5e854f25098ca40a4ac80197607bf883feaeb375,research/object_detection/utils/learning_schedules_test.py,LearningSchedulesTest,testCosineDecayWithWarmup,#LearningSchedulesTest#,43

Before Change

    learning_rate = learning_schedules.cosine_decay_with_warmup(
        global_step, learning_rate_base, total_steps,
        warmup_learning_rate, warmup_steps)
    with self.test_session() as sess:
      output_rates = []
      for input_global_step in input_global_steps:
        output_rate = sess.run(learning_rate,
                               feed_dict={global_step: input_global_step})
        output_rates.append(output_rate)
      self.assertAllClose(output_rates, exp_rates)

  def testManualStepping(self):
    global_step = tf.placeholder(tf.int64, [])
    boundaries = [2, 3, 7]
    rates = [1.0, 2.0, 3.0, 4.0]

After Change

      return (learning_rate,)
    exp_rates = [0.1, 0.5, 0.9, 1.0, 0]
    input_global_steps = [0, 4, 8, 9, 100]
    output_rates = [
        self.execute(graph_fn, [np.array(step).astype(np.int64)])
        for step in input_global_steps
    ]
    self.assertAllClose(output_rates, exp_rates)

  def testManualStepping(self):
    def graph_fn(global_step):

Instances