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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def create_sequence_pretty_tensor(sequence_input, shape=None, save_state=True):
 """Creates a PrettyTensor object for the given sequence. The first dimension is treated as a time-dimension * batch and a default is set for `unroll` and `state_saver`. TODO(eiderman):
 Remove shape. Args: sequence_input: A SequenceInput or StateSavingSequenceInput shape: The shape of each item in the sequence (including batch). save_state: If true, use the sequence_input's state and save_state methods. Returns: 2 Layers: inputs, targets """

  inputs = prettytensor.wrap_sequence(sequence_input.inputs, tensor_shape=shape)
  targets = prettytensor.wrap_sequence(sequence_input.targets)
  if save_state:
    bookkeeper.set_recurrent_state_saver(sequence_input)
  return inputs, targets