Index _ | A | B | C | D | E | F | G | H | I | J | L | M | N | O | P | Q | R | S | T | U _ __call__() (GNN method) __init__() (Problem method) (ProblemBatch method) (ProblemLoader method) __iter__() (ProblemLoader method) __len__() (ProblemLoader method) __next__() (ProblemLoader method) A array (GraphShape property) (HyperEdgeSet property) B build_hyper_edge_set_shape() (in module energnn.graph) C CenterReduceNormalizer (class in energnn.model.normalizer) check_dict_or_none() (in module energnn.graph) check_dict_shape() (in module energnn.graph) check_hyper_edge_set_dict_type() (in module energnn.graph) check_no_nan() (in module energnn.graph) collate_graphs() (in module energnn.graph) collate_hyper_edge_sets() (in module energnn.graph) collate_shapes() (in module energnn.graph) concatenate_graphs() (in module energnn.graph) concatenate_hyper_edge_sets() (in module energnn.graph) context_structure (Problem property) (ProblemBatch property) (ProblemLoader property) count_connected_components() (Graph method) Coupler (class in energnn.model.coupler) D decision_structure (Problem property) (ProblemBatch property) (ProblemLoader property) Decoder (class in energnn.model.decoder) dict2array() (in module energnn.graph) E Encoder (class in energnn.model.encoder) EquivariantDecoder (class in energnn.model.decoder) ExtraLargeRecurrentEquivariantGNN (class in energnn.model.ready_to_use) F feature_dict (HyperEdgeSet property) feature_flat_array (Graph property) (HyperEdgeSet property) (JaxGraph property) (JaxHyperEdgeSet property) forward_batch() (GNN method) from_dict() (Graph class method) (GraphShape class method) (HyperEdgeSet class method) from_jsonable_dict() (GraphShape class method) from_numpy_graph() (JaxGraph class method) from_numpy_hyper_edge_set() (JaxHyperEdgeSet class method) from_numpy_shape() (JaxGraphShape class method) from_pickle() (Graph class method) (ProblemDataset class method) G get_context() (Problem method) (ProblemBatch method) get_gradient() (Problem method) (ProblemBatch method) get_infos_for_feature_store() (ProblemDataset method) get_instance_paths() (ProblemDataset method) get_locally_missing_instances() (ProblemDataset method) get_score() (Problem method) (ProblemBatch method) get_statistics() (in module energnn.graph) GNN (class in energnn.model) Graph (class in energnn.graph) GraphShape (class in energnn.graph) H HyperEdgeSet (class in energnn.graph) I IdentityEncoder (class in energnn.model.encoder) IdentityMessagePassingFunction (class in energnn.model.coupler) InvariantDecoder (class in energnn.model.decoder) is_batch (Graph property) (GraphShape property) (HyperEdgeSet property) is_single (Graph property) (GraphShape property) (HyperEdgeSet property) J JaxGraph (class in energnn.graph) JaxGraphShape (class in energnn.graph) JaxHyperEdgeSet (class in energnn.graph) jnp_to_np() (in module energnn.graph) L LargeRecurrentEquivariantGNN (class in energnn.model.ready_to_use) load_checkpoint() (Trainer method) LocalSumMessagePassingFunction (class in energnn.model.coupler) M max() (GraphShape class method) max_shape() (in module energnn.graph) MeanInvariantDecoder (class in energnn.model.decoder) MediumRecurrentEquivariantGNN (class in energnn.model.ready_to_use) MessagePassingFunction (class in energnn.model.coupler) MLPEncoder (class in energnn.model.encoder) MLPEquivariantDecoder (class in energnn.model.decoder) N n_batch (GraphShape property) (HyperEdgeSet property) n_obj (HyperEdgeSet property) NODECoupler (class in energnn.model.coupler) Normalizer (class in energnn.model.normalizer) np_to_jnp() (in module energnn.graph) O offset_addresses() (Graph method) (HyperEdgeSet method) P pad() (Graph method) (HyperEdgeSet method) port_array (HyperEdgeSet property) port_names (HyperEdgeSet property) Problem (class in energnn.problem) ProblemBatch (class in energnn.problem) ProblemDataset (class in energnn.problem) ProblemLoader (class in energnn.problem) ProblemMetadata (class in energnn.problem) Q quantiles() (Graph method) (JaxGraph method) R RecurrentCoupler (class in energnn.model.coupler) run_evaluation() (Trainer method) S save_checkpoint() (Trainer method) separate_graphs() (in module energnn.graph) separate_hyper_edge_sets() (in module energnn.graph) separate_shapes() (in module energnn.graph) SmallRecurrentEquivariantGNN (class in energnn.model.ready_to_use) sum() (GraphShape class method) sum_shapes() (in module energnn.graph) SumInvariantDecoder (class in energnn.model.decoder) T TDigestNormalizer (class in energnn.model.normalizer) TinyRecurrentEquivariantGNN (class in energnn.model.ready_to_use) to_json() (ProblemDataset method) to_jsonable_dict() (GraphShape method) to_numpy() (in module energnn.graph) to_numpy_graph() (JaxGraph method) to_numpy_hyper_edge_set() (JaxHyperEdgeSet method) to_numpy_shape() (JaxGraphShape method) to_pickle() (Graph method) (ProblemDataset method) train() (Trainer method) Trainer (class in energnn.trainer) tree_flatten() (JaxGraph method) (JaxGraphShape method) (JaxHyperEdgeSet method) tree_unflatten() (JaxGraph class method) (JaxGraphShape class method) (JaxHyperEdgeSet class method) U unpad() (Graph method) (HyperEdgeSet method)