head.py 文件源码

def _regression_head(label_name=None,
                     weight_column_name=None,
                     label_dimension=1,
                     enable_centered_bias=False,
                     head_name=None):
  """Creates a _Head for linear regression.

  Args:
    label_name: String, name of the key in label dict. Can be null if label
        is a tensor (single headed models).
    weight_column_name: A string defining feature column name representing
      weights. It is used to down weight or boost examples during training. It
      will be multiplied by the loss of the example.
    label_dimension: Number of regression labels per example. This is the size
      of the last dimension of the labels `Tensor` (typically, this has shape
      `[batch_size, label_dimension]`).
    enable_centered_bias: A bool. If True, estimator will learn a centered
      bias variable for each class. Rest of the model structure learns the
      residual after centered bias.
    head_name: name of the head. If provided, predictions, summary and metrics
      keys will be suffixed by `"/" + head_name` and the default variable scope
      will be `head_name`.

  Returns:
    An instance of _Head
  """
  return _RegressionHead(
      label_name=label_name,
      weight_column_name=weight_column_name,
      label_dimension=label_dimension,
      enable_centered_bias=enable_centered_bias,
      head_name=head_name)


# TODO(zakaria): Add logistic_regression_head