From ad932c3e609ba77c74a61bd83880e730aaab4eeb Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Mon, 3 Feb 2025 04:42:49 -0800 Subject: [PATCH] cleanup of deprecated test methods PiperOrigin-RevId: 722607226 --- .../tests/graph_convolution_test.py | 21 ++++++------ .../convolution/tests/graph_pooling_test.py | 19 ++++++----- .../geometry/convolution/tests/utils_test.py | 34 +++++++++++-------- .../representation/mesh/tests/sampler_test.py | 4 +-- .../representation/mesh/tests/utils_test.py | 6 ++-- .../transformation/tests/quaternion_test.py | 7 ++-- tensorflow_graphics/io/tests/exr_test.py | 11 +++--- .../tests/intersection_over_union_test.py | 5 +-- .../opengl/tests/rasterizer_op_test.py | 2 +- .../tests/rasterization_backend_test_base.py | 2 +- 10 files changed, 60 insertions(+), 51 deletions(-) diff --git a/tensorflow_graphics/geometry/convolution/tests/graph_convolution_test.py b/tensorflow_graphics/geometry/convolution/tests/graph_convolution_test.py index 20a4771dc..a2f422039 100644 --- a/tensorflow_graphics/geometry/convolution/tests/graph_convolution_test.py +++ b/tensorflow_graphics/geometry/convolution/tests/graph_convolution_test.py @@ -140,7 +140,7 @@ def test_feature_steered_convolution_exception_raised_types( data, neighbors, sizes = _random_data(1, 5, 3, True, False, data_type, neighbors_type, sizes_type) u, v, c, w, b = _random_variables(3, 3, 1, var_type) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): _ = gc.feature_steered_convolution( data=data, neighbors=neighbors, @@ -178,7 +178,7 @@ def test_feature_steered_convolution_exception_not_raised_types( def test_feature_steered_convolution_exception_raised_shapes(self): """Check that invalid input shapes trigger the right exceptions.""" - with self.assertRaisesRegexp(ValueError, "must have a rank of 2"): + with self.assertRaisesRegex(ValueError, "must have a rank of 2"): data, neighbors = _dummy_data(1, 5, 2) u, v, c, w, b = _dummy_variables(2, 2, 1) data = data[0, :] @@ -192,7 +192,7 @@ def test_feature_steered_convolution_exception_raised_shapes(self): var_w=w, var_b=b) - with self.assertRaisesRegexp(ValueError, "must have a rank greater than 1"): + with self.assertRaisesRegex(ValueError, "must have a rank greater than 1"): u, v, c, w, b = _dummy_variables(2, 2, 1) data = np.ones(shape=(5), dtype=np.float32) neighbors = _dense_to_sparse(np.ones(shape=(5), dtype=np.float32)) @@ -206,8 +206,9 @@ def test_feature_steered_convolution_exception_raised_shapes(self): var_w=w, var_b=b) - with self.assertRaisesRegexp(ValueError, - "Not all batch dimensions are identical."): + with self.assertRaisesRegex( + ValueError, "Not all batch dimensions are identical." + ): data, neighbors = _dummy_data(1, 5, 2) u, v, c, w, b = _dummy_variables(2, 2, 1) _ = gc.feature_steered_convolution( @@ -553,7 +554,7 @@ def test_edge_convolution_template_exception_raised_types( """Check the type errors for invalid input types.""" data, neighbors, sizes = _random_data(1, 5, 3, True, False, data_type, neighbors_type, sizes_type) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): gc.edge_convolution_template( data=data, neighbors=neighbors, @@ -590,7 +591,7 @@ def test_edge_convolution_template_exception_not_raised_types( def test_edge_convolution_template_exception_raised_shapes(self): """Check that invalid input shapes trigger the right exceptions.""" - with self.assertRaisesRegexp(ValueError, "must have a rank of 2"): + with self.assertRaisesRegex(ValueError, "must have a rank of 2"): data, neighbors = _dummy_data(1, 5, 2) data = data[0, :] _ = gc.edge_convolution_template( @@ -601,7 +602,7 @@ def test_edge_convolution_template_exception_raised_shapes(self): reduction="weighted", edge_function_kwargs=dict()) - with self.assertRaisesRegexp(ValueError, "must have a rank greater than 1"): + with self.assertRaisesRegex(ValueError, "must have a rank greater than 1"): data = np.ones(shape=(5), dtype=np.float32) neighbors = _dense_to_sparse(np.ones(shape=(5), dtype=np.float32)) _ = gc.edge_convolution_template( @@ -612,7 +613,7 @@ def test_edge_convolution_template_exception_raised_shapes(self): reduction="weighted", edge_function_kwargs=dict()) - with self.assertRaisesRegexp(ValueError, "must have a rank of 1"): + with self.assertRaisesRegex(ValueError, "must have a rank of 1"): data, neighbors = _dummy_data(1, 5, 2) _ = gc.edge_convolution_template( data=data, @@ -626,7 +627,7 @@ def test_edge_convolution_template_exception_raised_shapes(self): def test_edge_convolution_template_exception_raised_reduction( self, reduction): """Check that an invalid reduction method triggers the exception.""" - with self.assertRaisesRegexp(ValueError, "reduction method"): + with self.assertRaisesRegex(ValueError, "reduction method"): data, neighbors = _dummy_data(1, 5, 2) gc.edge_convolution_template( data=data, diff --git a/tensorflow_graphics/geometry/convolution/tests/graph_pooling_test.py b/tensorflow_graphics/geometry/convolution/tests/graph_pooling_test.py index 1d7164ee7..d8398593f 100644 --- a/tensorflow_graphics/geometry/convolution/tests/graph_pooling_test.py +++ b/tensorflow_graphics/geometry/convolution/tests/graph_pooling_test.py @@ -62,7 +62,7 @@ def test_pool_exception_raised_types(self, err_msg, data_type, pool_map_type, pool_map = _dense_to_sparse(np.ones((2, 3, 3), dtype=pool_map_type)) sizes = np.array(((1, 2), (2, 3)), dtype=sizes_type) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): gp.pool(data, pool_map, sizes) @parameterized.parameters( @@ -80,7 +80,7 @@ def test_pool_exception_raised_shapes(self, err_msg, data_shape, else: sizes = None - with self.assertRaisesRegexp(ValueError, err_msg): + with self.assertRaisesRegex(ValueError, err_msg): gp.pool(data, pool_map, sizes) def test_pool_exception_raised_algorithm(self): @@ -88,8 +88,9 @@ def test_pool_exception_raised_algorithm(self): data = np.ones(shape=(2, 2)) pool_map = _dense_to_sparse(np.ones(shape=(2, 2))) - with self.assertRaisesRegexp( - ValueError, 'The pooling method must be "weighted" or "max"'): + with self.assertRaisesRegex( + ValueError, 'The pooling method must be "weighted" or "max"' + ): gp.pool(data, pool_map, sizes=None, algorithm='mean') @parameterized.parameters( @@ -201,7 +202,7 @@ def test_unpool_exception_raised_types(self, err_msg, data_type, pool_map = _dense_to_sparse(np.ones((2, 3, 3), dtype=pool_map_type)) sizes = np.array(((1, 2), (2, 3)), dtype=sizes_type) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): gp.unpool(data, pool_map, sizes) @parameterized.parameters( @@ -221,7 +222,7 @@ def test_unpool_exception_raised_shapes(self, err_msg, data_shape, else: sizes = None - with self.assertRaisesRegexp(ValueError, err_msg): + with self.assertRaisesRegex(ValueError, err_msg): gp.unpool(data, pool_map, sizes) @parameterized.parameters( @@ -311,7 +312,7 @@ def test_upsample_transposed_convolution_exception_raised_types( pool_map = _dense_to_sparse(np.ones((2, 3, 3), dtype=pool_map_type)) sizes = np.array(((1, 2), (2, 3)), dtype=sizes_type) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): gp.upsample_transposed_convolution( data, pool_map, sizes, kernel_size=1, transposed_convolution_op=None) @@ -332,7 +333,7 @@ def test_upsample_transposed_convolution_exception_raised_shapes( else: sizes = None - with self.assertRaisesRegexp(ValueError, err_msg): + with self.assertRaisesRegex(ValueError, err_msg): gp.upsample_transposed_convolution( data, pool_map, sizes, kernel_size=1, transposed_convolution_op=None) @@ -342,7 +343,7 @@ def test_upsample_transposed_convolution_exception_raised_callable(self): pool_map = _dense_to_sparse(np.eye(5)) err_msg = "'transposed_convolution_op' must be callable." - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): gp.upsample_transposed_convolution( data, pool_map, diff --git a/tensorflow_graphics/geometry/convolution/tests/utils_test.py b/tensorflow_graphics/geometry/convolution/tests/utils_test.py index 7a21dd210..849fb5288 100644 --- a/tensorflow_graphics/geometry/convolution/tests/utils_test.py +++ b/tensorflow_graphics/geometry/convolution/tests/utils_test.py @@ -58,7 +58,7 @@ def test_check_valid_graph_convolution_input_exception_raised_types( neighbors = _dense_to_sparse(np.ones(shape=(2, 2, 2), dtype=neighbors_type)) sizes = tf.convert_to_tensor(value=np.array((2, 2), dtype=sizes_type)) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): utils.check_valid_graph_convolution_input(data, neighbors, sizes) @parameterized.parameters( @@ -187,7 +187,7 @@ def test_check_valid_graph_pooling_exception_raised_types( sizes = tf.convert_to_tensor( value=np.array(((1, 2), (2, 3)), dtype=sizes_type)) - with self.assertRaisesRegexp(TypeError, err_msg): + with self.assertRaisesRegex(TypeError, err_msg): utils.check_valid_graph_pooling_input(data, pool_map, sizes) @parameterized.parameters( @@ -305,8 +305,9 @@ def test_input_rank_exception_raised(self, *shapes): def test_flatten_batch_to_2d_exception_raised_types(self): """Check the exception when input is not an integer.""" - with self.assertRaisesRegexp(TypeError, - "'sizes' must have an integer type."): + with self.assertRaisesRegex( + TypeError, "'sizes' must have an integer type." + ): utils.flatten_batch_to_2d(np.ones((3, 4, 3)), np.ones((3,))) @parameterized.parameters( @@ -433,8 +434,9 @@ def test_input_rank_exception_raised(self, *shapes): def test_input_type_exception_raised(self): """Check that invalid input types trigger the right exception.""" - with self.assertRaisesRegexp(TypeError, - "'sizes' must have an integer type."): + with self.assertRaisesRegex( + TypeError, "'sizes' must have an integer type." + ): utils.unflatten_2d_to_batch(np.ones((3, 4)), np.ones((3,))) @parameterized.parameters( @@ -518,11 +520,12 @@ def _validate_sizes(self, block_diag_tensor, sizes): def test_convert_to_block_diag_2d_exception_raised_types(self): """Check the exception when input is not a SparseTensor.""" - with self.assertRaisesRegexp(TypeError, "'data' must be a 'SparseTensor'."): + with self.assertRaisesRegex(TypeError, "'data' must be a 'SparseTensor'."): utils.convert_to_block_diag_2d(np.zeros(shape=(3, 3, 3))) - with self.assertRaisesRegexp(TypeError, - "'sizes' must have an integer type."): + with self.assertRaisesRegex( + TypeError, "'sizes' must have an integer type." + ): utils.convert_to_block_diag_2d( _dense_to_sparse(np.ones(shape=(3, 3, 3))), np.ones(shape=(3, 2)), @@ -530,26 +533,27 @@ def test_convert_to_block_diag_2d_exception_raised_types(self): def test_convert_to_block_diag_2d_exception_raised_ranks(self): """Check the exception when input data rank is invalid.""" - with self.assertRaisesRegexp(ValueError, "must have a rank greater than 2"): + with self.assertRaisesRegex(ValueError, "must have a rank greater than 2"): utils.convert_to_block_diag_2d(_dense_to_sparse(np.ones(shape=(3, 3)))) - with self.assertRaisesRegexp(ValueError, "must have a rank greater than 2"): + with self.assertRaisesRegex(ValueError, "must have a rank greater than 2"): utils.convert_to_block_diag_2d(_dense_to_sparse(np.ones(shape=(3,)))) def test_convert_to_block_diag_2d_exception_raised_sizes(self): """Check the expetion when the shape of sizes is invalid.""" - with self.assertRaisesRegexp(ValueError, "must have a rank of 2"): + with self.assertRaisesRegex(ValueError, "must have a rank of 2"): utils.convert_to_block_diag_2d( _dense_to_sparse(np.ones(shape=(3, 3, 3))), np.ones(shape=(3,), dtype=np.int32)) - with self.assertRaisesRegexp(ValueError, "must have a rank of 3"): + with self.assertRaisesRegex(ValueError, "must have a rank of 3"): utils.convert_to_block_diag_2d( _dense_to_sparse(np.ones(shape=(4, 3, 3, 3))), np.ones(shape=(4, 3), dtype=np.int32)) - with self.assertRaisesRegexp(ValueError, - "must have exactly 2 dimensions in axis -1"): + with self.assertRaisesRegex( + ValueError, "must have exactly 2 dimensions in axis -1" + ): utils.convert_to_block_diag_2d( _dense_to_sparse(np.ones(shape=(3, 3, 3))), np.ones(shape=(3, 1), dtype=np.int32)) diff --git a/tensorflow_graphics/geometry/representation/mesh/tests/sampler_test.py