      • +
    +
    +
    +
    +
    +lmax#
    +
    + +
    +
    +mmax#
    +
    + +
    +
    +lat_resolution#
    +
    + +
    +
    +mapping#
    +
    + +
    +
    +device = 'cpu'#
    +
    + +
    +
    +to_grid#
    +
    + +
    +
    +to_grid_mat#
    +
    + +
    +
    +from_grid#
    +
    + +
    +
    +from_grid_mat#
    +
    + +
    +
    +get_to_grid_mat(device=None)#
    +
    + +
    +
    +get_from_grid_mat(device=None)#
    +
    + +
    + +
    +
    + + + + +
    + + + + + + + + +
    + + + +
    + + +
    +
    + Contents +
    +
    + +
    + + +
    +
    + +
    + +
    + +

    +By FAIR Chemistry & Collaborators +

    + +
    + +
    + + +

    + + © Copyright 2024. +
    + +

    + +
    + +
    + +
    + +
    + +
    + +
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    + + +
    +
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    + + + + + +
    +
    + + \ No newline at end of file diff --git a/autoapi/core/models/finetune_hydra/index.html b/autoapi/core/models/finetune_hydra/index.html deleted file mode 100644 index 624a5c6616..0000000000 --- a/autoapi/core/models/finetune_hydra/index.html +++ /dev/null @@ -1,1079 +0,0 @@ - - - - - - - - - - - core.models.finetune_hydra - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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    core.models.finetune_hydra

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    core.models.finetune_hydra#

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    Attributes#

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    FTHYDRA_NAME

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    Classes#

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    FineTuneMode

    Create a collection of name/value pairs.

    FTConfig

    FineTuneHydra

    Base class for all neural network modules.

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    Functions#

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    get_model_config_from_checkpoint(→ dict)

    load_hydra_model(...)

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    Module Contents#

    -
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    -core.models.finetune_hydra.FTHYDRA_NAME = 'finetune_hydra'#
    -
    - -
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    -class core.models.finetune_hydra.FineTuneMode(*args, **kwds)#
    -

    Bases: enum.Enum

    -

    Create a collection of name/value pairs.

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    Example enumeration:

    -
    >>> class Color(Enum):
-...     RED = 1
-...     BLUE = 2
-...     GREEN = 3
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-<Color.RED: 1>
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-3
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-[<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]
-
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    Methods can be added to enumerations, and members can have their own -attributes – see the documentation for details.

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    -RETAIN_BACKBONE_ONLY = 2#
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    -core.models.finetune_hydra.get_model_config_from_checkpoint(checkpoint_path: str) → dict#
    -
    - -
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    -core.models.finetune_hydra.load_hydra_model(checkpoint_path: str) → fairchem.core.models.base.HydraInterface#
    -
    - -
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    -class core.models.finetune_hydra.FTConfig(config: dict)#
    -
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    -FT_CONFIG_NAME = 'finetune_config'#
    -
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    -STARTING_CHECKPOINT = 'starting_checkpoint'#
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    -STARTING_MODEL = 'starting_model'#
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    -property mode: FineTuneMode#
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    -property head_config: dict#
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    -class core.models.finetune_hydra.FineTuneHydra(finetune_config: dict)#
    -

    Bases: torch.nn.Module, fairchem.core.models.base.HydraInterface

    -

    Base class for all neural network modules.

    -

    Your models should also subclass this class.

    -

    Modules can also contain other Modules, allowing to nest them in -a tree structure. You can assign the submodules as regular attributes:

    -
    import torch.nn as nn
-import torch.nn.functional as F
-
-class Model(nn.Module):
-    def __init__(self):
-        super().__init__()
-        self.conv1 = nn.Conv2d(1, 20, 5)
-        self.conv2 = nn.Conv2d(20, 20, 5)
-
-    def forward(self, x):
-        x = F.relu(self.conv1(x))
-        return F.relu(self.conv2(x))
-
    -
    -

    Submodules assigned in this way will be registered, and will have their -parameters converted too when you call to(), etc.

    -
    -

    Note

    -

    As per the example above, an __init__() call to the parent class -must be made before assignment on the child.

    -
    -
    -
    Variables:
    -

    training (bool) – Boolean represents whether this module is in training or -evaluation mode.

