def testMultilabelMatch3(self):
predictions = np.random.randint(1, 5, size=(5, 1, 1, 1))
targets = np.random.randint(1, 5, size=(5, 10, 1, 1))
weights = np.random.randint(0, 2, size=(5, 1, 1, 1))
targets *= weights
print(
"========================================================================================"
)
print("Predictions are: ")
print(predictions)
print("Targets are: ")
print(targets)
print(
"========================================================================================"
)
predictions_repeat = np.repeat(predictions, 10, axis=1)
expected = (predictions_repeat == targets).astype(float)
expected = np.sum(expected, axis=(1, 2, 3))
expected = np.minimum(expected / 3.0, 1.)
expected = np.sum(expected * weights[:, 0, 0, 0]) / weights.shape[0]
with self.test_session() as session:
scores, weights_ = metrics.multilabel_accuracy_match3(
tf.one_hot(predictions, depth=5, dtype=tf.float32),
tf.constant(targets, dtype=tf.int32))
a, a_op = tf.metrics.mean(scores, weights_)
session.run(tf.local_variables_initializer())
session.run(tf.global_variables_initializer())
_ = session.run(a_op)
actual = session.run(a)
self.assertAlmostEqual(actual, expected, places=6)
def testMultilabelMatch3(self):
predictions = np.random.randint(1, 5, size=(100, 1, 1, 1))
targets = np.random.randint(1, 5, size=(100, 10, 1, 1))
weights = np.random.randint(0, 2, size=(100, 1, 1, 1))
targets *= weights
predictions_repeat = np.repeat(predictions, 10, axis=1)
expected = (predictions_repeat == targets).astype(float)
expected = np.sum(expected, axis=(1, 2, 3))
expected = np.minimum(expected / 3.0, 1.)
expected = np.sum(expected * weights[:, 0, 0, 0]) / np.sum(weights)
with self.test_session() as session:
scores, weights_ = metrics.multilabel_accuracy_match3(
tf.one_hot(predictions, depth=5, dtype=tf.float32),
tf.constant(targets, dtype=tf.int32))
a, a_op = tf.metrics.mean(scores, weights_)
session.run(tf.local_variables_initializer())
session.run(tf.global_variables_initializer())
_ = session.run(a_op)
actual = session.run(a)
self.assertAlmostEqual(actual, expected, places=6)