| @@ -14,6 +14,7 @@ | |||
| * limitations under the License. | |||
| */ | |||
| #include <algorithm> | |||
| #include <cmath> | |||
| #include <random> | |||
| #include <utility> | |||
| #include <vector> | |||
| @@ -72,7 +73,7 @@ Status RandomAffineOp::Compute(const std::shared_ptr<Tensor> &input, std::shared | |||
| float_t shear_y = 0.0; | |||
| RETURN_IF_NOT_OK(GenerateRealNumber(shear_ranges_[2], shear_ranges_[3], &rnd_, &shear_y)); | |||
| // assign to base class variables | |||
| degrees_ = degrees; | |||
| degrees_ = fmod(degrees, 360.0); | |||
| scale_ = scale; | |||
| translation_[0] = translation_x; | |||
| translation_[1] = translation_y; | |||
| @@ -44,6 +44,7 @@ valid_detype = [ | |||
| "uint32", "uint64", "float16", "float32", "float64", "string" | |||
| ] | |||
| def is_iterable(obj): | |||
| """ | |||
| Helper function to check if object is iterable. | |||
| @@ -60,6 +61,7 @@ def is_iterable(obj): | |||
| return False | |||
| return True | |||
| def pad_arg_name(arg_name): | |||
| if arg_name != "": | |||
| arg_name = arg_name + " " | |||
| @@ -70,8 +72,8 @@ def check_value(value, valid_range, arg_name=""): | |||
| arg_name = pad_arg_name(arg_name) | |||
| if value < valid_range[0] or value > valid_range[1]: | |||
| raise ValueError( | |||
| "Input {0}is not within the required interval of ({1} to {2}).".format(arg_name, valid_range[0], | |||
| valid_range[1])) | |||
| "Input {0}is not within the required interval of [{1}, {2}].".format(arg_name, valid_range[0], | |||
| valid_range[1])) | |||
| def check_value_cutoff(value, valid_range, arg_name=""): | |||
| @@ -86,16 +88,16 @@ def check_value_normalize_std(value, valid_range, arg_name=""): | |||
| arg_name = pad_arg_name(arg_name) | |||
| if value <= valid_range[0] or value > valid_range[1]: | |||
| raise ValueError( | |||
| "Input {0}is not within the required interval of ({1} to {2}).".format(arg_name, valid_range[0], | |||
| valid_range[1])) | |||
| "Input {0}is not within the required interval of ({1}, {2}].".format(arg_name, valid_range[0], | |||
| valid_range[1])) | |||
| def check_range(values, valid_range, arg_name=""): | |||
| arg_name = pad_arg_name(arg_name) | |||
| if not valid_range[0] <= values[0] <= values[1] <= valid_range[1]: | |||
| raise ValueError( | |||
| "Input {0}is not within the required interval of ({1} to {2}).".format(arg_name, valid_range[0], | |||
| valid_range[1])) | |||
| "Input {0}is not within the required interval of [{1}, {2}].".format(arg_name, valid_range[0], | |||
| valid_range[1])) | |||
| def check_positive(value, arg_name=""): | |||
| @@ -506,12 +506,12 @@ class Dataset: | |||
| Dataset, dataset applied by the function. | |||
| Examples: | |||
| >>> # use NumpySliceDataset as an example | |||
| >>> # use NumpySlicesDataset as an example | |||
| >>> dataset = ds.NumpySlicesDataset([[0, 1], [2, 3]]) | |||
| >>> | |||
| >>> def flat_map_func(array): | |||
| ... # create a NumpySliceDataset with the array | |||
| ... dataset = ds.NumpySliceDataset(array) | |||
| ... # create a NumpySlicesDataset with the array | |||
| ... dataset = ds.NumpySlicesDataset(array) | |||
| ... # repeat the dataset twice | |||
| ... dataset = dataset.repeat(2) | |||
| ... return dataset | |||
| @@ -3429,6 +3429,8 @@ class GeneratorDataset(MappableDataset): | |||
| option could be beneficial if the Python operation is computational heavy (default=True). | |||
| Examples: | |||
| >>> import numpy as np | |||
| >>> | |||
| >>> # 1) Multidimensional generator function as callable input. | |||
| >>> def generator_multidimensional(): | |||
| ... for i in range(64): | |||
| @@ -24,18 +24,16 @@ and use Lookup to find the index of tokens in Vocab. | |||
| class attributes (self.xxx) to support save() and load(). | |||
| Examples: | |||
| >>> text_file_dataset_dir = "/path/to/text_file_dataset_file" | |||
| >>> text_file_dataset_dir = ["/path/to/text_file_dataset_file"] # contains 1 or multiple text files | |||
| >>> # Create a dataset for text sentences saved as line data in a file | |||
| >>> text_file_dataset = ds.TextFileDataset(text_file_dataset_dir, shuffle=False) | |||