    -
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    -ft_config#
    -
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    -hydra_model: fairchem.core.models.base.HydraInterface#
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    -backbone: fairchem.core.models.base.BackboneInterface#
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    - -
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    -forward(data: torch_geometric.data.Batch)#
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    -get_backbone() → fairchem.core.models.base.BackboneInterface#
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  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/index.html b/autoapi/core/models/gemnet/index.html index c0dfe14143..7822748223 100644 --- a/autoapi/core/models/gemnet/index.html +++ b/autoapi/core/models/gemnet/index.html @@ -62,7 +62,7 @@ - + @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -943,12 +943,12 @@

    Package Contents

    previous

    -

    core.models.escn.so3

    +

    core.models.escn.so3_exportable

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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
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  • core.scripts.download_data
  • core.scripts.download_large_files
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  • core.scripts.eqv2_to_hydra_eqv2
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    • diff --git a/autoapi/core/models/gemnet/layers/atom_update_block/index.html b/autoapi/core/models/gemnet/layers/atom_update_block/index.html index da2253ec59..d2d74ae19c 100644 --- a/autoapi/core/models/gemnet/layers/atom_update_block/index.html +++ b/autoapi/core/models/gemnet/layers/atom_update_block/index.html @@ -335,7 +335,6 @@
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  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/base_layers/index.html b/autoapi/core/models/gemnet/layers/base_layers/index.html index 3cb4cd336a..bcf3ed8a76 100644 --- a/autoapi/core/models/gemnet/layers/base_layers/index.html +++ b/autoapi/core/models/gemnet/layers/base_layers/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/basis_utils/index.html b/autoapi/core/models/gemnet/layers/basis_utils/index.html index e776154876..9baf22c9b6 100644 --- a/autoapi/core/models/gemnet/layers/basis_utils/index.html +++ b/autoapi/core/models/gemnet/layers/basis_utils/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/efficient/index.html b/autoapi/core/models/gemnet/layers/efficient/index.html index 223a309e6d..b4e87d6488 100644 --- a/autoapi/core/models/gemnet/layers/efficient/index.html +++ b/autoapi/core/models/gemnet/layers/efficient/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/embedding_block/index.html b/autoapi/core/models/gemnet/layers/embedding_block/index.html index ba19d79c23..033082ec2b 100644 --- a/autoapi/core/models/gemnet/layers/embedding_block/index.html +++ b/autoapi/core/models/gemnet/layers/embedding_block/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/index.html b/autoapi/core/models/gemnet/layers/index.html index ffa0d3281f..e898e6220d 100644 --- a/autoapi/core/models/gemnet/layers/index.html +++ b/autoapi/core/models/gemnet/layers/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/interaction_block/index.html b/autoapi/core/models/gemnet/layers/interaction_block/index.html index 42ef3fb5fa..619f28efda 100644 --- a/autoapi/core/models/gemnet/layers/interaction_block/index.html +++ b/autoapi/core/models/gemnet/layers/interaction_block/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/radial_basis/index.html b/autoapi/core/models/gemnet/layers/radial_basis/index.html index 9d0c651426..a889a1f2a1 100644 --- a/autoapi/core/models/gemnet/layers/radial_basis/index.html +++ b/autoapi/core/models/gemnet/layers/radial_basis/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/layers/spherical_basis/index.html b/autoapi/core/models/gemnet/layers/spherical_basis/index.html index 158b8b7839..cfc2bf9cd4 100644 --- a/autoapi/core/models/gemnet/layers/spherical_basis/index.html +++ b/autoapi/core/models/gemnet/layers/spherical_basis/index.html @@ -335,7 +335,6 @@
  • core.models.utils
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet/utils/index.html b/autoapi/core/models/gemnet/utils/index.html index a6ac79a427..92eb9ed54f 100644 --- a/autoapi/core/models/gemnet/utils/index.html +++ b/autoapi/core/models/gemnet/utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/gemnet/index.html b/autoapi/core/models/gemnet_gp/gemnet/index.html index 8ce960c53a..d08102534b 100644 --- a/autoapi/core/models/gemnet_gp/gemnet/index.html +++ b/autoapi/core/models/gemnet_gp/gemnet/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/index.html b/autoapi/core/models/gemnet_gp/index.html index 9a79ca6e44..6a168f52fd 100644 --- a/autoapi/core/models/gemnet_gp/index.html +++ b/autoapi/core/models/gemnet_gp/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/initializers/index.html b/autoapi/core/models/gemnet_gp/initializers/index.html index a071c90a79..109bccbfa3 100644 --- a/autoapi/core/models/gemnet_gp/initializers/index.html +++ b/autoapi/core/models/gemnet_gp/initializers/index.html @@ -335,7 +335,6 @@
