def __init__()

in tensorflow_hub/keras_layer.py [0:0]

• 38 lines of code
• 14 McCabe index (conditional complexity)

  def __init__(
      self,
      handle,
      trainable=False,
      arguments=None,
      _sentinel=None,  # pylint: disable=invalid-name
      tags=None,
      signature=None,
      signature_outputs_as_dict=None,
      output_key=None,
      output_shape=None,
      load_options=None,
      **kwargs):
    # Note: for compatibility with keras-model serialization this layer is
    # json-serializable. If you add or change arguments here, please also update
    # the `get_config` method.
    # The arguments are marked NoDependency to avoid autoconversion to a
    # trackable _DictWrapper, because that upsets json.dumps() when saving
    # the result of get_config().
    self._handle = handle
    self._arguments = data_structures.NoDependency(arguments or {})
    self._signature = signature
    self._signature_outputs_as_dict = signature_outputs_as_dict
    self._output_key = output_key
    if output_shape:
      # Autograph chokes on _convert_nest_to_shapes(), so we call it here
      # and not from within call().
      self._output_shape = data_structures.NoDependency(
          _convert_nest_to_shapes(output_shape))

    self._load_options = load_options
    self._func = load_module(handle, tags, self._load_options)
    self._is_hub_module_v1 = getattr(self._func, "_is_hub_module_v1", False)

    # Update with the defaults when using legacy TF1 Hub format.
    if self._is_hub_module_v1:
      self._signature = self._signature or "default"
      if not self._signature_outputs_as_dict:
        self._output_key = self._output_key or "default"
    # More validity checks.
    if self._signature and (bool(self._output_key is not None)
                            == bool(self._signature_outputs_as_dict)):
      raise ValueError("When using a signature, either output_key or "
                       "signature_outputs_as_dict=True should be set.")
    if not self._signature and self._signature_outputs_as_dict:
      raise ValueError("signature_outputs_as_dict is only valid if specifying "
                       "a signature (or using a legacy TF1 Hub format).")

    self._callable = self._get_callable()
    self._has_training_argument = func_has_training_argument(self._callable)
    self._setup_layer(trainable, **kwargs)