Index _ | A | B | C | D | E | F | G | H | I | L | M | N | O | P | R | S | T | U | V | W | X | Z _ __init__() (vak.config.config.Config method) (vak.config.dataset.DatasetConfig method) (vak.config.eval.EvalConfig method) (vak.config.learncurve.LearncurveConfig method) (vak.config.model.ModelConfig method) (vak.config.predict.PredictConfig method) (vak.config.prep.PrepConfig method) (vak.config.spect_params.SpectParamsConfig method) (vak.config.train.TrainConfig method) (vak.config.trainer.TrainerConfig method) (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe method) (vak.datapipes.frame_classification.metadata.Metadata method) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe method) (vak.datapipes.parametric_umap.metadata.Metadata method) (vak.datapipes.parametric_umap.parametric_umap.Datapipe method) (vak.metrics.classification.classification.Accuracy method) (vak.metrics.distance.distance.CharacterErrorRate method) (vak.metrics.distance.distance.Levenshtein method) (vak.models.definition.ModelDefinition method) (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAP method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) (vak.predict.frame_classification.AnnotationDataFrame method) (vak.prep.frame_classification.learncurve.Sample method) (vak.prep.frame_classification.make_splits.Sample method) (vak.prep.unit_dataset.unit_dataset.Segment method) (vak.prep.unit_dataset.unit_dataset.SpectToSave method) (vak.transforms.defaults.frame_classification.InferItemTransform method) (vak.transforms.defaults.frame_classification.TrainItemTransform method) (vak.transforms.frame_labels.transforms.FromSegments method) (vak.transforms.frame_labels.transforms.PostProcess method) (vak.transforms.frame_labels.transforms.ToLabels method) (vak.transforms.frame_labels.transforms.ToSegments method) (vak.transforms.transforms.AddChannel method) (vak.transforms.transforms.FramesStandardizer method) (vak.transforms.transforms.PadToWindow method) (vak.transforms.transforms.ToFloatTensor method) (vak.transforms.transforms.ToLongTensor method) (vak.transforms.transforms.ViewAsWindowBatch method) A abspath() (in module vak.prep.unit_dataset.unit_dataset) accelerator (vak.config.trainer.TrainerConfig attribute) Accuracy (class in vak.metrics.classification.classification) accuracy() (in module vak.metrics.classification.functional) add_channel() (in module vak.transforms.functional) add_module() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) add_split_col() (in module vak.prep.dataset_df_helper) AddChannel (class in vak.transforms.transforms) all_gather() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) allow_zero_length_dataloader_with_multiple_devices (vak.models.parametric_umap_model.ParametricUMAPDatamodule attribute) annot_file (vak.config.prep.PrepConfig attribute), [1] annot_format (vak.config.prep.PrepConfig attribute), [1] annotation() (in module vak.plot.annot) AnnotationDataFrame (class in vak.predict.frame_classification) apply() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) are_keys_valid() (in module vak.config.validators) are_table_keys_valid() (in module vak.config.validators) are_tables_valid() (in module vak.config.validators) are_valid_dask_bag_kwargs() (in module vak.config.prep) are_valid_post_tfm_kwargs() (in module vak.config.eval) argsort_by_label_freq() (in module vak.prep.frame_classification.make_splits) asdict() (vak.config.dataset.DatasetConfig method) (vak.config.model.ModelConfig method) (vak.config.trainer.TrainerConfig method) audio_dask_bag_kwargs (vak.config.prep.PrepConfig attribute), [1] audio_filename_from_path() (in module vak.common.annotation) audio_format (vak.config.prep.PrepConfig attribute), [1] (vak.datapipes.parametric_umap.metadata.Metadata attribute) audio_path_key (vak.config.spect_params.SpectParamsConfig attribute), [1] AudioFilenameNotFoundError automatic_optimization (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) B background_label (vak.transforms.frame_labels.transforms.FromSegments attribute) (vak.transforms.frame_labels.transforms.PostProcess attribute) backward() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) batch_size (vak.config.eval.EvalConfig attribute), [1] (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] bfloat16() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) bool_from_str() (in module vak.common.converters) boundary_inds_from_boundary_labels() (in module vak.transforms.frame_labels.functional) brute_force() (in module vak.prep.split.algorithms.bruteforce) buffers() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) butter_bandpass() (in module vak.prep.spectrogram_dataset.spect) butter_bandpass_filter() (in module vak.prep.spectrogram_dataset.spect) C character_error_rate() (in module vak.metrics.distance.functional) CharacterErrorRate (class in vak.metrics.distance.distance) checkpoint_path (vak.config.eval.EvalConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] children() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) ckpt_step (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] cli() (in module vak.cli.cli) clip_gradients() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) cnn (vak.nets.tweetynet.TweetyNet attribute) column_or_1d() (in module vak.common.validators) compile() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) compute_cross_entropy() (in module vak.nn.loss.umap) Config (class in vak.config.config), [1] config_logging_for_cli() (in module vak.common.logging) configure_callbacks() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) configure_gradient_clipping() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) configure_model() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) configure_optimizers() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) configure_sharded_model() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) ConvEncoder (class in vak.nets.conv_encoder) convert_distance_to_probability() (in module vak.nn.loss.umap) convert_post_tfm_kwargs() (in module vak.config.eval) cpu() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) CrossEntropyLoss (class in vak.nn.loss.crossentropy) cuda() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) current_epoch (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) D data_dir (vak.config.prep.PrepConfig attribute), [1] Datapipe (class in vak.datapipes.parametric_umap.parametric_umap) dataset (vak.config.eval.EvalConfig attribute), [1] (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] dataset_csv_filename (vak.datapipes.frame_classification.metadata.Metadata attribute) (vak.datapipes.parametric_umap.metadata.Metadata attribute) dataset_df (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) dataset_path (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) dataset_type (vak.config.prep.PrepConfig attribute), [1] DatasetConfig (class in vak.config.dataset) devices (vak.config.trainer.TrainerConfig attribute) dice_loss() (in module vak.nn.loss.dice) DiceLoss (class in vak.nn.loss.dice) double() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) duration_from_toml_value() (in module vak.config.prep) E ED_TCN (class in vak.nets.ed_tcn) eval (vak.config.config.Config attribute), [1] eval() (in module vak.cli.cli) (in module vak.cli.eval) (in module vak.eval.eval_) (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) eval_frame_classification_model() (in module vak.eval.frame_classification) eval_labelmap (vak.models.frame_classification_model.FrameClassificationModel attribute) eval_parametric_umap_model() (in module vak.eval.parametric_umap) EvalConfig (class in vak.config.eval), [1] events2df() (in module vak.common.tensorboard) example_input_array (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) expanded_user_path() (in module vak.common.converters) extra_repr() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) F fc (vak.nets.tweetynet.TweetyNet attribute) fft_size (vak.config.spect_params.SpectParamsConfig attribute), [1] files_from_dir() (in module vak.common.annotation) (in module vak.prep.spectrogram_dataset.audio_helper) find_audio_fname() (in module vak.common.files.spect) find_fname() (in module vak.common.files.files) fit() (vak.transforms.transforms.FramesStandardizer class method) fit_dataset_path() (vak.transforms.transforms.FramesStandardizer class method) fit_learning_curve() (in module vak.learncurve.curvefit) float() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) format_from_df() (in module vak.common.annotation) forward() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) frame_classification_dataframe() (in module vak.prep.split.split) frame_dur (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.metadata.Metadata attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) frame_error_rate() (in module vak.plot.learncurve) frame_labels_npy_path (vak.prep.frame_classification.make_splits.Sample attribute) frame_labels_padval (vak.transforms.defaults.frame_classification.InferItemTransform attribute) frame_labels_paths (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) frame_paths (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) FrameClassificationModel (class in vak.models.frame_classification_model) frames_padval (vak.transforms.defaults.frame_classification.InferItemTransform attribute) frames_path (vak.prep.frame_classification.make_splits.Sample attribute) frames_paths (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) frames_standardizer (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute), [1] (vak.transforms.defaults.frame_classification.InferItemTransform attribute) frames_standardizer_path (vak.config.eval.EvalConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] FramesStandardizer (class in vak.transforms.transforms) freeze() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) freq_cutoffs (vak.config.spect_params.SpectParamsConfig attribute), [1] freq_cutoffs_validator() (in