text: import click
  import numpy as np
  import requests
  import tensorflow as tf
  
  from huoguoml.util.string import concat_uri, coerce_url
  
  
  def softmax(x):
      """Compute softmax values for each sets of scores in x."""
      return np.exp(x) / np.sum(np.exp(x), axis=0)
  
  
  @click.command()
  @click.option("--service_uri", default="127.0.0.1:5000",
                help="URI to the HuoguoML serving client (default: 127.0.0.1:5000)")
  def main(service_uri: str):
      service_uri = coerce_url(service_uri)
  
      version = requests.get(concat_uri(service_uri, "api", "version"))
      print("VERSION:{}\n".format(version.json()))
  
      _, (x_test, y_test) = tf.keras.datasets.mnist.load_data()
      x_test = x_test / 255.0
  
      correct_predictions = 0
      for sample, label in zip(x_test, y_test):
          prediction = requests.post(concat_uri(service_uri, "api", "predict"), json={
              "flatten_input": sample.tolist()
          })
          prediction = np.array(prediction.json()["dense_1"])[0]
          predicted_class = np.argmax(softmax(prediction))
  
          if predicted_class == label:
              correct_predictions += 1
      print("TEST ACCURACY {}".format(correct_predictions / x_test.shape[0]))
  
  
  if __name__ == "__main__":
      main()
  