def __init__()

in adanet/autoensemble/estimator.py [0:0]

• 56 lines of code
• 1 McCabe index (conditional complexity)

  def __init__(self,
               head,
               candidate_pool,
               max_iteration_steps,
               ensemblers=None,
               ensemble_strategies=None,
               logits_fn=None,
               last_layer_fn=None,
               evaluator=None,
               metric_fn=None,
               force_grow=False,
               adanet_loss_decay=.9,
               model_dir=None,
               config=None,
               use_tpu=True,
               eval_on_tpu=True,
               export_to_tpu=True,
               train_batch_size=None,
               eval_batch_size=None,
               predict_batch_size=None,
               embedding_config_spec=None,
               debug=False,
               enable_ensemble_summaries=True,
               enable_subnetwork_summaries=True,
               global_step_combiner_fn=tf.math.reduce_mean,
               max_iterations=None,
               replay_config=None,
               **kwargs):
    subnetwork_generator = _GeneratorFromCandidatePool(candidate_pool,
                                                       logits_fn, last_layer_fn)
    super(AutoEnsembleTPUEstimator, self).__init__(
        head=head,
        subnetwork_generator=subnetwork_generator,
        max_iteration_steps=max_iteration_steps,
        ensemblers=ensemblers,
        ensemble_strategies=ensemble_strategies,
        evaluator=evaluator,
        metric_fn=metric_fn,
        force_grow=force_grow,
        adanet_loss_decay=adanet_loss_decay,
        model_dir=model_dir,
        config=config,
        use_tpu=use_tpu,
        eval_on_tpu=eval_on_tpu,
        export_to_tpu=export_to_tpu,
        train_batch_size=train_batch_size,
        eval_batch_size=eval_batch_size,
        predict_batch_size=predict_batch_size,
        embedding_config_spec=embedding_config_spec,
        debug=debug,
        enable_ensemble_summaries=enable_ensemble_summaries,
        enable_subnetwork_summaries=enable_subnetwork_summaries,
        global_step_combiner_fn=global_step_combiner_fn,
        max_iterations=max_iterations,
        replay_config=replay_config,
        **kwargs)