module vak.config.spect_params) freqbins_key (vak.config.spect_params.SpectParamsConfig attribute), [1] from_config_dict() (vak.config.config.Config class method) (vak.config.eval.EvalConfig class method) (vak.config.learncurve.LearncurveConfig class method) (vak.config.model.ModelConfig class method) (vak.config.predict.PredictConfig class method) (vak.config.prep.PrepConfig class method) (vak.config.train.TrainConfig class method) from_dataset_path() (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe class method) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe class method) (vak.datapipes.parametric_umap.parametric_umap.Datapipe class method) from_datasets() (vak.models.parametric_umap_model.ParametricUMAPDatamodule class method) from_df() (in module vak.common.annotation) (in module vak.common.labels) from_dir() (in module vak.common.files.files) from_path() (vak.datapipes.frame_classification.metadata.Metadata class method) (vak.datapipes.parametric_umap.metadata.Metadata class method) from_segments() (in module vak.transforms.frame_labels.functional) from_toml_path() (vak.config.config.Config class method) FromSegments (class in vak.transforms.frame_labels.transforms) G generate_results_dir_name_as_path() (in module vak.common.paths) get_all_results_list() (in module vak.plot.learncurve) get_buffer() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) get_dataset_csv_filename() (in module vak.prep.dataset_df_helper) get_dataset_csv_path() (in module vak.prep.dataset_df_helper) get_default() (in module vak.common.accelerator) get_default_train_callbacks() (in module vak.common.trainer) get_default_trainer() (in module vak.common.trainer) get_extra_state() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) get_graph_elements() (in module vak.datapipes.parametric_umap.parametric_umap) get_or_make_source_files() (in module vak.prep.frame_classification.source_files) get_parameter() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) get_split_dur() (in module vak.train.frame_classification) (in module vak.train.parametric_umap) get_submodule() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) get_summary_writer() (in module vak.common.tensorboard) get_timenow_as_str() (in module vak.common.timenow) get_train_dur_replicate_subset_name() (in module vak.common.learncurve) get_trainer() (in module vak.train.parametric_umap) get_umap_graph() (in module vak.datapipes.parametric_umap.parametric_umap) get_window_inds() (in module vak.datapipes.frame_classification.train_datapipe) global_rank (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) global_step (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) H half() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) has_unlabeled() (in module vak.common.annotation) has_unlabeled_segments() (in module vak.prep.sequence_dataset) hparams (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPDatamodule property) (vak.models.parametric_umap_model.ParametricUMAPModel property) hparams_initial (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPDatamodule property) (vak.models.parametric_umap_model.ParametricUMAPModel property) I inds_in_sample (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) inds_in_sample_array_filename_for_subset() (in module vak.datapipes.frame_classification.helper) inds_in_sample_vec (vak.prep.frame_classification.make_splits.Sample attribute) InferDatapipe (class in vak.datapipes.frame_classification.infer_datapipe) InferItemTransform (class in vak.transforms.defaults.frame_classification) input_shape (vak.nets.tweetynet.TweetyNet attribute) input_type (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.metadata.Metadata attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) ipu() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) is_a_directory() (in module vak.common.validators) (in module vak.config.validators) is_a_file() (in module vak.common.validators) (in module vak.config.validators) is_annot_format() (in module vak.config.validators) is_audio_format() (in module vak.config.validators) is_spect_format() (in module vak.config.validators) is_valid_accelerator() (in module vak.config.trainer) is_valid_audio_format() (in module vak.datapipes.frame_classification.metadata) (in module vak.datapipes.parametric_umap.metadata) is_valid_dataset_csv_filename() (in module vak.datapipes.frame_classification.metadata) (in module vak.datapipes.parametric_umap.metadata) is_valid_devices() (in module vak.config.trainer) is_valid_duration() (in module vak.config.prep) is_valid_model_name() (in module vak.config.validators) is_valid_set_of_spect_files() (in module vak.common.files.spect) is_valid_spect_format() (in module vak.datapipes.frame_classification.metadata) (in module vak.datapipes.parametric_umap.metadata) is_valid_transform_type() (in module vak.config.spect_params) L labelmap (vak.models.frame_classification_model.FrameClassificationModel