  
      def build(self, input_shape):
          pass
  
      def call(self, input_tensor, mask=None):  # pylint:disable=unused-argument,arguments-differ
          """This is where the layer's logic lives.
  
 
</s> remove     def call(self, x, mask=None):
        y = self.depth_to_space(x, self.scale_factor, self.data_format)
        return y
 </s> add     def call(self, input_tensor, mask=None):  # pylint:disable=unused-argument,arguments-differ
        """This is where the layer's logic lives.

        Parameters
        ----------
        inputs: tensor
            Input tensor, or list/tuple of input tensors
        kwargs: dict
            Additional keyword arguments

        Returns
        -------
        tensor
            A tensor or list/tuple of tensors
        """
        retval = self._depth_to_space(input_tensor, self.scale_factor, self.data_format)
        return retval </s> remove     def call(self, x, mask=None):
 </s> add     def call(self, x, mask=None):  # pylint:disable=unused-argument,arguments-differ
        """This is where the layer's logic lives.

        Parameters
        ----------
        inputs: tensor
            Input tensor, or list/tuple of input tensors
        kwargs: dict
            Additional keyword arguments

        Returns
        -------
        tensor
            A tensor or list/tuple of tensors
        """ </s> remove     def call(self, inputs, training=None):
 </s> add     def call(self, inputs, training=None):  # pylint:disable=arguments-differ,unused-argument
        """This is where the layer's logic lives.

        Parameters
        ----------
        inputs: tensor
            Input tensor, or list/tuple of input tensors

        Returns
        -------
        tensor
            A tensor or list/tuple of tensors
        """ </s> remove     def call(self, x):
        return K.l2_normalize(x, self.axis)
 </s> add     def call(self, inputs):  # pylint:disable=arguments-differ
        """This is where the layer's logic lives.

        Parameters
        ----------
        inputs: tensor
            Input tensor, or list/tuple of input tensors
        kwargs: dict
            Additional keyword arguments

        Returns
        -------
        tensor
            A tensor or list/tuple of tensors
        """
        return K.l2_normalize(inputs, self.axis)
        """Creates the layer weights.

        Must be implemented on all layers that have weights.

        Parameters
        ----------
        input_shape: tensor
            Keras tensor (future input to layer) or ``list``/``tuple`` of Keras tensors to
            reference for weight shape computations.
        """
  
      def build(self, input_shape):
        """Creates the layer weights.

        Must be implemented on all layers that have weights.

        Parameters
        ----------
        input_shape: tensor
            Keras tensor (future input to layer) or ``list``/``tuple`` of Keras tensors to
            reference for weight shape computations.
        """
          pass
  
      def call(self, input_tensor, mask=None):  # pylint:disable=unused-argument,arguments-differ
          """This is where the layer's logic lives.
  
keep add keep keep keep keep keep
 Simple backend unit tests (#1020)

* Add simple backend tests for lib.model
* Document lib.model
* Fix GMSD Loss for AMD
* Remove obsolete code from lib.model 
lib/model/layers.py