class_docstr: Applies an activation function to an output.
  Arguments:
      activation: name of activation function to use or
          TF Encrypted operation.
  Input shape:
      Arbitrary. Use the keyword argument `input_shape`
      (tuple of integers, does not include the samples axis)
      when using this layer as the first layer in a model.
  Output shape:
      Same shape as input.
code: def __init__(self, activation, **kwargs):
      super(Activation, self).__init__(**kwargs)
      self.activation_identifier = activation
      self.activation = activations.get(self.activation_identifier)
  
file_path: tf-encrypted/tf_encrypted/keras/layers/activation.py
imports: from tf_encrypted.keras import activations
  from tf_encrypted.keras.engine import Layer
label_desc: Use image node_id 1 to create a new Activation object from inherited base classes: Layer with example: obj = Activation(activation)