class_docstr: Metrics for MIDI Autoencoder.
class_docstr_tok: ["Metrics","for","MIDI","Autoencoder","."]
code: def evaluate(self, batch, outputs, losses):
      del losses  # Unused.
      self._midi_metrics.update_state(outputs, outputs["pianoroll"])
  
imports: import ddsp
  from ddsp.training import heuristics
  from ddsp.training import metrics
  from ddsp.training import summaries
  import gin
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the MidiAutoencoderEvaluator obj's underlying member method code with example usage: obj.evaluate(batch, outputs, losses) without return types