| >>> text_file_dataset = ds.TextFileDataset(dataset_files=text_file_dataset_dir, shuffle=False) | |||
| >>> # Tokenize sentences to unicode characters | |||
| >>> tokenizer = text.UnicodeCharTokenizer() | |||
| >>> # Load vocabulary from list | |||
| >>> vocab = text.Vocab.from_list(['深', '圳', '欢', '迎', '您']) | |||
| >>> vocab = text.Vocab.from_list(word_list=['深', '圳', '欢', '迎', '您']) | |||
| >>> # Use Lookup operator to map tokens to ids | |||
| >>> lookup = text.Lookup(vocab) | |||
| >>> lookup = text.Lookup(vocab=vocab) | |||
| >>> text_file_dataset = text_file_dataset.map(operations=[tokenizer, lookup]) | |||
| >>> for i in text_file_dataset.create_dict_iterator(): | |||
| ... print(i) | |||
| >>> # if text line in dataset_file is: | |||
| >>> # 深圳欢迎您 | |||
| >>> # then the output will be: | |||
| @@ -125,10 +125,12 @@ def check_degrees(degrees): | |||
| """Check if the degrees is legal.""" | |||
| type_check(degrees, (numbers.Number, list, tuple), "degrees") | |||
| if isinstance(degrees, numbers.Number): | |||
| check_value(degrees, (0, float("inf")), "degrees") | |||
| check_pos_float32(degrees, "degrees") | |||
| elif isinstance(degrees, (list, tuple)): | |||
| if len(degrees) == 2: | |||
| type_check_list(degrees, (numbers.Number,), "degrees") | |||
| for value in degrees: | |||
| check_float32(value, "degrees") | |||
| if degrees[0] > degrees[1]: | |||
| raise ValueError("degrees should be in (min,max) format. Got (max,min).") | |||
| else: | |||
| @@ -477,7 +477,7 @@ def test_batch_exception_15(): | |||
| _ = data1.batch(batch_size=batch_size, input_columns=input_columns) | |||
| except ValueError as e: | |||
| err_msg = str(e) | |||
| assert "batch_size is not within the required interval of (1 to 2147483647)" in err_msg | |||
| assert "batch_size is not within the required interval of [1, 2147483647]" in err_msg | |||
| if __name__ == '__main__': | |||
| @@ -243,7 +243,7 @@ def test_bounding_box_augment_invalid_ratio_c(): | |||
| column_order=["image", "bbox"]) # Add column for "bbox" | |||
| except ValueError as error: | |||
| logger.info("Got an exception in DE: {}".format(str(error))) | |||
| assert "Input ratio is not within the required interval of (0.0 to 1.0)." in str(error) | |||
| assert "Input ratio is not within the required interval of [0.0, 1.0]." in str(error) | |||
| def test_bounding_box_augment_invalid_bounds_c(): | |||
| @@ -181,7 +181,7 @@ def test_numpy_slices_distributed_shard_limit(): | |||
| num = sys.maxsize | |||
| with pytest.raises(ValueError) as err: | |||
| de.NumpySlicesDataset(np_data, num_shards=num, shard_id=0, shuffle=False) | |||
| assert "Input num_shards is not within the required interval of (1 to 2147483647)." in str(err.value) | |||
| assert "Input num_shards is not within the required interval of [1, 2147483647]." in str(err.value) | |||
| def test_numpy_slices_distributed_zero_shard(): | |||
| @@ -190,7 +190,7 @@ def test_numpy_slices_distributed_zero_shard(): | |||
| np_data = [1, 2, 3] | |||
| with pytest.raises(ValueError) as err: | |||
| de.NumpySlicesDataset(np_data, num_shards=0, shard_id=0, shuffle=False) | |||
| assert "Input num_shards is not within the required interval of (1 to 2147483647)." in str(err.value) | |||
| assert "Input num_shards is not within the required interval of [1, 2147483647]." in str(err.value) | |||
| def test_numpy_slices_sequential_sampler(): | |||
| @@ -201,7 +201,7 @@ def test_minddataset_invalidate_num_shards(): | |||
| for _ in data_set.create_dict_iterator(num_epochs=1): | |||
| num_iter += 1 | |||
| try: | |||
| assert 'Input shard_id is not within the required interval of (0 to 0).' in str(error_info.value) | |||
| assert 'Input shard_id is not within the required interval of [0, 0].' in str(error_info.value) | |||
| except Exception as error: | |||
| os.remove(CV_FILE_NAME) | |||
| os.remove("{}.db".format(CV_FILE_NAME)) | |||
| @@ -221,7 +221,7 @@ def test_minddataset_invalidate_shard_id(): | |||
| for _ in data_set.create_dict_iterator(num_epochs=1): | |||
| num_iter += 1 | |||
| try: | |||
| assert 'Input shard_id is not within the required interval of (0 to 0).' in str(error_info.value) | |||
