class_docstr: A layer that combines multiple :class:`Layer` that have the same output shapes
  according to an element-wise operation.
  If the element-wise operation is complicated, please consider to use :class:`ElementwiseLambda`.
  
  Parameters
  ----------
  combine_fn : a TensorFlow element-wise combine function
      e.g. AND is ``tf.minimum`` ;  OR is ``tf.maximum`` ; ADD is ``tf.add`` ; MUL is ``tf.multiply`` and so on.
      See `TensorFlow Math API <https://www.tensorflow.org/versions/master/api_docs/python/math_ops.html#math>`__ .
      If the combine function is more complicated, please consider to use :class:`ElementwiseLambda`.
  act : activation function
      The activation function of this layer.
  name : None or str
      A unique layer name.
  
  Examples
  --------
  >>> class CustomModel(tl.models.Model):
  >>>     def __init__(self):
  >>>         super(CustomModel, self).__init__(name="custom")
  >>>         self.dense1 = tl.layers.Dense(in_channels=20, n_units=10, act=tf.nn.relu, name='relu1_1')
  >>>         self.dense2 = tl.layers.Dense(in_channels=20, n_units=10, act=tf.nn.relu, name='relu2_1')
  >>>         self.element = tl.layers.Elementwise(combine_fn=tf.minimum, name='minimum', act=tf.identity)
  
  >>>     def forward(self, inputs):
  >>>         d1 = self.dense1(inputs)
  >>>         d2 = self.dense2(inputs)
  >>>         outputs = self.element([d1, d2])
  >>>         return outputs
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code: def build(self, inputs_shape):
      pass
  
file_path: TensorLayer/tensorlayer/layers/merge.py
imports: import tensorflow
  from tensorlayer import logging
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 3 for calling the Elementwise obj's underlying member method code with example usage: obj.build(inputs_shape) without return types