def testRMSEMetric(self):
predictions = np.full((10, 1), 1) # All 1's
targets = np.full((10, 1), 3) # All 3's
expected = np.sqrt(np.mean((predictions - targets)**2)) # RMSE = 2.0
with self.test_session() as session:
rmse, _ = metrics.padded_rmse(
tf.constant(predictions, dtype=tf.int32),
tf.constant(targets, dtype=tf.int32))
session.run(tf.global_variables_initializer())
actual = session.run(rmse)
self.assertEqual(actual, expected)
def testRMSEMetric(self):
predictions = np.full((10, 1), 1) # All 1's
targets = np.full((10, 1), 3) # All 3's
expected = np.sqrt(np.mean((predictions - targets)**2)) # RMSE = 2.0
with self.test_session() as session:
rmse, _ = metrics.padded_rmse(
tf.constant(predictions, dtype=tf.int32),
tf.constant(targets, dtype=tf.int32))
session.run(tf.global_variables_initializer())
actual = session.run(rmse)
self.assertEqual(actual, expected)
