<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def wrap(tensor, books=None, tensor_shape=None):
 """Creates an input layer representing the given tensor. Args: tensor: The tensor. books: The bookkeeper; this is usually not required unless you are building multiple `tf.Graphs.` tensor_shape: An optional shape that will be set on the Tensor or verified to match the tensor. Returns: A layer. """

  if books is None:
    books = bookkeeper.for_default_graph()
  if isinstance(tensor, PrettyTensor):
    return tensor.as_layer()
  elif isinstance(tensor, UnboundVariable):

    def set_input_from_unbound_var(data):
      """Sets the input from the given unbound_var."""
      if data is not None:
        return wrap(data, books)
      else:
        return None

    return _DeferredLayer(books, set_input_from_unbound_var, [tensor], {})
  else:
    tensor = tf.convert_to_tensor(tensor, name='input')
    if tensor_shape:
      _set_shape_on_tensor(tensor, tensor_shape)
    return Layer(books, tensor=tensor, name=tensor.name)