| assert 'Input shard_id is not within the required interval of [0, 0].' in str(error_info.value) | |||
| except Exception as error: | |||
| os.remove(CV_FILE_NAME) | |||
| os.remove("{}.db".format(CV_FILE_NAME)) | |||
| @@ -241,7 +241,7 @@ def test_minddataset_shard_id_bigger_than_num_shard(): | |||
| for _ in data_set.create_dict_iterator(num_epochs=1): | |||
| num_iter += 1 | |||
| try: | |||
| assert 'Input shard_id is not within the required interval of (0 to 1).' in str(error_info.value) | |||
| assert 'Input shard_id is not within the required interval of [0, 1].' in str(error_info.value) | |||
| except Exception as error: | |||
| os.remove(CV_FILE_NAME) | |||
| os.remove("{}.db".format(CV_FILE_NAME)) | |||
| @@ -253,7 +253,7 @@ def test_minddataset_shard_id_bigger_than_num_shard(): | |||
| for _ in data_set.create_dict_iterator(num_epochs=1): | |||
| num_iter += 1 | |||
| try: | |||
| assert 'Input shard_id is not within the required interval of (0 to 1).' in str(error_info.value) | |||
| assert 'Input shard_id is not within the required interval of [0, 1].' in str(error_info.value) | |||
| except Exception as error: | |||
| os.remove(CV_FILE_NAME) | |||
| os.remove("{}.db".format(CV_FILE_NAME)) | |||
| @@ -277,6 +277,7 @@ def test_cv_minddataset_partition_num_samples_equals_0(): | |||
| num_iter = 0 | |||
| for _ in data_set.create_dict_iterator(num_epochs=1): | |||
| num_iter += 1 | |||
| with pytest.raises(ValueError) as error_info: | |||
| partitions(5) | |||
| try: | |||
| @@ -289,8 +290,10 @@ def test_cv_minddataset_partition_num_samples_equals_0(): | |||
| os.remove(CV_FILE_NAME) | |||
| os.remove("{}.db".format(CV_FILE_NAME)) | |||
| def test_mindrecord_exception(): | |||
| """tutorial for exception scenario of minderdataset + map would print error info.""" | |||
| def exception_func(item): | |||
| raise Exception("Error occur!") | |||
| @@ -33,7 +33,7 @@ def normalize_np(image, mean, std): | |||
| """ | |||
| Apply the normalization | |||
| """ | |||
| # DE decodes the image in RGB by deafult, hence | |||
| # DE decodes the image in RGB by default, hence | |||
| # the values here are in RGB | |||
| image = np.array(image, np.float32) | |||
| image = image - np.array(mean) | |||
| @@ -300,7 +300,7 @@ def test_normalize_exception_invalid_range_py(): | |||
| _ = py_vision.Normalize([0.75, 1.25, 0.5], [0.1, 0.18, 1.32]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input mean_value is not within the required interval of (0.0 to 1.0)." in str(e) | |||
| assert "Input mean_value is not within the required interval of [0.0, 1.0]." in str(e) | |||
| def test_normalize_grayscale_md5_01(): | |||
| @@ -33,7 +33,7 @@ def normalizepad_np(image, mean, std): | |||
| """ | |||
| Apply the normalize+pad | |||
| """ | |||
| # DE decodes the image in RGB by deafult, hence | |||
| # DE decodes the image in RGB by default, hence | |||
| # the values here are in RGB | |||
| image = np.array(image, np.float32) | |||
| image = image - np.array(mean) | |||
| @@ -198,4 +198,4 @@ def test_normalizepad_exception_invalid_range_py(): | |||
| _ = py_vision.NormalizePad([0.75, 1.25, 0.5], [0.1, 0.18, 1.32]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input mean_value is not within the required interval of (0.0 to 1.0)." in str(e) | |||
| assert "Input mean_value is not within the required interval of [0.0, 1.0]." in str(e) | |||
| @@ -211,7 +211,7 @@ def test_random_affine_exception_negative_degrees(): | |||
| _ = py_vision.RandomAffine(degrees=-15) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input degrees is not within the required interval of (0 to inf)." | |||
| assert str(e) == "Input degrees is not within the required interval of [0, 16777216]." | |||
| def test_random_affine_exception_translation_range(): | |||
| @@ -223,13 +223,13 @@ def test_random_affine_exception_translation_range(): | |||
| _ = c_vision.RandomAffine(degrees=15, translate=(0.1, 1.5)) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input translate at 1 is not within the required interval of (-1.0 to 1.0)." | |||
