class_docstr: Computes F0 and loudness metrics.
class_docstr_tok: ["Computes","F0","and","loudness","metrics","."]
code: def sample(self, batch, outputs, step):
      if "f0_hz" in outputs and "f0_hz" in batch:
          summaries.f0_summary(
              batch["f0_hz"], outputs["f0_hz"], step, name="f0_harmonic"
          )
  
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 3 for calling the F0LdEvaluator obj's underlying member method code with example usage: obj.sample(batch, outputs, step) without return types