class_docstr: A Module that converts monophonic melodies to a model specific encoding.
code: def transform(self, input_object):
      melody = input_object
      melody.squash(
          self._min_note, self._max_note, self._transpose_to_key
      )
      encoded = pipelines_common.make_sequence_example(
          *self._melody_encoder_decoder.encode(melody)
      )
      return [encoded]
  
file_path: magenta/magenta/models/melody_rnn/melody_rnn_pipeline.py
imports: from magenta.pipelines import dag_pipeline
  from magenta.pipelines import melody_pipelines
  from magenta.pipelines import note_sequence_pipelines
  from magenta.pipelines import pipeline
  from magenta.pipelines import pipelines_common
  import note_seq
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the EncoderPipeline obj's underlying member method code with example usage: obj.transform(input_object) and returns: list