b/tensorflow_graphics/geometry/representation/mesh/tests/sampler_test.py index c6a39b1f9..cdc207459 100644 --- a/tensorflow_graphics/geometry/representation/mesh/tests/sampler_test.py +++ b/tensorflow_graphics/geometry/representation/mesh/tests/sampler_test.py @@ -65,7 +65,7 @@ def test_negative_weights_random_face_indices_exception(self): face_wts = np.array([0.1, -0.1], dtype=np.float32) num_samples = 10 error_msg = "Condition x >= y did not hold." - with self.assertRaisesRegexp(tf.errors.InvalidArgumentError, error_msg): + with self.assertRaisesRegex(tf.errors.InvalidArgumentError, error_msg): sampler.generate_random_face_indices(num_samples, face_weights=face_wts) @parameterized.parameters( @@ -154,7 +154,7 @@ def test_weighted_sampler_negative_weights(self): face_wts = np.array([-0.3, 0.1, 0.5, 0.6], dtype=np.float32) num_samples = 10 error_msg = "Condition x >= y did not hold." - with self.assertRaisesRegexp(tf.errors.InvalidArgumentError, error_msg): + with self.assertRaisesRegex(tf.errors.InvalidArgumentError, error_msg): sampler.weighted_random_sample_triangle_mesh( vertices, faces, num_samples, face_weights=face_wts) diff --git a/tensorflow_graphics/geometry/representation/mesh/tests/utils_test.py b/tensorflow_graphics/geometry/representation/mesh/tests/utils_test.py index 9ced4f2d7..f4ce30b5f 100644 --- a/tensorflow_graphics/geometry/representation/mesh/tests/utils_test.py +++ b/tensorflow_graphics/geometry/representation/mesh/tests/utils_test.py @@ -65,7 +65,7 @@ def test_extract_directed_edges_from_triangular_mesh_preset( def test_extract_edges_from_triangular_mesh_raised( self, invalid_input, error_msg): """Tests that the shape exceptions are properly raised.""" - with self.assertRaisesRegexp(ValueError, error_msg): + with self.assertRaisesRegex(ValueError, error_msg): utils.extract_unique_edges_from_triangular_mesh(invalid_input) @parameterized.parameters( @@ -98,7 +98,7 @@ def test_get_degree_based_edge_weights_preset( def test_get_degree_based_edge_weights_invalid_edges_raised( self, invalid_input, error_msg): """Tests that the shape exceptions are properly raised.""" - with self.assertRaisesRegexp(ValueError, error_msg): + with self.assertRaisesRegex(ValueError, error_msg): utils.get_degree_based_edge_weights(invalid_input) @parameterized.parameters( @@ -111,7 +111,7 @@ def test_get_degree_based_edge_weights_invalid_edges_raised( def test_get_degree_based_edge_weights_dtype_raised( self, invalid_type, error_msg): """Tests that the shape exceptions are properly raised.""" - with self.assertRaisesRegexp(ValueError, error_msg): + with self.assertRaisesRegex(ValueError, error_msg): utils.get_degree_based_edge_weights(np.array(((1, 1),)), invalid_type) if __name__ == "__main__": diff --git a/tensorflow_graphics/geometry/transformation/tests/quaternion_test.py b/tensorflow_graphics/geometry/transformation/tests/quaternion_test.py index 9bd446f22..9b14d5f03 100644 --- a/tensorflow_graphics/geometry/transformation/tests/quaternion_test.py +++ b/tensorflow_graphics/geometry/transformation/tests/quaternion_test.py @@ -508,13 +508,14 @@ def test_normalized_random_initializer_raised(self): tensor_shape = np.random.randint(1, 10, size=(tensor_size)).tolist() with self.subTest(name="dtype"): - with self.assertRaisesRegexp(ValueError, "'dtype' must be tf.float32."): + with self.assertRaisesRegex(ValueError, "'dtype' must be tf.float32."): quaternion.normalized_random_uniform_initializer()( tensor_shape + [4], dtype=tf.uint8) with self.subTest(name="shape"): - with self.assertRaisesRegexp(ValueError, - "Last dimension of 'shape' must be 4."): + with self.assertRaisesRegex( + ValueError, "Last dimension of 'shape' must be 4." + ): quaternion.normalized_random_uniform_initializer()( tensor_shape + [3], dtype=tf.float32) diff --git a/tensorflow_graphics/io/tests/exr_test.py b/tensorflow_graphics/io/tests/exr_test.py index ee577edd9..43acf215d 100644 --- a/tensorflow_graphics/io/tests/exr_test.py +++ b/tensorflow_graphics/io/tests/exr_test.py @@ -79,23 +79,24 @@ def