          Parameters
          ----------
          inputs: tensor
              Input tensor, or list/tuple of input tensors
          """
          return tf.nn.swish(inputs * self.beta)
  
      def get_config(self):
          """Returns the config of the layer.
  
 
</s> remove     def get_config(self):
 </s> add     def get_config(self) -> dict[str, T.Any]: </s> remove     def get_config(self):
 </s> add     def get_config(self) -> dict[str, T.Any]: </s> remove         if self.data_format == 'channels_last':
            pooled = K.std(inputs, axis=[1, 2])
        else:
            pooled = K.std(inputs, axis=[2, 3])
        return pooled

 </s> add  </s> remove         tensor
 </s> add         :class:`tf.Tensor`
        Returns
        -------
        :class:`tf.Tensor`
            A tensor or list/tuple of tensors
          Parameters
          ----------
          inputs: tensor
              Input tensor, or list/tuple of input tensors
        Returns
        -------
        :class:`tf.Tensor`
            A tensor or list/tuple of tensors
          """
          return tf.nn.swish(inputs * self.beta)
  
      def get_config(self):
          """Returns the config of the layer.
  
keep keep keep add keep keep keep keep keep keep
 Training fixes:
  - Fix mixed precision layer storing and switching
  - typofix in _requirements_base.txt
  - lib.model.layers - cleanup, docs and tests fixes
  - lib.model.nn_blocks - typing fixes 
lib/model/layers.py