  • core.models.utils
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/layers/atom_update_block/index.html b/autoapi/core/models/gemnet_gp/layers/atom_update_block/index.html index 9180f8729a..66a3fde039 100644 --- a/autoapi/core/models/gemnet_gp/layers/atom_update_block/index.html +++ b/autoapi/core/models/gemnet_gp/layers/atom_update_block/index.html @@ -335,7 +335,6 @@
  • core.models.utils
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/layers/base_layers/index.html b/autoapi/core/models/gemnet_gp/layers/base_layers/index.html index 803ce65da4..f16efb4d6f 100644 --- a/autoapi/core/models/gemnet_gp/layers/base_layers/index.html +++ b/autoapi/core/models/gemnet_gp/layers/base_layers/index.html @@ -335,7 +335,6 @@
  • core.models.utils
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  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/layers/basis_utils/index.html b/autoapi/core/models/gemnet_gp/layers/basis_utils/index.html index 99b8dcc31e..48d6e15802 100644 --- a/autoapi/core/models/gemnet_gp/layers/basis_utils/index.html +++ b/autoapi/core/models/gemnet_gp/layers/basis_utils/index.html @@ -335,7 +335,6 @@
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
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    • diff --git a/autoapi/core/models/gemnet_gp/layers/efficient/index.html b/autoapi/core/models/gemnet_gp/layers/efficient/index.html index 160029bd29..97690aa84e 100644 --- a/autoapi/core/models/gemnet_gp/layers/efficient/index.html +++ b/autoapi/core/models/gemnet_gp/layers/efficient/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
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  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/layers/embedding_block/index.html b/autoapi/core/models/gemnet_gp/layers/embedding_block/index.html index 3efc25c941..860a9fbc47 100644 --- a/autoapi/core/models/gemnet_gp/layers/embedding_block/index.html +++ b/autoapi/core/models/gemnet_gp/layers/embedding_block/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/layers/index.html b/autoapi/core/models/gemnet_gp/layers/index.html index 4f925edad2..c2679532d7 100644 --- a/autoapi/core/models/gemnet_gp/layers/index.html +++ b/autoapi/core/models/gemnet_gp/layers/index.html @@ -335,7 +335,6 @@
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    • -
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
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    • diff --git a/autoapi/core/models/gemnet_gp/layers/interaction_block/index.html b/autoapi/core/models/gemnet_gp/layers/interaction_block/index.html index 25e1f133bd..e4833664b0 100644 --- a/autoapi/core/models/gemnet_gp/layers/interaction_block/index.html +++ b/autoapi/core/models/gemnet_gp/layers/interaction_block/index.html @@ -335,7 +335,6 @@
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  • core.models.dimenet_plus_plus
    • -
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
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  • core.scripts.eqv2_to_hydra_eqv2
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  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/models/gemnet_gp/layers/radial_basis/index.html b/autoapi/core/models/gemnet_gp/layers/radial_basis/index.html index cd2d3a12f5..d6d55e459e 100644 --- a/autoapi/core/models/gemnet_gp/layers/radial_basis/index.html +++ b/autoapi/core/models/gemnet_gp/layers/radial_basis/index.html @@ -335,7 +335,6 @@
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    • -
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    • @@ -358,6 +357,7 @@
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    • diff --git a/autoapi/core/models/gemnet_gp/layers/spherical_basis/index.html b/autoapi/core/models/gemnet_gp/layers/spherical_basis/index.html index 92b3560206..5ad14d4199 100644 --- a/autoapi/core/models/gemnet_gp/layers/spherical_basis/index.html +++ b/autoapi/core/models/gemnet_gp/layers/spherical_basis/index.html @@ -335,7 +335,6 @@
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    • @@ -358,6 +357,7 @@
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    • @@ -358,6 +357,7 @@
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    • @@ -358,6 +357,7 @@
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    • diff --git a/autoapi/core/models/gemnet_oc/index.html b/autoapi/core/models/gemnet_oc/index.html index b231085d91..3789fe536c 100644 --- a/autoapi/core/models/gemnet_oc/index.html +++ b/autoapi/core/models/gemnet_oc/index.html @@ -335,7 +335,6 @@
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    • @@ -358,6 +357,7 @@
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    • diff --git a/autoapi/core/models/gemnet_oc/initializers/index.html b/autoapi/core/models/gemnet_oc/initializers/index.html index 0607796af3..45d1baea5a 100644 --- a/autoapi/core/models/gemnet_oc/initializers/index.html +++ b/autoapi/core/models/gemnet_oc/initializers/index.html @@ -335,7 +335,6 @@
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  • core.models.schnet
    • @@ -358,6 +357,7 @@
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    • @@ -360,6 +359,7 @@
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    • @@ -827,8 +827,7 @@

