class_docstr: Layer that computes the maximum (element-wise) 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).
  
  >>> tf.keras.layers.Maximum()([np.arange(5).reshape(5, 1),
  ...                            np.arange(5, 10).reshape(5, 1)])
  <tf.Tensor: shape=(5, 1), dtype=int64, numpy=
  array([[5],
       [6],
       [7],
       [8],
       [9]])>
  
  >>> x1 = tf.keras.layers.Dense(8)(np.arange(10).reshape(5, 2))
  >>> x2 = tf.keras.layers.Dense(8)(np.arange(10, 20).reshape(5, 2))
  >>> maxed = tf.keras.layers.Maximum()([x1, x2])
  >>> maxed.shape
  TensorShape([5, 8])
code: def _merge_function(self, inputs):
      output = inputs[0]
      for i in range(1, len(inputs)):
          output = math_ops.maximum(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 Maximum obj's underlying member method code with example usage: obj._merge_function(inputs) and returns: output