attribute) (vak.transforms.frame_labels.transforms.ToLabels attribute) (vak.transforms.frame_labels.transforms.ToSegments attribute) labelmap_path (vak.config.eval.EvalConfig attribute), [1] labelset (vak.config.prep.PrepConfig attribute), [1] labelset_to_set() (in module vak.common.converters) learncurve (vak.config.config.Config attribute), [1] learncurve() (in module vak.cli.cli) LearncurveConfig (class in vak.config.learncurve), [1] learning_curve() (in module vak.cli.learncurve) (in module vak.learncurve.learncurve) learning_curve_for_frame_classification_model() (in module vak.learncurve.frame_classification) Levenshtein (class in vak.metrics.distance.distance) levenshtein() (in module vak.metrics.distance.functional) load() (in module vak.common.files.spect) load_frames() (in module vak.datapipes.frame_classification.helper) load_from_checkpoint() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) load_state_dict() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) load_state_dict_from_path() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) local_rank (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) log() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) log_dict() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) log_version() (in module vak.common.logging) logger (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) loggers (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) loss (vak.config.model.ModelConfig attribute) (vak.models.frame_classification_model.FrameClassificationModel attribute) lr_scheduler_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) lr_schedulers() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) M majority_vote (vak.transforms.frame_labels.transforms.PostProcess attribute) make_dataframe_of_spect_files() (in module vak.prep.spectrogram_dataset.spect_helper) make_index_vectors_for_each_subset() (in module vak.prep.frame_classification.learncurve) make_spectrogram_files_from_audio_files() (in module vak.prep.spectrogram_dataset.audio_helper) make_splits() (in module vak.prep.frame_classification.make_splits) make_subsets_from_dataset_df() (in module vak.prep.frame_classification.learncurve) manual_backward() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) map_annotated_to_annot() (in module vak.common.annotation) MapUsingExtensionError MapUsingNotatedPathError mean_freqs (vak.transforms.transforms.FramesStandardizer attribute) Metadata (class in vak.datapipes.frame_classification.metadata) (class in vak.datapipes.parametric_umap.metadata) metrics (vak.config.model.ModelConfig attribute) (vak.models.frame_classification_model.FrameClassificationModel attribute) min_segment_dur (vak.transforms.frame_labels.transforms.PostProcess attribute) model (vak.config.eval.EvalConfig attribute), [1] (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] model() (in module vak.models.decorator) model_family() (in module vak.models.registry) ModelConfig (class in vak.config.model) ModelDefinition (class in vak.models.definition) ModelDefinitionValidationError module vak vak.cli.cli vak.cli.eval vak.cli.learncurve vak.cli.predict vak.cli.prep vak.cli.train vak.common.accelerator vak.common.annotation vak.common.constants vak.common.converters vak.common.files vak.common.files.files vak.common.files.spect vak.common.labels vak.common.learncurve vak.common.logging vak.common.paths vak.common.tensorboard vak.common.timebins vak.common.timenow vak.common.trainer vak.common.typing vak.common.validators vak.config.config vak.config.dataset vak.config.eval vak.config.learncurve vak.config.load vak.config.model vak.config.predict vak.config.prep vak.config.spect_params vak.config.train vak.config.trainer vak.config.validators vak.datapipes.frame_classification vak.datapipes.frame_classification.constants vak.datapipes.frame_classification.helper vak.datapipes.frame_classification.infer_datapipe vak.datapipes.frame_classification.metadata vak.datapipes.frame_classification.train_datapipe vak.datapipes.parametric_umap vak.datapipes.parametric_umap.metadata vak.datapipes.parametric_umap.parametric_umap vak.eval.eval_ vak.eval.frame_classification vak.eval.parametric_umap vak.learncurve.curvefit vak.learncurve.dirname vak.learncurve.frame_classification vak.learncurve.learncurve vak.metrics.classification.classification vak.metrics.classification.functional vak.metrics.distance.distance vak.metrics.distance.functional vak.models.convencoder_umap vak.models.decorator vak.models.definition vak.models.ed_tcn vak.models.frame_classification_model vak.models.get vak.models.parametric_umap_model vak.models.registry vak.models.tweetynet vak.nets.conv_encoder vak.nets.ed_tcn vak.nets.tweetynet vak.nn.functional vak.nn.loss vak.nn.loss.crossentropy vak.nn.loss.dice vak.nn.loss.umap vak.plot.annot vak.plot.learncurve vak.plot.spect vak.predict.frame_classification vak.predict.parametric_umap vak.predict.predict_ vak.prep vak.prep.audio_dataset vak.prep.constants