parameters: (examples, unused_features, predictions)
return_statement: return default_signature, {}
docstring: Creates regression signature from given examples and predictions.
  
    Args:
      examples: `Tensor`.
      unused_features: `dict` of `Tensor`s.
      predictions: `Tensor`.
  
    Returns:
      Tuple of default regression signature and empty named signatures.
  
    Raises:
      ValueError: If examples is `None`.
docstring_summary: Creates regression signature from given examples and predictions.
docstring_tokens: Creates regression signature from given examples and predictions .
function: def regression_signature_fn(examples, unused_features, predictions):
    """Creates regression signature from given examples and predictions.
  
    Args:
      examples: `Tensor`.
      unused_features: `dict` of `Tensor`s.
      predictions: `Tensor`.
  
    Returns:
      Tuple of default regression signature and empty named signatures.
  
    Raises:
      ValueError: If examples is `None`.
    """
    if examples is None:
      raise ValueError('examples cannot be None when using this signature fn.')
  
    default_signature = exporter.regression_signature(
        input_tensor=examples, output_tensor=predictions)
    return default_signature, {}
function_tokens: def regression_signature_fn ( examples , unused_features , predictions ) : if examples is None : raise ValueError ( 'examples cannot be None when using this signature fn.' ) default_signature = exporter . regression_signature ( input_tensor = examples , output_tensor = predictions ) return default_signature , { }