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Functions1,670 in github.com/Yangxinsix/curator

⨍ Functions 1,670◇ Types & classes 262
↓ 2 callersFunction_normalize_shared_internal_weights
( *, internal_weights: Optional[bool], shared_weights: Optional[bool], )
curator/layer/wrappers/oeq.py:67
↓ 2 callersFunction_normalize_symbol
(raw: str)
curator/model/utils.py:199
↓ 2 callersMethod_parse_outputs
(self, out: torch.Tensor, index: Optional[torch.Tensor] = None)
curator/layer/_atomwise_nn.py:143
↓ 2 callersMethod_per_atom_output_keys
(self, module: AtomwiseNN)
curator/layer/_atomwise_nn.py:456
↓ 2 callersFunction_prepare_model
( loaded: LoadedModel, *, config: DictConfig, datamodule: Any, data_dtype=None, )
curator/commands/train.py:242
↓ 2 callersMethod_prepare_weight
( self, weight: Optional[torch.Tensor], *, batch_shape: torch.Size, dt
curator/layer/wrappers/oeq.py:241
↓ 2 callersFunction_promote_instruction
(ins: Any)
curator/layer/wrappers/oeq.py:97
↓ 2 callersMethod_read_trajectory
(source: Union[str, Path])
curator/select/active_learning.py:408
↓ 2 callersFunction_register_legacy_outputspec
()
curator/model/checkpoint_upgrade.py:185
↓ 2 callersMethod_reorder_to_oeq
( self, weight: torch.Tensor, *, dtype: torch.dtype, shared_weights: b
curator/layer/wrappers/oeq.py:214
↓ 2 callersMethod_reshape_output
(tensor: torch.Tensor, batch_shape: torch.Size)
curator/layer/wrappers/oeq.py:238
↓ 2 callersMethod_resolve_calculators
(self)
curator/layer/feature/statistics.py:96
↓ 2 callersMethod_resolve_distance_kernel
(self, kernel: Optional[KernelName] = None)
curator/layer/feature/calculator.py:183
↓ 2 callersFunction_resolve_domain_selector
( available: List[str], selector: Optional[Union[str, int]], )
curator/model/conversion.py:167
↓ 2 callersFunction_resolve_elora_hyperparameters
( *, rank: int, alpha: float, elora_rank: int | None, elora_alpha: float | None, )
curator/layer/wrappers/mlp.py:18
↓ 2 callersMethod_resolve_head_out_features
(self, head: HeadConfig)
curator/layer/_atomwise_nn.py:204
↓ 2 callersMethod_resolve_key
(self, data: properties.Type)
curator/layer/_rescale.py:110
↓ 2 callersFunction_resolve_model_domains
( model: torch.nn.Module, domains: Optional[Union[str, int, List[Union[str, int]]]] = None, )
curator/model/conversion.py:203
↓ 2 callersFunction_resolve_target_path
(target_path: str, *, lammps_mliap: bool, python_object: bool = False)
curator/commands/deploy.py:40
↓ 2 callersMethod_resolve_value_pair
( self, pred: Dict, target: Optional[Dict] = None, apply_sampling: bool = Fals
curator/train/model_output.py:98
↓ 2 callersMethod_retarget_rescale_module
(module)
curator/simulate/lammps_mliap_interface.py:181
↓ 2 callersFunction_run_command
( command: Sequence[str], *, timeout_sec: int, cwd: Optional[str] = None, )
curator/mcp_server.py:30
↓ 2 callersMethod_scatter_outputs
( self, combined: Dict[str, torch.Tensor], output: Dict[str, torch.Tensor], mo
curator/layer/_atomwise_nn.py:494
↓ 2 callersMethod_select_groups
(self, available_groups, requested_names, *, kind: str)
curator/train/callbacks.py:170
↓ 2 callersMethod_set_buffer_tensor
(self, name: str, tensor: torch.Tensor)
curator/layer/feature/kme.py:301
↓ 2 callersMethod_set_trainable
(self, module_groups, names, *, trainable: bool)
curator/train/callbacks.py:91
↓ 2 callersMethod_split_output_modules
(self)
curator/model/multi_domain.py:24
↓ 2 callersFunction_squeeze_if_compatible
(src: torch.Tensor, target_shape: torch.Size)
curator/utils.py:1129
↓ 2 callersMethod_stack_features
( cache: Optional[Dict[str, List[List[torch.Tensor]]]], kernel_names: List[str], )
curator/layer/feature/statistics.py:276
↓ 2 callersMethod_stats
( self, models: List[nn.Module], dataset: torch.utils.data.Dataset, feature_sp
curator/select/active_learning.py:289
↓ 2 callersFunction_strip_idx
(value: Optional[str])
curator/utils.py:689
↓ 2 callersMethod_summarize_atoms
Return a human-friendly summary for one Atoms object.
