parameters: (name, input_map)
return_statement: return input_map
docstring: Ensures all input map values are tensors.
  
    This should be called from inside the import name scope.
  
    Args:
      name: the `name` argument passed to import_graph_def
      input_map: the `input_map` argument passed to import_graph_def.
  
    Returns:
      An possibly-updated version of `input_map`.
  
    Raises:
      ValueError: if input map values cannot be converted due to empty name scope.
docstring_summary: Ensures all input map values are tensors.
docstring_tokens: Ensures all input map values are tensors .
function: def _ConvertInputMapValues(name, input_map):
    """Ensures all input map values are tensors.
  
    This should be called from inside the import name scope.
  
    Args:
      name: the `name` argument passed to import_graph_def
      input_map: the `input_map` argument passed to import_graph_def.
  
    Returns:
      An possibly-updated version of `input_map`.
  
    Raises:
      ValueError: if input map values cannot be converted due to empty name scope.
    """
    if not all(isinstance(v, ops.Tensor) for v in input_map.values()):
      if name == '':  # pylint: disable=g-explicit-bool-comparison
        raise ValueError(
            'tf.import_graph_def() requires a non-empty `name` if `input_map` '
            'contains non-Tensor values. Try calling tf.convert_to_tensor() on '
            '`input_map` values before calling tf.import_graph_def().')
      with ops.name_scope('_inputs'):
        input_map = {k: ops.convert_to_tensor(v) for k, v in input_map.items()}
    return input_map
function_tokens: def _ConvertInputMapValues ( name , input_map ) : if not all ( isinstance ( v , ops . Tensor ) for v in input_map . values ( ) ) : if name == '' : # pylint: disable=g-explicit-bool-comparison raise ValueError ( 'tf.import_graph_def() requires a non-empty `name` if `input_map` ' 'contains non-Tensor values. Try calling tf.convert_to_tensor() on ' '`input_map` values before calling tf.import_graph_def().' ) with ops . name_scope ( '_inputs' ) : input_map = { k : ops . convert_to_tensor ( v ) for k , v in input_map . items ( ) } return input_map