class_docstr: Represents the contents of a hub.Module before it has been instantiated.
  
  Warning: Deprecated. This belongs to the hub.Module API and TF1 Hub format.
  For TF2, switch to plain SavedModels and hub.load().
  
  A ModuleSpec is the blueprint used by `Module` to create one or more instances
  of a specific module in one or more graphs. The details on how to construct
  the Module are internal to the library implementation but methods to inspect
  a Module interface are public.
  
  Note: Do not instantiate this class directly. Use `hub.load_module_spec` or
  `hub.create_module_spec`.
  
  THIS FUNCTION IS DEPRECATED.
docstr: Internal.
  
  Args:
    name: A string with the an unused name scope.
    trainable: A boolean, whether the Module is to be instantiated as
      trainable.
    tags: A set of strings specifying the graph variant to use.
  
  Returns:
    A ModuleImpl.
code: def _create_impl(self, name, trainable, tags):
      """Internal.
  
      Args:
        name: A string with the an unused name scope.
        trainable: A boolean, whether the Module is to be instantiated as
          trainable.
        tags: A set of strings specifying the graph variant to use.
  
      Returns:
        A ModuleImpl.
      """
      raise NotImplementedError()
  
file_path: hub/tensorflow_hub/module_spec.py
imports: import abc
label_desc: Use image node_id 9 for calling the ModuleSpec obj's underlying member method code with example usage: obj._create_impl(name, trainable, tags) without return types