code: def multiplex(cond, a, b, name=None):
      """Return elements chosen from `a` or `b` depending on `cond`.
  
      This is similar to `np.where` and `tf.where`, but simplified to only handle
      the case of dense tensors, no optional parameters, no broadcasting, etc..
  
      >>> multiplex([True, False, False, True], [1,2,3,4], [100,200,300,400])
      <tf.Tensor: shape=(4,), dtype=int32, numpy=array([  1, 200, 300,   4], ...)>
  
      Args:
        cond: tf.Tensor of type bool. Where True, yield `a`, otherwise yield `b`.
        a: tf.Tensor with the same type and shape as `b`.
        b: tf.Tensor with the same type and shape as `a`.
        name: An optional name for the op.
  
      Returns:
        A tf.Tensor with elements from `a` where `cond` is True, and elements
        from `b` elsewhere.
      """
      return examples_multiplex_dense(cond=cond, a=a, b=b, name=name)
  
label_desc: Use image node_id 1 for calling a global function with example usage: multiplex(cond, a, b, name) and returns: examples_multiplex_dense