| assert str(e) == "Input translate at 1 is not within the required interval of [-1.0, 1.0]." | |||
| logger.info("test_random_affine_exception_translation_range") | |||
| try: | |||
| _ = c_vision.RandomAffine(degrees=15, translate=(-2, 1.5)) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input translate at 0 is not within the required interval of (-1.0 to 1.0)." | |||
| assert str(e) == "Input translate at 0 is not within the required interval of [-1.0, 1.0]." | |||
| def test_random_affine_exception_scale_value(): | |||
| @@ -260,7 +260,7 @@ def test_random_crop_with_bbox_op_bad_padding(): | |||
| break | |||
| except ValueError as err: | |||
| logger.info("Got an exception in DE: {}".format(str(err))) | |||
| assert "Input padding is not within the required interval of (0 to 2147483647)." in str(err) | |||
| assert "Input padding is not within the required interval of [0, 2147483647]." in str(err) | |||
| try: | |||
| test_op = c_vision.RandomCropWithBBox([512, 512], padding=[16777216, 16777216, 16777216, 16777216]) | |||
| @@ -188,7 +188,7 @@ def test_random_grayscale_invalid_param(): | |||
| data = data.map(operations=transform, input_columns=["image"]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input prob is not within the required interval of (0.0 to 1.0)." in str(e) | |||
| assert "Input prob is not within the required interval of [0.0, 1.0]." in str(e) | |||
| if __name__ == "__main__": | |||
| @@ -143,7 +143,7 @@ def test_random_horizontal_invalid_prob_c(): | |||
| data = data.map(operations=random_horizontal_op, input_columns=["image"]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input prob is not within the required interval of (0.0 to 1.0)." in str(e) | |||
| assert "Input prob is not within the required interval of [0.0, 1.0]." in str(e) | |||
| def test_random_horizontal_invalid_prob_py(): | |||
| @@ -166,7 +166,7 @@ def test_random_horizontal_invalid_prob_py(): | |||
| data = data.map(operations=transform, input_columns=["image"]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input prob is not within the required interval of (0.0 to 1.0)." in str(e) | |||
| assert "Input prob is not within the required interval of [0.0, 1.0]." in str(e) | |||
| def test_random_horizontal_comp(plot=False): | |||
| @@ -185,7 +185,7 @@ def test_random_horizontal_flip_with_bbox_invalid_prob_c(): | |||
| column_order=["image", "bbox"]) # Add column for "bbox" | |||
| except ValueError as error: | |||
| logger.info("Got an exception in DE: {}".format(str(error))) | |||
| assert "Input prob is not within the required interval of (0.0 to 1.0)." in str(error) | |||
| assert "Input prob is not within the required interval of [0.0, 1.0]." in str(error) | |||
| def test_random_horizontal_flip_with_bbox_invalid_bounds_c(): | |||
| @@ -24,7 +24,6 @@ from mindspore import log as logger | |||
| from util import visualize_list, save_and_check_md5, \ | |||
| config_get_set_seed, config_get_set_num_parallel_workers | |||
| GENERATE_GOLDEN = False | |||
| DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"] | |||
| @@ -82,7 +81,7 @@ def skip_test_random_perspective_md5(): | |||
| py_vision.Decode(), | |||
| py_vision.RandomPerspective(distortion_scale=0.3, prob=0.7, | |||
| interpolation=Inter.BILINEAR), | |||
| py_vision.Resize(1450), # resize to a smaller size to prevent round-off error | |||
| py_vision.Resize(1450), # resize to a smaller size to prevent round-off error | |||
| py_vision.ToTensor() | |||
| ] | |||
| transform = mindspore.dataset.transforms.py_transforms.Compose(transforms) | |||
| @@ -109,7 +108,7 @@ def test_random_perspective_exception_distortion_scale_range(): | |||
| _ = py_vision.RandomPerspective(distortion_scale=1.5) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input distortion_scale is not within the required interval of (0.0 to 1.0)." | |||
| assert str(e) == "Input distortion_scale is not within the required interval of [0.0, 1.0]." | |||
| def test_random_perspective_exception_prob_range(): | |||
| @@ -121,7 +120,7 @@ def test_random_perspective_exception_prob_range(): | |||