vak.prep.dataset_df_helper vak.prep.frame_classification vak.prep.frame_classification.assign_samples_to_splits vak.prep.frame_classification.frame_classification vak.prep.frame_classification.learncurve vak.prep.frame_classification.make_splits vak.prep.frame_classification.source_files vak.prep.frame_classification.validators vak.prep.parametric_umap vak.prep.parametric_umap.dataset_arrays vak.prep.parametric_umap.parametric_umap vak.prep.prep_ vak.prep.sequence_dataset vak.prep.spectrogram_dataset vak.prep.spectrogram_dataset.audio_helper vak.prep.spectrogram_dataset.prep vak.prep.spectrogram_dataset.spect vak.prep.spectrogram_dataset.spect_helper vak.prep.split vak.prep.split.algorithms vak.prep.split.algorithms.bruteforce vak.prep.split.algorithms.validate vak.prep.split.split vak.prep.unit_dataset vak.prep.unit_dataset.unit_dataset vak.train.frame_classification vak.train.parametric_umap vak.train.train_ vak.transforms.defaults vak.transforms.defaults.frame_classification vak.transforms.frame_labels.functional vak.transforms.frame_labels.transforms vak.transforms.functional vak.transforms.transforms modules() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) move_files_into_split_subdirs() (in module vak.prep.parametric_umap.dataset_arrays) multi_char_labels_to_single_char() (in module vak.common.labels) N n_decimals_trunc (vak.transforms.frame_labels.transforms.ToSegments attribute) name (vak.config.dataset.DatasetConfig attribute) (vak.config.model.ModelConfig attribute) named_buffers() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) named_children() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) named_modules() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) named_parameters() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) network (vak.config.model.ModelConfig attribute) (vak.models.frame_classification_model.FrameClassificationModel attribute) non_zero_std (vak.transforms.transforms.FramesStandardizer attribute) num_classes (vak.nets.tweetynet.TweetyNet attribute) num_epochs (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] num_replicates (vak.config.prep.PrepConfig attribute), [1] num_workers (vak.config.eval.EvalConfig attribute), [1] (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] O on_after_backward() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_after_batch_transfer() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_before_backward() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_before_batch_transfer() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_before_optimizer_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_before_zero_grad() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_fit_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_fit_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_gpu (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) on_load_checkpoint() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_batch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_batch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_epoch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_epoch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_model_eval() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_predict_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_save_checkpoint() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_batch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_batch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_epoch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_epoch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_model_eval() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_model_train() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_test_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_train_batch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_train_batch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_train_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_train_epoch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_train_epoch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_train_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_batch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_batch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_epoch_end() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_epoch_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_model_eval() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_model_train() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_model_zero_grad() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) on_validation_start() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) one_hot() (in module vak.nn.functional) optimizer (vak.config.model.ModelConfig attribute) (vak.models.frame_classification_model.FrameClassificationModel