Developer API#

`das.annot`	Utilities for dealing with annotations.
`das.augmentation`	Waveform level augmentations.
`das.block_stratify`	A bit on semantics: - blocks are parts of the data (individual files in a file list, parts of a data array) - individual blocks are assigned specific groups (train/test/val)
`das.data`	Utils for loading and manipulating data for training and prediction.
`das.data_hash`
`das.evaluate`
`das.event_utils`	Utilities for handling events.
`das.io`	Load data for training/testing.
`das.make_dataset`
`das.menagerie`	Utilities for interacting with DAS-Menagerie.
`das.models`	Defines the network architectures.
`das.models_legacy`	Defines the network architectures.
`das.npy_dir`	Dict of dicts <-> hierarchy of npy files.
`das.postprocessing`
`das.predict`	Code for training and evaluating networks.
`das.pulse_utils`	Utilities for handling pulses.
`das.segment_utils`	Segment (syllable) utilities.
`das.spec_utils`
`das.tracking`	Utilities for logging training runs.
`das.train`	Code for training networks.
`das.train_tune`	Code for tuning the hyperparameters of a network.
`das.utils`	General utilities
`das.utils_plot`	Plot utilities.
`das.tcn.tcn`
`das.tcn.tcn_new`
`das.morpholayers.constraints`
`das.morpholayers.initializers`
`das.morpholayers.layers`	References
`das.morpholayers.regularizers`
`das.kapre.augmentation`
`das.kapre.backend`	Kapre backend functions Some backend functions that mainly use numpy. Functions with Keras' backend is in backend_keras.py.
`das.kapre.backend_keras`
`das.kapre.filterbank`
`das.kapre.time_frequency`
`das.kapre.utils`