parameters: (weight_column=None,
                                                    label_dimension=1,
                                                    name=None)
return_statement: return _RegressionHeadWithMeanSquaredErrorLoss(
        weight_column=weight_column,
        label_dimension=label_dimension,
        name=name)
docstring: Creates a `_Head` for regression using the mean squared loss.
  
    Args:
      weight_column: A string or a `_NumericColumn` created by
        `tf.feature_column.numeric_column` defining feature column 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]`).
      name: name of the head. If provided, summary and metrics keys will be
        suffixed by `"/" + name`. Also used as `name_scope` when creating ops.
  
    Returns:
      An instance of `_Head` for linear regression.
docstring_summary: Creates a `_Head` for regression using the mean squared loss.
docstring_tokens: Creates a _Head for regression using the mean squared loss .
function: def _regression_head_with_mean_squared_error_loss(weight_column=None,
                                                    label_dimension=1,
                                                    name=None):
    """Creates a `_Head` for regression using the mean squared loss.
  
    Args:
      weight_column: A string or a `_NumericColumn` created by
        `tf.feature_column.numeric_column` defining feature column 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]`).
      name: name of the head. If provided, summary and metrics keys will be
        suffixed by `"/" + name`. Also used as `name_scope` when creating ops.
  
    Returns:
      An instance of `_Head` for linear regression.
    """
    return _RegressionHeadWithMeanSquaredErrorLoss(
        weight_column=weight_column,
        label_dimension=label_dimension,
        name=name)
function_tokens: def _regression_head_with_mean_squared_error_loss ( weight_column = None , label_dimension = 1 , name = None ) : return _RegressionHeadWithMeanSquaredErrorLoss ( weight_column = weight_column , label_dimension = label_dimension , name = name )