class_docstr: Layer that adds a list of inputs.
  
  It takes as input a list of tensors,
  all of the same shape, and returns
  a single tensor (also of the same shape).
  
  Examples:
  
  >>> input_shape = (2, 3, 4)
  >>> x1 = tf.random.normal(input_shape)
  >>> x2 = tf.random.normal(input_shape)
  >>> y = tf.keras.layers.Add()([x1, x2])
  >>> print(y.shape)
  (2, 3, 4)
  
  Used in a functional model:
  
  >>> input1 = tf.keras.layers.Input(shape=(16,))
  >>> x1 = tf.keras.layers.Dense(8, activation='relu')(input1)
  >>> input2 = tf.keras.layers.Input(shape=(32,))
  >>> x2 = tf.keras.layers.Dense(8, activation='relu')(input2)
  >>> # equivalent to `added = tf.keras.layers.add([x1, x2])`
  >>> added = tf.keras.layers.Add()([x1, x2])
  >>> out = tf.keras.layers.Dense(4)(added)
  >>> model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)
code: def _merge_function(self, inputs):
      output = inputs[0]
      for i in range(1, len(inputs)):
          output += inputs[i]
      return output
  
imports: from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.engine.base_layer import Layer
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
label_desc: Use image node_id 1 for calling the Add obj's underlying member method code with example usage: obj._merge_function(inputs) and returns: output