parameters: (input_fn)
docstring: Creates `FeatureColumn` objects for inputs defined by `input_fn`.
  
    This interprets all inputs as dense, fixed-length float values. This creates
    a local graph in which it calls `input_fn` to build the tensors, then discards
    it.
  
    Args:
      input_fn: Function returning a tuple of input and target `Tensor` objects.
  
    Returns:
      List of `FeatureColumn` objects.
docstring_summary: Creates `FeatureColumn` objects for inputs defined by `input_fn`.
docstring_tokens: Creates FeatureColumn objects for inputs defined by input_fn .
function: def infer_real_valued_columns_from_input_fn(input_fn):
    """Creates `FeatureColumn` objects for inputs defined by `input_fn`.
  
    This interprets all inputs as dense, fixed-length float values. This creates
    a local graph in which it calls `input_fn` to build the tensors, then discards
    it.
  
    Args:
      input_fn: Function returning a tuple of input and target `Tensor` objects.
  
    Returns:
      List of `FeatureColumn` objects.
    """
    with ops.Graph().as_default():
      features, _ = input_fn()
      return layers.infer_real_valued_columns(features)
function_tokens: def infer_real_valued_columns_from_input_fn ( input_fn ) : with ops . Graph ( ) . as_default ( ) : features , _ = input_fn ( ) return layers . infer_real_valued_columns ( features )