class_docstr: Encode an audio clip to WAV.
  
  This function is thread-safe and exhibits good parallel performance.
  
  Arguments:
    audio: A numpy array of shape `[samples, channels]`.
    samples_per_second: A positive `int`, in Hz.
  
  Returns:
    A bytestring with WAV-encoded data.
code: def initialize_graph(self):
      # TODO(nickfelt): remove on-demand imports once dep situation is fixed.
      import tensorflow.compat.v1 as tf
  
      self._audio_placeholder = tf.placeholder(
          dtype=tf.float32, name="image_to_encode"
      )
      self._samples_per_second_placeholder = tf.placeholder(
          dtype=tf.int32, name="samples_per_second"
      )
      self._encode_op = tf.audio.encode_wav(
          self._audio_placeholder,
          sample_rate=self._samples_per_second_placeholder,
      )
  
file_path: tensorboard/tensorboard/util/encoder.py
imports: import numpy
  from tensorboard.util import op_evaluator
label_desc: Use image node_id 2 for calling the _TensorFlowWavEncoder obj's underlying member method code with example usage: obj.initialize_graph() without return types