BERNN-MSMS

Minimal README for quick usage.

Longer historical content is kept in LEGACY_README.md.

Install

pip install bernn

Basic usage

from bernn import TrainAEClassifierHoldout

trainer_cls = TrainAEClassifierHoldout
trainer = trainer_cls(config=bernn_config, log_metrics=True, keep_models=False)

# Train and predict in one call
preds_encoded = trainer.fit_predict(
    X_train,
    y_train,
    X_test=X_test,
    y_test=y_test,
    groups_train=batches_train,
    groups_test=batches_test,
    cross_validation=False,
    cross_test=False,
)

# Decode predictions back to original labels
preds = trainer.predict(X_test)

Important runtime contract:

  • groups_train is mandatory.
  • If X_test is provided, groups_test is mandatory.

Important parameters

Focus on these first:

  • optimize_hyperparams: enable/disable Ax optimization.
  • n_trials: number of optimization trials.
  • fixed_hyperparams: force values and remove them from search.
  • n_repeats: number of holdout repeats.
  • n_layers, layer1: classifier depth and width seed.
  • dloss: domain loss mode.
  • warmup, n_epochs: core training schedule.
  • device: cpu/cuda target.
  • scaler, bs: preprocessing and batch size.

Official documentation

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.0.6)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for spell00 from gravatar.com spell00

Credits

Author: Simon Pelletier

License

MIT License (MIT)

Requires

Python >=3.10

Provides Extra

minimal core-extended deep-learning experiment-tracking notebooks tools python311-plus tools-with-ax web web-dev external-tools typing r-integration dev-tools special ml-full analysis analysis-with-ax development modern-web ide-tools python313-ml-minimal python313-ml-stable python313-minimal-safe python313-safe full-no-ax full full-safe py311-plus py312-plus py313-plus

Classifiers

Report project as malware

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