curator/simulate/core/simulator.py:78
↓ 2 callersMethod_sync_reduced_outputs
(self, data: properties.Type)
curator/layer/_rescale.py:395
↓ 2 callersFunction_torch_load
(model_file: Path, device, load_weights_only: bool)
curator/utils.py:112
↓ 2 callersMethod_train_step_single
(self, batch: Dict)
curator/model/lit_module.py:304
↓ 2 callersFunction_unwrap_hook_payload
(payload)
curator/model/external/backbone.py:28
↓ 2 callersFunction_update_rescale_heads
(cfg: DictConfig, heads: List)
curator/utils.py:598
↓ 2 callersMethod_update_uncertainty_outputs
( self, result_dict: Dict[str, torch.Tensor], *, energy_per_model: torch.Tenso
curator/model/ensemble.py:123
↓ 2 callersFunction_upgrade_legacy_rescale_transforms
(module: GlobalRescaleShift)
curator/model/checkpoint_upgrade.py:42
↓ 2 callersFunction_validate_oeq_instructions
( instructions: Sequence[tuple[int, int, int, str, bool, float]], )
curator/layer/wrappers/oeq.py:125
↓ 2 callersMethod_voigt6_to_full
Convert a (..., 6) Voigt-form tensor to (..., 3, 3). Order assumed: xx, yy, zz, yz, xz, xy (ASE convention).
curator/interface/torchsim.py:353
↓ 2 callersMethodadd_data
Add data from a dictionary to the SQLite database. :param data_dict: Dictionary containing the data to insert :param flags: S
curator/data/sql_database.py:150
↓ 2 callersFunctionadd_from
(candidate: nn.Module)
curator/data/_uncertainty.py:33
↓ 2 callersMethodadd_hooks
(self)
curator/layer/feature/extractor.py:66
↓ 2 callersMethodannotate
(self, atoms: ase.Atoms)
curator/label/annotator.py:26
↓ 2 callersFunctionas_scalar
(value: Any, default: float)
curator/model/checkpoint_upgrade.py:83
↓ 2 callersMethodattach
(self, repr_callback: nn.Module)
curator/layer/feature/extractor.py:53
↓ 2 callersFunctionbuild_atomic_number_to_type_map
( type_names: Iterable[str], type_map: Optional[str] = None, )
curator/model/utils.py:205
↓ 2 callersFunctionbuild_energy_head
(head_idx: int)
curator/model/conversion.py:640
↓ 2 callersFunctionbuild_ptr
(n_atoms: torch.Tensor, device: torch.device)
curator/model/utils.py:89
↓ 2 callersFunctionbuild_scalar_mlp
( dims: Sequence[int], *, layer_builder: Callable[[int, int, bool], nn.Module], activation: Op
curator/layer/wrappers/scalar.py:181
↓ 2 callersFunctionbuild_species_value_dict
(values: Optional[torch.Tensor])
curator/model/conversion.py:1163
↓ 2 callersMethodcalculate
Calculate atomic properties using ML model. Args: atoms (ase.Atoms): ASE atoms object. properties (list of st
curator/simulate/core/calculator.py:69
↓ 2 callersMethodcalculate_loss
(self, pred: Dict, target: Optional[Dict] = None, return_num_obs=True)
curator/train/model_output.py:111
↓ 2 callersMethodcalculate_metrics
(self, pred: Dict, target: Dict, subset: str)
curator/train/model_output.py:156
↓ 2 callersFunctioncat_tensors
(tensors: List[torch.Tensor])
curator/data/collate_atoms_data.py:11
↓ 2 callersFunctioncheckpoint_state_dict
(checkpoint_payload: Any, *, context: str)
curator/commands/train.py:62
↓ 2 callersMethodclone_with_representation
(self, representation: nn.Module)
curator/model/base.py:265
↓ 2 callersFunctioncollect_uncertainty_outputs
Return declared scalar and per-atom uncertainty keys for a module tree.