test_write_read_roundtrip(self, num_channels, datatype, pass_channels): def test_reading_mixed_datatypes_fails(self): with tempfile.NamedTemporaryFile() as temp: _WriteMixedDatatypesExr(temp.name) - with self.assertRaisesRegexp(ValueError, 'Channels have mixed datatypes'): + with self.assertRaisesRegex(ValueError, 'Channels have mixed datatypes'): _, _ = exr.read_exr(temp.name) def test_writing_with_array_channel_name_mismatch_fails(self): array_three_channels = np.zeros([64, 64, 3], dtype=np.float32) names_two_channels = ['A', 'B'] with tempfile.NamedTemporaryFile() as temp: - with self.assertRaisesRegexp( + with self.assertRaisesRegex( ValueError, - 'Number of channels in values does not match channel names'): + 'Number of channels in values does not match channel names', + ): exr.write_exr(temp.name, array_three_channels, names_two_channels) def test_writing_unsupported_numpy_type_fails(self): uint8_array = np.zeros([64, 64, 3], dtype=np.uint8) names = ['R', 'G', 'B'] with tempfile.NamedTemporaryFile() as temp: - with self.assertRaisesRegexp(TypeError, 'Unsupported numpy type'): + with self.assertRaisesRegex(TypeError, 'Unsupported numpy type'): exr.write_exr(temp.name, uint8_array, names) def test_reading_unknown_exr_type_fails(self): @@ -109,7 +110,7 @@ def test_reading_unknown_exr_type_fails(self): header_dict['channels']['R'].type.v = -1 # Any bad value will do. make_mock_exr = collections.namedtuple('MockExr', ['header', 'channel']) mock_broken_exr = make_mock_exr(lambda: header_dict, exr_file.channel) - with self.assertRaisesRegexp(RuntimeError, 'Unknown EXR channel type'): + with self.assertRaisesRegex(RuntimeError, 'Unknown EXR channel type'): _ = exr.channels_to_ndarray(mock_broken_exr, ['R', 'G', 'B']) diff --git a/tensorflow_graphics/nn/metric/tests/intersection_over_union_test.py b/tensorflow_graphics/nn/metric/tests/intersection_over_union_test.py index c9906a7f7..73000b25e 100644 --- a/tensorflow_graphics/nn/metric/tests/intersection_over_union_test.py +++ b/tensorflow_graphics/nn/metric/tests/intersection_over_union_test.py @@ -69,8 +69,9 @@ def test_evaluate_preset(self, ground_truth, predictions, expected_iou): def test_evaluate_invalid_argument_exception_raised(self, error_msg, ground_truth, predictions, grid_size): - with self.assertRaisesRegexp((tf.errors.InvalidArgumentError, ValueError), - error_msg): + with self.assertRaisesRegex( + (tf.errors.InvalidArgumentError, ValueError), error_msg + ): self.evaluate( intersection_over_union.evaluate(ground_truth, predictions, grid_size)) diff --git a/tensorflow_graphics/rendering/opengl/tests/rasterizer_op_test.py b/tensorflow_graphics/rendering/opengl/tests/rasterizer_op_test.py index a000e1bed..fe63b680b 100644 --- a/tensorflow_graphics/rendering/opengl/tests/rasterizer_op_test.py +++ b/tensorflow_graphics/rendering/opengl/tests/rasterizer_op_test.py @@ -220,7 +220,7 @@ def test_invalid_variable_inputs(self, error_msg, variable_names, error = error_eager else: error = error_graph_mode - with self.assertRaisesRegexp(error, error_msg): + with self.assertRaisesRegex(error, error_msg): self.evaluate( rasterization_backend.render_ops.rasterize( num_points=0, diff --git a/tensorflow_graphics/rendering/tests/rasterization_backend_test_base.py b/tensorflow_graphics/rendering/tests/rasterization_backend_test_base.py index 5d99ce6c7..00c1ac98d 100644 --- a/tensorflow_graphics/rendering/tests/rasterization_backend_test_base.py +++ b/tensorflow_graphics/rendering/tests/rasterization_backend_test_base.py @@ -97,7 +97,7 @@ def test_rasterizer_return_correct_batch_shapes(self, shapes, dtypes, def test_rasterizer_rasterize_exception_raised(self, shapes, dtypes, backend): """Tests that unsupported backends raise exceptions.""" placeholders = self._create_placeholders(shapes, dtypes) - with self.assertRaisesRegexp(KeyError, 'Backend is not supported'): + with self.assertRaisesRegex(KeyError, 'Backend is not supported'): rasterization_backend.rasterize(placeholders[0], placeholders[1], placeholders[2], (self.IMAGE_WIDTH, self.IMAGE_HEIGHT),