def test_unsupported_input_type(self):
data = constant_op.constant([1.0, 0.0])
error_message = ('Tensor conversion requested dtype bool for Tensor'
' with dtype float32: .*')
with self.assertRaisesRegexp(ValueError, error_message):
_ = create_feature_bitmask_op.create_feature_bitmask(data)
def test_feature_bitmask_single_dim_single_tensor(self):
"""Test that the op can reduce a single-dimension tensor to a constant."""
data = constant_op.constant([True, False])
result = create_feature_bitmask_op.create_feature_bitmask(data)
expected_result = constant_op.constant(2)
self.assertAllEqual(expected_result, result)
def test_feature_bitmask_multi_dim_single_tensor(self):
"""Test that the op can reduce a multi-dimension tensor."""
data = tf.constant([[True, True, False], [True, False, False]])
result = create_feature_bitmask_op.create_feature_bitmask(data)
expected_result = tf.constant([6, 4])
self.assertAllEqual(expected_result, result)
def test_feature_bitmask_multiple_tensors_multi_dim_stack(self):
"""Test that the op can reduce a stacked list of multi-dim tensors."""
data_1 = constant_op.constant([[True, False], [False, True]])
data_2 = constant_op.constant([[False, True], [True, True]])
stack_data = array_ops.stack([data_1, data_2], -1)
expected_result = constant_op.constant([[2, 1], [1, 3]])
result = create_feature_bitmask_op.create_feature_bitmask(stack_data)
self.assertAllEqual(expected_result, result)
def test_larger_than_dtype_shape(self):
data = array_ops.fill([2, 9], False)
error_message = (
r'data.shape\[-1\] is too large for %s \(was 9, cannot '
r'exceed 8\).*') % dtypes.uint8.name
with self.assertRaisesRegexp(ValueError, error_message):
_ = create_feature_bitmask_op.create_feature_bitmask(
data, dtype=dtypes.uint8)
def test_unsupported_dtype_type(self):
data = constant_op.constant([True, False])
bad_dtype = dtypes.uint32
error_message = 'dtype must be one of: .*, was %s' % bad_dtype.name
with self.assertRaisesRegexp(errors.InvalidArgumentError,
error_message):
_ = create_feature_bitmask_op.create_feature_bitmask(
data, dtype=bad_dtype)
def test_feature_bitmask_multiple_tensors_stack(self):
"""Test that the op can reduce a stacked list of tensors."""
data_1 = tf.constant([True, False])
data_2 = tf.constant([False, True])
stack_data = tf.stack([data_1, data_2], -1)
expected_result = tf.constant([2, 1])
result = create_feature_bitmask_op.create_feature_bitmask(stack_data)
self.assertAllEqual(expected_result, result)
def test_larger_than_dtype_shape_at_runtime(self):
data = tf.placeholder_with_default(tf.fill([2, 9], False), shape=None)
error_message = r'.*data.shape\[-1\] is too large for %s.*' % tf.uint8.name
with self.assertRaisesRegexp(
(tf.errors.InvalidArgumentError, ValueError), error_message):
self.evaluate(
create_feature_bitmask_op.create_feature_bitmask(
data, dtype=tf.uint8))
def test_feature_bitmask_multiple_tensors_error(self):
"""Test that the op errors when presented with a single tensor."""
data_1 = constant_op.constant([True, False])
data_2 = constant_op.constant([True, True])
list_data = [data_1, data_2]
error_message = 'CreateFeatureBitmask does not support lists of tensors.*'
with self.assertRaisesRegexp(errors.InvalidArgumentError,
error_message):
_ = create_feature_bitmask_op.create_feature_bitmask(list_data)
def test_supports_tensors_with_unknown_shape(self):
"""Test that the op handles tensors with unknown shape."""
data = array_ops.placeholder_with_default(constant_op.constant(
[[[True, True, False], [True, False, False]],
[[False, False, True], [True, False, True]]]),
shape=None)
result = create_feature_bitmask_op.create_feature_bitmask(data)
expected_result = constant_op.constant([[6, 4], [1, 5]])
self.assertAllEqual(expected_result, result)
def test_docstring_example2(self):
data = [[True, False], [False, True], [True, True]]
result = create_feature_bitmask_op.create_feature_bitmask(data)
expected_result = constant_op.constant([0b10, 0b01, 0b11])
self.assertAllEqual(result, expected_result)
def test_docstring_example1(self):
data = [True, False, False, True]
result = create_feature_bitmask_op.create_feature_bitmask(data)
self.assertAllEqual(result, 0b1001)
def test_larger_than_max_shape(self):
data = array_ops.fill([2, 64], False)
error_message = r'data.shape\[-1\] must be less than 64, is 64.'
with self.assertRaisesRegexp(ValueError, error_message):
_ = create_feature_bitmask_op.create_feature_bitmask(data)
