Index A | B | C | D | E | F | G | I | L | M | P | R | S | T | U | V A apply_rotary_pos_emb() (in module torch_brain.nn) B BINARY (DataType attribute), [1] C chain() (in module torch_brain.data.collate) collate() (in module torch_brain.data.collate) Compose (class in torch_brain.transforms) ConditionalChoice (class in torch_brain.transforms) CONTINUOUS (DataType attribute), [1] create_linspace_latent_tokens() (in module torch_brain.utils) create_start_end_unit_tokens() (in module torch_brain.utils) CrossEntropyLoss (class in torch_brain.nn.loss) D Dataset (class in torch_brain.data.dataset) DatasetIndex (class in torch_brain.data.dataset) DataType (class in torch_brain.registry) detokenizer() (InfiniteVocabEmbedding method) dim (ModalitySpec attribute), [1] disable_data_leakage_check() (Dataset method) DistributedStitchingFixedWindowSampler (class in torch_brain.data.sampler) E Embedding (class in torch_brain.nn) end (DatasetIndex attribute) extend_vocab() (InfiniteVocabEmbedding method) F FeedForward (class in torch_brain.nn) forward() (CrossEntropyLoss method) (FeedForward method) (Loss method) (MallowDistanceLoss method) (MSELoss method) (MultitaskReadout method) (POYO method) (POYOPlus method) (RotaryCrossAttention method) (RotaryEmbedding method) (RotarySelfAttention method) forward_varlen() (MultitaskReadout method) (RotaryCrossAttention method) (RotarySelfAttention method) G get() (Dataset method) get_brainset_ids() (Dataset method) get_modality_by_id() (in module torch_brain.registry) get_recording_config_dict() (Dataset method) get_recording_data() (Dataset method) get_sampling_intervals() (Dataset method) get_session_ids() (Dataset method) get_subject_ids() (Dataset method) get_unit_ids() (Dataset method) I id (ModalitySpec attribute), [1] InfiniteVocabEmbedding (class in torch_brain.nn) initialize_vocab() (InfiniteVocabEmbedding method) is_lazy() (InfiniteVocabEmbedding method) L Loss (class in torch_brain.nn.loss) loss_fn (ModalitySpec attribute), [1] M MallowDistanceLoss (class in torch_brain.nn.loss) ModalitySpec (class in torch_brain.registry) MSELoss (class in torch_brain.nn.loss) MULTILABEL (DataType attribute), [1] MULTINOMIAL (DataType attribute), [1] MultitaskReadout (class in torch_brain.nn) P pad() (in module torch_brain.data.collate) pad8() (in module torch_brain.data.collate) POYO (class in torch_brain.models) POYOPlus (class in torch_brain.models) prepare_for_multitask_readout() (in module torch_brain.nn) proposal_distribution() (TriangleDistribution method) R RandomChoice (class in torch_brain.transforms) RandomFixedWindowSampler (class in torch_brain.data.sampler) RandomOutputSampler (class in torch_brain.transforms) RandomTimeScaling (class in torch_brain.transforms) recording_id (DatasetIndex attribute) register_modality() (in module torch_brain.registry) reset_parameters() (Embedding method) (InfiniteVocabEmbedding method) RotaryCrossAttention (class in torch_brain.nn) RotaryEmbedding (class in torch_brain.nn) RotarySelfAttention (class in torch_brain.nn) S sample() (TriangleDistribution method) SequentialFixedWindowSampler (class in torch_brain.data.sampler) set_epoch() (DistributedStitchingFixedWindowSampler method) SparseLamb (class in torch_brain.optim) start (DatasetIndex attribute) step() (SparseLamb method) subset_vocab() (InfiniteVocabEmbedding method) T timestamp_key (ModalitySpec attribute), [1] tokenize() (POYO method) (POYOPlus method) tokenizer() (InfiniteVocabEmbedding method) track_batch() (in module torch_brain.data.collate) track_mask() (in module torch_brain.data.collate) track_mask8() (in module torch_brain.data.collate) TrialSampler (class in torch_brain.data.sampler) TriangleDistribution (class in torch_brain.transforms) type (ModalitySpec attribute), [1] U UnitDropout (class in torch_brain.transforms) unnormalized_density_function() (TriangleDistribution method) V value_key (ModalitySpec attribute), [1]