layers.py 文件源码

def __init__(self, input_type=None, output_type=None, name_or_scope=None):
    """Creates the layer.

    Args:
      input_type: A type.
      output_type: A type.
      name_or_scope: A string or variable scope. If a string, a new variable
        scope will be created by calling
        [`create_variable_scope`](#create_variable_scope), with defaults
        inherited from the current variable scope. If no caching device is set,
        it will be set to `lambda op: op.device`. This is because `tf.while` can
        be very inefficient if the variables it uses are not cached locally.
    """
    if name_or_scope is None: name_or_scope = type(self).__name__
    if isinstance(name_or_scope, tf.VariableScope):
      self._vscope = name_or_scope
      name = str(self._vscope.name)
    elif isinstance(name_or_scope, six.string_types):
      self._vscope = create_variable_scope(name_or_scope)
      name = name_or_scope
    else:
      raise TypeError('name_or_scope must be a tf.VariableScope or a string: '
                      '%s' % (name_or_scope,))
    if self._vscope.caching_device is None:
      self._vscope.set_caching_device(lambda op: op.device)
    super(Layer, self).__init__(input_type, output_type, name)

    if not hasattr(self, '_constructor_name'):
      self._constructor_name = '__.%s' % self.__class__.__name__
    if not hasattr(self, '_constructor_args'):
      self._constructor_args = None
    if not hasattr(self, '_constructor_kwargs'):
      self._constructor_kwargs = None