    Package Contents
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    • @@ -360,6 +359,7 @@
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    • @@ -914,8 +914,7 @@

    Module Contents
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  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/exponential_moving_average/index.html b/autoapi/core/modules/exponential_moving_average/index.html index f5b4a0f29f..f724d2d437 100644 --- a/autoapi/core/modules/exponential_moving_average/index.html +++ b/autoapi/core/modules/exponential_moving_average/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/index.html b/autoapi/core/modules/index.html index d50c2adc2a..35d90b5ff7 100644 --- a/autoapi/core/modules/index.html +++ b/autoapi/core/modules/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/loss/index.html b/autoapi/core/modules/loss/index.html index 70248a899a..7b8021fb5f 100644 --- a/autoapi/core/modules/loss/index.html +++ b/autoapi/core/modules/loss/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/normalization/_load_utils/index.html b/autoapi/core/modules/normalization/_load_utils/index.html index 384dd7a1e9..6934ec9ac1 100644 --- a/autoapi/core/modules/normalization/_load_utils/index.html +++ b/autoapi/core/modules/normalization/_load_utils/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/normalization/element_references/index.html b/autoapi/core/modules/normalization/element_references/index.html index 0137d00e9d..2ad5608d53 100644 --- a/autoapi/core/modules/normalization/element_references/index.html +++ b/autoapi/core/modules/normalization/element_references/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/normalization/index.html b/autoapi/core/modules/normalization/index.html index 1c2d20ecbe..7700e783ec 100644 --- a/autoapi/core/modules/normalization/index.html +++ b/autoapi/core/modules/normalization/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/normalization/normalizer/index.html b/autoapi/core/modules/normalization/normalizer/index.html index b9d5802fac..be5d2fc572 100644 --- a/autoapi/core/modules/normalization/normalizer/index.html +++ b/autoapi/core/modules/normalization/normalizer/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/scaling/compat/index.html b/autoapi/core/modules/scaling/compat/index.html index 6d2d9c60c2..5e6e1a4d3a 100644 --- a/autoapi/core/modules/scaling/compat/index.html +++ b/autoapi/core/modules/scaling/compat/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • diff --git a/autoapi/core/modules/scaling/fit/index.html b/autoapi/core/modules/scaling/fit/index.html index 0449fbb174..32e68362f4 100644 --- a/autoapi/core/modules/scaling/fit/index.html +++ b/autoapi/core/modules/scaling/fit/index.html @@ -335,7 +335,6 @@
  • core.models.utils
  • core.models.base
  • core.models.dimenet_plus_plus
    • -
  • core.models.finetune_hydra
  • core.models.model_registry
  • core.models.schnet
    • @@ -358,6 +357,7 @@
  • core.scripts.hpo
  • core.scripts.download_data
  • core.scripts.download_large_files
    • +
  • core.scripts.eqv2_to_hydra_eqv2
  • core.scripts.fit_normalizers
  • core.scripts.fit_references
  • core.scripts.gif_maker_parallelized
    • @@ -625,11 +625,13 @@

    Contents