curator/data/_uncertainty.py:27
↓ 2 callersMethodcompute_error
(self, pred, target)
curator/train/metrics.py:179
↓ 2 callersFunctioncompute_grad
(grad_output: torch.Tensor)
curator/layer/_energy_hessian.py:14
↓ 2 callersMethodcompute_shift
(self, data: properties.Type, target_key: Optional[str] = None)
curator/layer/_rescale.py:116
↓ 2 callersFunctionconvert_lammps_dump_to_trajectory
( dump_file: Path | str, output_path: Path | str, *, specorder: Optional[Sequence[str]] = None
curator/simulate/engines/lammps/io.py:82
↓ 2 callersMethoddatamodule
(self, _datamodule)
curator/layer/_convnet.py:202
↓ 2 callersMethoddelta
(self)
curator/layer/wrappers/utils.py:129
↓ 2 callersFunctiondense_idx_or_none
(mlp_idx: int)
curator/model/conversion.py:1245
↓ 2 callersFunctiondeploy_model
(model, file_path: str)
curator/utils.py:996
↓ 2 callersFunctiondistill_output_source_property
(cfg: DictConfig)
curator/train/distill.py:31
↓ 2 callersMethodensure
( self, kernels: Optional[Sequence[KernelName]] = None, dataset_size: Optional[int] =
curator/layer/feature/store.py:33
↓ 2 callersMethodextract_outputs
(self, data: properties.Type)
curator/model/base.py:240
↓ 2 callersMethodextract_peratom
interface/ML-IAP/pair_mliap.cpp:459
↓ 2 callersMethodfit
( self, features: torch.Tensor, image_idx: Optional[torch.Tensor] = None, redu
curator/layer/feature/distance.py:26
↓ 2 callersMethodforward
( self, data: properties.Type, lammps_data: Optional[Any] = None, n_local: Opt
curator/model/mace.py:316
↓ 2 callersMethodforward_with_weight
( self, x: torch.Tensor, attrs: torch.Tensor, weight: torch.Tensor, )
curator/layer/wrappers/cueq.py:115
↓ 2 callersMethodfrom_readers
(cls, readers)
curator/data/_data_reader.py:39
↓ 2 callersMethodget_ekin
(self, ctx: SimContext, idx: Optional[int] = None)
curator/simulate/callbacks/torchsim_logger.py:99
↓ 2 callersMethodget_epot
(self, ctx: SimContext)
curator/simulate/callbacks/thermo.py:106
↓ 2 callersFunctionget_kmax_pairs
( max_L: int, correlation: int, num_layers: int )
curator/utils.py:1094
↓ 2 callersMethodget_metric_name
(self)
curator/train/metrics.py:89
↓ 2 callersMethodget_number_of_columns
(self)
curator/select/kernel.py:8
↓ 2 callersMethodget_reciprocal_k_vectors
Generate all reciprocal vectors k = B @ n such that |k| <= k_cut. Parameters ---------- cell : torch.Tensor,
curator/layer/_ewald.py:207
↓ 2 callersFunctionget_wrapper_config
()
curator/layer/wrappers/config.py:155
↓ 2 callersFunctionidentity_matrix
curator/native/neighbors.cpp:219
↓ 2 callersFunctioninfer_allegro_cutoff
(model: nn.Module)
curator/model/utils.py:296
↓ 2 callersFunctioninfer_allegro_type_names
( model: nn.Module, species: Optional[Iterable[str]] = None, *, error_hint: Optional[str] = No
curator/model/utils.py:307
↓ 2 callersFunctionis_elora_parameter
(name: str, parameter: nn.Parameter)
curator/layer/wrappers/utils.py:17
↓ 2 callersFunctionis_offline_distill_output
(cfg: DictConfig)
curator/train/distill.py:36
↓ 2 callersFunctioniter_distill_outputs
(outputs: Optional[DictConfig])
curator/train/distill.py:15
↓ 2 callersMethoditer_kernel_features
(self, kernel: KernelName)
curator/layer/feature/statistics.py:111
↓ 2 callersFunctionload_pretrained_weights_from_model
( target_model: torch.nn.Module, source_model: torch.nn.Module, )
curator/model/conversion.py:1501
↓ 2 callersMethodlog_summary
(self)
curator/data/datamodule.py:773
↓ 2 callersFunctionloss_fn
Computes the loss for the given predictions and batch data. Args: outputs: List of output modules. pred: Predicted values fr
curator/train/train.py:7
↓ 2 callersFunctionmake_bytearray_int32
curator/native/neighbors.cpp:278
↓ 2 callersFunctionmap_atomic_numbers_to_types
(numbers: torch.Tensor, z_to_type: Dict[int, int])
curator/model/utils.py:235
↓ 2 callersFunctionmark_lora_parameter
(parameter: nn.Parameter | None)
curator/layer/wrappers/utils.py:12
↓ 2 callersFunctionmatmul_row
curator/native/neighbors.cpp:180
↓ 2 callersFunctionmerge_model_wrappers
(model: nn.Module)
curator/layer/wrappers/patch.py:215
↓ 2 callersFunctionoeq_runtime_error
()
curator/layer/wrappers/oeq.py:28
↓ 2 callersFunctionoffset_is_zero
curator/native/neighbors.cpp:247
↓ 2 callersFunctionpick
(values: torch.Tensor)
curator/model/conversion.py:661
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