gw.training.train_pipeline.prepare_training_new

gw.training.train_pipeline.prepare_training_new(
    train_settings,
    train_dir,
    local_settings,
)

Based on a settings dictionary, initialize a WaveformDataset and PosteriorModel.

For model type ‘nsf+embedding’ (the only acceptable type at this point) this also initializes the embedding network projection stage with SVD V matrices based on clean detector waveforms.

Parameters

Name	Type	Description	Default
train_settings	dict	Settings which ultimately come from train_settings.yaml file.	required
train_dir	str	This is only used to save diagnostics from the SVD.	required
local_settings	dict	Local settings (e.g., num_workers, device)	required

Returns

Name	Type	Description
	(BasePosteriorModel, WaveformDataset)