code: def broadcast(*args):
      """Broadcast given variables.
  
      Args:
          args (:class:`~chainer.Variable` or :ref:`ndarray`):
              Input variables to be broadcasted. Each dimension of the shapes \
              of the input variables must have the same size.
  
      Returns:
          ~chainer.Variable: :class:`~chainer.Variable` or tuple of \
              :class:`~chainer.Variable` objects which are broadcasted \
              from the given arguments.
  
      .. admonition:: Example
  
          >>> x = np.random.uniform(0, 1, (3, 2)).astype(np.float32)
          >>> y = F.broadcast(x)
          >>> np.all(x == y.array)
          True
          >>> z = np.random.uniform(0, 1, (3, 2)).astype(np.float32)
          >>> y, w = F.broadcast(x, z)
          >>> np.all(x == y.array) & np.all(z == w.array)
          True
  
      """
      if len(args) == 1:
          return chainer.as_variable(args[0])
      return Broadcast().apply(args)
  
imports: import six
  import chainer
  from chainer import backend
  from chainer import function_node
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 1 for calling a global function with example usage: broadcast() and returns: Broadcast, chainer