def test_construct(self):
m = counters.NumBatchesCounter()
self.assertEqual(m.name, 'num_batches')
self.assertTrue(m.stateful)
self.assertEqual(m.dtype, tf.int64)
self.assertLen(m.variables, 1)
self.assertEqual(m.total, 0)
m = counters.NumBatchesCounter('num_batches2')
self.assertEqual(m.name, 'num_batches2')
def test_update_with_sample_weight(self, batch1, batch2):
m = counters.NumBatchesCounter()
self.assertEqual(m(batch1, batch1), 1)
self.assertEqual(m.total, 1)
self.assertEqual(m.update_state(batch2, batch2), 2)
self.assertEqual(m.total, 2)
def test_reset_to_zero(self):
m = counters.NumBatchesCounter()
self.assertGreater(m(tf.zeros([10, 1]), tf.zeros([10])), 0)
self.assertGreater(m.total, 0)
m.reset_state()
self.assertEqual(m.total, 0)
def metrics_fn():
return [
counters.NumExamplesCounter(),
counters.NumBatchesCounter(),
tf.keras.metrics.SparseCategoricalAccuracy()
]
