def test_invalid_input(self):
"""Test that functions properly fail on invalid input."""
with self.assertRaisesRegexp(ValueError, 'Shapes .* are incompatible'):
classifier_metrics.run_inception(array_ops.ones([7, 50, 50, 3]))
p = array_ops.zeros([8, 10])
p_logits = array_ops.zeros([8, 10])
q = array_ops.zeros([10])
with self.assertRaisesRegexp(ValueError, 'must be floating type'):
classifier_metrics._kl_divergence(
array_ops.zeros([8, 10], dtype=dtypes.int32), p_logits, q)
with self.assertRaisesRegexp(ValueError, 'must be floating type'):
classifier_metrics._kl_divergence(p,
array_ops.zeros(
[8, 10], dtype=dtypes.int32), q)
with self.assertRaisesRegexp(ValueError, 'must be floating type'):
classifier_metrics._kl_divergence(p, p_logits,
array_ops.zeros(
[10], dtype=dtypes.int32))
with self.assertRaisesRegexp(ValueError, 'must have rank 2'):
classifier_metrics._kl_divergence(array_ops.zeros([8]), p_logits, q)
with self.assertRaisesRegexp(ValueError, 'must have rank 2'):
classifier_metrics._kl_divergence(p, array_ops.zeros([8]), q)
with self.assertRaisesRegexp(ValueError, 'must have rank 1'):
classifier_metrics._kl_divergence(p, p_logits, array_ops.zeros([10, 8]))
def test_invalid_input(self):
"""Test that functions properly fail on invalid input."""
with self.assertRaisesRegexp(ValueError, 'Shapes .* are incompatible'):
classifier_metrics.run_inception(array_ops.ones([7, 50, 50, 3]))
p = array_ops.zeros([8, 10])
p_logits = array_ops.zeros([8, 10])
q = array_ops.zeros([10])
with self.assertRaisesRegexp(ValueError, 'must be floating type'):
classifier_metrics._kl_divergence(
array_ops.zeros([8, 10], dtype=dtypes.int32), p_logits, q)
with self.assertRaisesRegexp(ValueError, 'must be floating type'):
classifier_metrics._kl_divergence(
p, array_ops.zeros([8, 10], dtype=dtypes.int32), q)
with self.assertRaisesRegexp(ValueError, 'must be floating type'):
classifier_metrics._kl_divergence(
p, p_logits, array_ops.zeros([10], dtype=dtypes.int32))
with self.assertRaisesRegexp(ValueError, 'must have rank 2'):
classifier_metrics._kl_divergence(array_ops.zeros([8]), p_logits,
q)
with self.assertRaisesRegexp(ValueError, 'must have rank 2'):
classifier_metrics._kl_divergence(p, array_ops.zeros([8]), q)
with self.assertRaisesRegexp(ValueError, 'must have rank 1'):
classifier_metrics._kl_divergence(p, p_logits,
array_ops.zeros([10, 8]))