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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 decode(pieces, sequence_length, model_file=None, model_proto=None, reverse=False, name=None):
 """Decode pieces into postprocessed text. Args: pieces: A 2D int32 or string tensor [batch_size x max_length] of encoded sequences. sequence_length: A 1D int32 tensor [batch_size] representing the length of pieces. model_file: The sentencepiece model file path. model_proto: The sentencepiece model serialized proto. Either `model_file` or `model_proto` must be set. reverse: Reverses the tokenized sequence (Default = false) name: The name argument that is passed to the op function. Returns: text: A 1D string tensor of decoded string. """


  return _gen_sentencepiece_processor_op.sentencepiece_decode(
      pieces, sequence_length, model_file=model_file,
      model_proto=model_proto, reverse=reverse, name=name)