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machinable

A modular configuration system for machine learning research

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deviation: 0.5
components:
    - baseline_model:
        learning_rate: base_learning_rate(2**-7)
        distribution:
          name: normal
          sigma: $.deviation
          mu: 0
        ~heavytailed:
          distribution:
            name: lognormal
            sigma: 1.0
    - biased_model^baseline_model:
        distribution:
          # overwrite mean to introduces some bias
          mu: -0.5
        control_variate: True
    - +.kaggle.sota_model:
        control_variate: True
experiment = Experiment().component('biased_model', 
                        [('~heavytailed', {'learning_rate': lr}) 
                        for lr in (0.25, 0.1, 0.5)]).repeat(3)

execute(
    experiment, 
    storage='s3://bucket/results', 
    engine='ray'
)