metric_ops_test.py 文件源码

def testValueTensorIsIdempotent(self):
    labels = tf.random_normal((10, 3), seed=2)
    predictions = labels * 0.5 + tf.random_normal((10, 3), seed=1) * 0.5
    cov, update_op = metrics.streaming_covariance(predictions, labels)

    with self.test_session() as sess:
      sess.run(tf.initialize_local_variables())

      # Run several updates.
      for _ in range(10):
        sess.run(update_op)

      # Then verify idempotency.
      initial_cov = cov.eval()
      for _ in range(10):
        self.assertEqual(initial_cov, cov.eval())