attribute) optimizer_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) optimizer_zero_grad() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) optimizers() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) output_dir (vak.config.eval.EvalConfig attribute), [1] (vak.config.prep.PrepConfig attribute), [1] P pad_to_window() (in module vak.transforms.functional) PadToWindow (class in vak.transforms.transforms) parameters() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) ParametricUMAP (class in vak.models.parametric_umap_model) ParametricUMAPDatamodule (class in vak.models.parametric_umap_model) ParametricUMAPModel (class in vak.models.parametric_umap_model) params (vak.config.dataset.DatasetConfig attribute) path (vak.config.dataset.DatasetConfig attribute) patience (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] plot_labels() (in module vak.plot.annot) plot_segments() (in module vak.plot.annot) post_tfm (vak.models.frame_classification_model.FrameClassificationModel attribute) post_tfm_kwargs (vak.config.eval.EvalConfig attribute), [1] (vak.config.learncurve.LearncurveConfig attribute), [1] PostProcess (class in vak.transforms.frame_labels.transforms) postprocess() (in module vak.transforms.frame_labels.functional) predict (vak.config.config.Config attribute), [1] predict() (in module vak.cli.cli) (in module vak.cli.predict) (in module vak.predict.predict_) predict_dataloader() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) predict_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) predict_with_frame_classification_model() (in module vak.predict.frame_classification) predict_with_parametric_umap_model() (in module vak.predict.parametric_umap) PredictConfig (class in vak.config.predict), [1] prep (vak.config.config.Config attribute), [1] prep() (in module vak.cli.cli) (in module vak.cli.prep) (in module vak.prep.prep_) prep_audio_dataset() (in module vak.prep.audio_dataset) prep_frame_classification_dataset() (in module vak.prep.frame_classification.frame_classification) prep_parametric_umap_dataset() (in module vak.prep.parametric_umap.parametric_umap) prep_spectrogram_dataset() (in module vak.prep.spectrogram_dataset.prep) prep_unit_dataset() (in module vak.prep.unit_dataset.unit_dataset) prepare_data() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) prepare_data_per_node (vak.models.parametric_umap_model.ParametricUMAPDatamodule attribute), [1] PrepConfig (class in vak.config.prep), [1] print() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) purpose_from_toml() (in module vak.cli.prep) R range_str() (in module vak.common.converters) register_backward_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_buffer() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_forward_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_forward_pre_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_full_backward_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_full_backward_pre_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_load_state_dict_post_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_model() (in module vak.models.registry) register_module() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_parameter() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) register_state_dict_pre_hook() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) remove_short_segments() (in module vak.transforms.frame_labels.functional) replicate_dirname() (in module vak.learncurve.dirname) requires_grad_() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) residual_two_functions() (in module vak.learncurve.curvefit) return_padding_mask (vak.transforms.defaults.frame_classification.InferItemTransform attribute) rnn (vak.nets.tweetynet.TweetyNet attribute) rnn_input_size (vak.nets.tweetynet.TweetyNet attribute) root_results_dir (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] row_or_1d() (in module vak.common.validators) S Sample (class in vak.prep.frame_classification.learncurve) (class in vak.prep.frame_classification.make_splits) sample_id_vec (vak.prep.frame_classification.make_splits.Sample attribute) sample_ids (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) sample_ids_array_filename_for_subset() (in module vak.datapipes.frame_classification.helper) save_hyperparameters() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) save_spect() (in module vak.prep.unit_dataset.unit_dataset) Segment (class in vak.prep.unit_dataset.unit_dataset) segment_inds_list_from_boundary_labels() (in module vak.transforms.frame_labels.functional) segment_inds_list_from_class_labels() (in module vak.transforms.frame_labels.functional) set_extra_state() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) setup() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) share_memory() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) shuffle (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] source_id (vak.prep.frame_classification.make_splits.Sample attribute) spect_format (vak.config.prep.PrepConfig attribute), [1] spect_key (vak.config.spect_params.SpectParamsConfig attribute), [1] spect_params (vak.config.prep.PrepConfig attribute), [1] SpectParamsConfig (class in vak.config.spect_params), [1] spectrogram() (in module vak.prep.spectrogram_dataset.spect) spectrogram_from_segment() (in module vak.prep.unit_dataset.unit_dataset) SpectToSave (class in vak.prep.unit_dataset.unit_dataset) split (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) splits_path (vak.config.dataset.DatasetConfig attribute) standardize_frames (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] standardize_spect() (in module vak.transforms.functional) state_dict() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) std_freqs (vak.transforms.transforms.FramesStandardizer attribute) step_size (vak.config.spect_params.SpectParamsConfig attribute), [1] strict_loading (vak.models.frame_classification_model.FrameClassificationModel property) (vak.models.parametric_umap_model.ParametricUMAPModel property) stride (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) subset (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) syllable_error_rate() (in module vak.plot.learncurve) T take_majority_vote() (in module vak.transforms.frame_labels.functional) teardown() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) test_dataloader() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) test_dur (vak.config.prep.PrepConfig attribute), [1] test_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) thresh (vak.config.spect_params.SpectParamsConfig attribute), [1] timebin_dur (vak.transforms.frame_labels.transforms.PostProcess attribute) timebin_dur() (in module vak.common.files.spect) timebin_dur_from_vec() (in module vak.common.timebins) timebins_key (vak.config.spect_params.SpectParamsConfig attribute), [1] to() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) to_empty() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) to_floattensor() (in module vak.transforms.functional) to_json() (vak.datapipes.frame_classification.metadata.Metadata method) (vak.datapipes.parametric_umap.metadata.Metadata method) to_labels() (in module vak.transforms.frame_labels.functional) to_labels_eval (vak.models.frame_classification_model.FrameClassificationModel attribute) to_longtensor() (in module vak.transforms.functional) to_map() (in module vak.common.labels) to_onnx() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) to_segments() (in module vak.transforms.frame_labels.functional) to_set() (in module vak.common.labels) to_torchscript() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) ToFloatTensor (class in vak.transforms.transforms) toggle_optimizer() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) ToLabels (class in vak.transforms.frame_labels.transforms) ToLongTensor (class in vak.transforms.transforms) ToSegments (class in vak.transforms.frame_labels.transforms) train (vak.config.config.Config attribute), [1] train() (in module vak.cli.cli) (in module vak.cli.train) (in module vak.train.train_) (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) train_dataloader() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) train_dur (vak.config.prep.PrepConfig attribute), [1] train_dur_dirname() (in module vak.learncurve.dirname) train_frame_classification_model() (in module vak.train.frame_classification) train_parametric_umap_model() (in module vak.train.parametric_umap) train_set_durs (vak.config.prep.PrepConfig attribute), [1] train_test_dur_split_inds() (in module vak.prep.split.split) TrainConfig (class in vak.config.train), [1] TrainDatapipe (class in vak.datapipes.frame_classification.train_datapipe) trainer (vak.config.eval.EvalConfig attribute), [1] (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] TrainerConfig (class in vak.config.trainer) training_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) TrainItemTransform (class in vak.transforms.defaults.frame_classification) transfer_batch_to_device() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) transform_type (vak.config.spect_params.SpectParamsConfig attribute), [1] TweetyNet (class in vak.nets.tweetynet) type() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) U umap_loss() (in module vak.nn.loss.umap) UmapLoss (class in vak.nn.loss.umap) unfreeze() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) unique_set_from_labels() (in module vak.prep.split.algorithms.bruteforce) unit_dataframe() (in module vak.prep.split.split) untoggle_optimizer() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) V vak module vak.cli.cli module vak.cli.eval module vak.cli.learncurve module vak.cli.predict module vak.cli.prep module vak.cli.train module vak.common.accelerator module vak.common.annotation module vak.common.constants module vak.common.converters module vak.common.files module vak.common.files.files module vak.common.files.spect module vak.common.labels module vak.common.learncurve module vak.common.logging module vak.common.paths module vak.common.tensorboard