code: from scipy.io.wavfile import read
  import numpy as np
  import io
  import csv
  
  
  class TensorFlowPredictor:
      def __init__(self, tensorflow_client, config):
          self.client = tensorflow_client
          self.class_names = self.class_names_from_csv("class_names.csv")
  
      def class_names_from_csv(self, csv_file):
          class_names = []
          with open(csv_file, "r", newline="") as f:
              for row in csv.reader(f, delimiter=","):
                  class_names.append(row[2])
          return class_names
  
      def predict(self, payload):
          rate, data = read(io.BytesIO(payload))
          assert rate == 16000
  
          result = self.client.predict({"waveform": np.array(data, dtype=np.float32)})
          scores = np.array(result["output_0"]).reshape((-1, 521))
  
          predicted_class = self.class_names[scores.mean(axis=0).argmax() + 1]
          return predicted_class
  
apis: numpy.array