def _build_estimator()

in tfx_addons/sampling/example/sampler_utils.py [0:0]

• 10 lines of code
• 3 McCabe index (conditional complexity)

def _build_estimator(config, hidden_units=None, warm_start_from=None):
  """Build an estimator for classifier fraud/not fraud
  Args:
    config: tf.estimator.RunConfig defining the runtime environment for the
      estimator (including model_dir).
    hidden_units: [int], the layer sizes of the DNN (input layer first)
    warm_start_from: Optional directory to warm start from.
  Returns:
    A dict of the following:
      - estimator: The estimator that will be used for training and eval.
      - train_spec: Spec for training.
      - eval_spec: Spec for eval.
      - eval_input_receiver_fn: Input function for eval.
  """
  real_valued_columns = [
      tf.feature_column.numeric_column(key, shape=())
      for key in _transformed_names(_FEATURE_KEYS)
  ]

  return tf.estimator.DNNLinearCombinedClassifier(
      config=config,
      dnn_feature_columns=real_valued_columns,
      dnn_hidden_units=hidden_units or [100, 70, 50, 25],
      warm_start_from=warm_start_from)