module vak.common.timebins module vak.common.timenow module vak.common.trainer module vak.common.typing module vak.common.validators module vak.config.config module vak.config.dataset module vak.config.eval module vak.config.learncurve module vak.config.load module vak.config.model module vak.config.predict module vak.config.prep module vak.config.spect_params module vak.config.train module vak.config.trainer module vak.config.validators module vak.datapipes.frame_classification module vak.datapipes.frame_classification.constants module vak.datapipes.frame_classification.helper module vak.datapipes.frame_classification.infer_datapipe module vak.datapipes.frame_classification.metadata module vak.datapipes.frame_classification.train_datapipe module vak.datapipes.parametric_umap module vak.datapipes.parametric_umap.metadata module vak.datapipes.parametric_umap.parametric_umap module vak.eval.eval_ module vak.eval.frame_classification module vak.eval.parametric_umap module vak.learncurve.curvefit module vak.learncurve.dirname module vak.learncurve.frame_classification module vak.learncurve.learncurve module vak.metrics.classification.classification module vak.metrics.classification.functional module vak.metrics.distance.distance module vak.metrics.distance.functional module vak.models.convencoder_umap module vak.models.decorator module vak.models.definition module vak.models.ed_tcn module vak.models.frame_classification_model module vak.models.get module vak.models.parametric_umap_model module vak.models.registry module vak.models.tweetynet module vak.nets.conv_encoder module vak.nets.ed_tcn module vak.nets.tweetynet module vak.nn.functional module vak.nn.loss module vak.nn.loss.crossentropy module vak.nn.loss.dice module vak.nn.loss.umap module vak.plot.annot module vak.plot.learncurve module vak.plot.spect module vak.predict.frame_classification module vak.predict.parametric_umap module vak.predict.predict_ module vak.prep module vak.prep.audio_dataset module vak.prep.constants module vak.prep.dataset_df_helper module vak.prep.frame_classification module vak.prep.frame_classification.assign_samples_to_splits module vak.prep.frame_classification.frame_classification module vak.prep.frame_classification.learncurve module vak.prep.frame_classification.make_splits module vak.prep.frame_classification.source_files module vak.prep.frame_classification.validators module vak.prep.parametric_umap module vak.prep.parametric_umap.dataset_arrays module vak.prep.parametric_umap.parametric_umap module vak.prep.prep_ module vak.prep.sequence_dataset module vak.prep.spectrogram_dataset module vak.prep.spectrogram_dataset.audio_helper module vak.prep.spectrogram_dataset.prep module vak.prep.spectrogram_dataset.spect module vak.prep.spectrogram_dataset.spect_helper module vak.prep.split module vak.prep.split.algorithms module vak.prep.split.algorithms.bruteforce module vak.prep.split.algorithms.validate module vak.prep.split.split module vak.prep.unit_dataset module vak.prep.unit_dataset.unit_dataset module vak.train.frame_classification module vak.train.parametric_umap module vak.train.train_ module vak.transforms.defaults module vak.transforms.defaults.frame_classification module vak.transforms.frame_labels.functional module vak.transforms.frame_labels.transforms module vak.transforms.functional module vak.transforms.transforms module val_dataloader() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPDatamodule method) (vak.models.parametric_umap_model.ParametricUMAPModel method) val_dur (vak.config.prep.PrepConfig attribute), [1] val_step (vak.config.learncurve.LearncurveConfig attribute), [1] (vak.config.train.TrainConfig attribute), [1] validate() (in module vak.models.definition) validate_and_get_frame_dur() (in module vak.prep.frame_classification.validators) validate_labels() (in module vak.prep.split.algorithms.bruteforce) validate_split_durations() (in module vak.prep.split.algorithms.validate) validation_step() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) view_as_window_batch() (in module vak.transforms.functional) ViewAsWindowBatch (class in vak.transforms.transforms) W where_unlabeled_segments() (in module vak.prep.sequence_dataset) window_inds (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) window_size (vak.datapipes.frame_classification.infer_datapipe.InferDatapipe attribute) (vak.datapipes.frame_classification.train_datapipe.TrainDatapipe attribute) (vak.transforms.defaults.frame_classification.InferItemTransform attribute) X xpu() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method) Z zero_grad() (vak.models.frame_classification_model.FrameClassificationModel method) (vak.models.parametric_umap_model.ParametricUMAPModel method) (vak.nets.conv_encoder.ConvEncoder method) (vak.nets.ed_tcn.ED_TCN method) (vak.nets.tweetynet.TweetyNet method) (vak.nn.loss.crossentropy.CrossEntropyLoss method) (vak.nn.loss.dice.DiceLoss method) (vak.nn.loss.umap.UmapLoss method)