class_docstr: Urmp training set with midi note data.
  
  This class loads the segmented data in tfrecord that contains 4-second audio
  clips of the URMP dataset. To load tfrecord that contains unsegmented full
  piece of URMP recording, please use `UrmpMidiUnsegmented` class instead.
class_docstr_tok: ["Urmp","training","set","with","midi","note","data",".","This","class","loads","the","segmented","data","in","tfrecord","that","contains","4-second","audio","clips","of","the","URMP","dataset",".","To","load","tfrecord","that","contains","unsegmented","full","piece","of","URMP","recording",",","please","use","`","UrmpMidiUnsegmented","`","class","instead","."]
code: def features_dict(self):
      base_features = super().features_dict
      base_features.update(
          {
              "note_active_velocities": tf.io.FixedLenFeature(
                  [self._feature_length * 128], tf.float32
              ),
              "note_active_frame_indices": tf.io.FixedLenFeature(
                  [self._feature_length * 128], tf.float32
              ),
              "instrument_id": tf.io.FixedLenFeature([], tf.string),
              "recording_id": tf.io.FixedLenFeature([], tf.string),
              "power_db": tf.io.FixedLenFeature(
                  [self._feature_length], dtype=tf.float32
              ),
              "note_onsets": tf.io.FixedLenFeature(
                  [self._feature_length * 128], dtype=tf.float32
              ),
              "note_offsets": tf.io.FixedLenFeature(
                  [self._feature_length * 128], dtype=tf.float32
              ),
          }
      )
      return base_features
  
imports: import os
  from absl import logging
  from ddsp.spectral_ops import CREPE_FRAME_SIZE
  from ddsp.spectral_ops import CREPE_SAMPLE_RATE
  from ddsp.spectral_ops import get_framed_lengths
  import gin
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 1 for calling the UrmpMidi obj's underlying member method code with example usage: obj.features_dict() and returns: base_features