bacpipe.embedding_evaluation.probing.probe

Functions

embeds_array_without_noise(embeds, ...)
eval_probe(probe, embeds, df, label2index[, ...])	Perform inference using probe.
generate_annotations_for_probing_task(...[, ...])
prepare_probe_inference(model[, probe_path])
probing_pipeline(model_name, ground_truth, ...)	Probing pipeline consisting of building the classifier, evaluating it and saving metrics and plots of performance.
run_probe_inference(model, linear_probe, ...)
train_probe(embeds, df, label2index[, ...])	Classification pipeline.

Classes

LinearProbe(in_dim, out_dim[, device])
Path(*args, **kwargs)	PurePath subclass that can make system calls.

bacpipe.embedding_evaluation.probing.probe.embeds_array_without_noise(embeds, ground_truth, label_column, **kwargs)

bacpipe.embedding_evaluation.probing.probe.prepare_probe_inference(model, probe_path='')

bacpipe.embedding_evaluation.probing.probe.probing_pipeline(model_name, ground_truth, embeds, paths=None, name='linear', overwrite=True, label_column='species', **kwargs)

Probing pipeline consisting of building the classifier, evaluating it and saving metrics and plots of performance.

Parameters:

• paths (SimpleNamespace object) – dict with attributes corresponding to paths for loading and saving

• embeds (np.array) – embeddings

• name (string) – Type of Probing

• dataset_csv_path (string) – name of Probing dataframe as specified in settings.yaml

• overwrite (bool) – overwrite existing Probing?, defaults to False

bacpipe.embedding_evaluation.probing.probe.run_probe_inference(model, linear_probe, threshold, embeds=None, return_binary_presence=True, callbacks=None)