| _ = py_vision.RandomPerspective(prob=1.2) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input prob is not within the required interval of (0.0 to 1.0)." | |||
| assert str(e) == "Input prob is not within the required interval of [0.0, 1.0]." | |||
| if __name__ == "__main__": | |||
| @@ -168,19 +168,19 @@ def test_random_posterize_exception_bit(): | |||
| _ = c_vision.RandomPosterize((1, 9)) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input is not within the required interval of (1 to 8)." | |||
| assert str(e) == "Input is not within the required interval of [1, 8]." | |||
| # Test min < 1 | |||
| try: | |||
| _ = c_vision.RandomPosterize((0, 7)) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input is not within the required interval of (1 to 8)." | |||
| assert str(e) == "Input is not within the required interval of [1, 8]." | |||
| # Test max < min | |||
| try: | |||
| _ = c_vision.RandomPosterize((8, 1)) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert str(e) == "Input is not within the required interval of (1 to 8)." | |||
| assert str(e) == "Input is not within the required interval of [1, 8]." | |||
| # Test wrong type (not uint8) | |||
| try: | |||
| _ = c_vision.RandomPosterize(1.1) | |||
| @@ -160,7 +160,7 @@ def test_random_resize_with_bbox_op_invalid_c(): | |||
| except ValueError as err: | |||
| logger.info("Got an exception in DE: {}".format(str(err))) | |||
| assert "Input is not within the required interval of (1 to 16777216)." in str(err) | |||
| assert "Input is not within the required interval of [1, 16777216]." in str(err) | |||
| try: | |||
| # one of the size values is zero | |||
| @@ -168,7 +168,7 @@ def test_random_resize_with_bbox_op_invalid_c(): | |||
| except ValueError as err: | |||
| logger.info("Got an exception in DE: {}".format(str(err))) | |||
| assert "Input size at dim 0 is not within the required interval of (1 to 2147483647)." in str(err) | |||
| assert "Input size at dim 0 is not within the required interval of [1, 2147483647]." in str(err) | |||
| try: | |||
| # negative value for resize | |||
| @@ -176,7 +176,7 @@ def test_random_resize_with_bbox_op_invalid_c(): | |||
| except ValueError as err: | |||
| logger.info("Got an exception in DE: {}".format(str(err))) | |||
| assert "Input is not within the required interval of (1 to 16777216)." in str(err) | |||
| assert "Input is not within the required interval of [1, 16777216]." in str(err) | |||
| try: | |||
| # invalid input shape | |||
| @@ -42,8 +42,8 @@ def test_random_select_subpolicy(): | |||
| assert "policy can not be empty." in test_config([[1, 2, 3]], []) | |||
| assert "policy[0] can not be empty." in test_config([[1, 2, 3]], [[]]) | |||
| assert "op of (op, prob) in policy[1][0] is neither a c_transform op (TensorOperation) nor a callable pyfunc" \ | |||
| in test_config([[1, 2, 3]], [[(ops.PadEnd([4], 0), 0.5)], [(1, 0.4)]]) | |||
| assert "prob of (op, prob) policy[1][0] is not within the required interval of (0 to 1)" in test_config([[1]], [ | |||
| in test_config([[1, 2, 3]], [[(ops.PadEnd([4], 0), 0.5)], [(1, 0.4)]]) | |||
| assert "prob of (op, prob) policy[1][0] is not within the required interval of [0, 1]" in test_config([[1]], [ | |||
| [(ops.Duplicate(), 0)], [(ops.Duplicate(), -0.1)]]) | |||
| @@ -110,7 +110,7 @@ def test_random_solarize_errors(): | |||
| with pytest.raises(ValueError) as error_info: | |||
| vision.RandomSolarize((12, 1000)) | |||
| assert "Input is not within the required interval of (0 to 255)." in str(error_info.value) | |||
| assert "Input is not within the required interval of [0, 255]." in str(error_info.value) | |||
| with pytest.raises(TypeError) as error_info: | |||
| vision.RandomSolarize((122.1, 140)) | |||
| @@ -143,7 +143,7 @@ def test_random_vertical_invalid_prob_c(): | |||
| data = data.map(operations=random_horizontal_op, input_columns=["image"]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert 'Input prob is not within the required interval of (0.0 to 1.0).' in str(e) | |||
| assert 'Input prob is not within the required interval of [0.0, 1.0].' in str(e) | |||
| def test_random_vertical_invalid_prob_py(): | |||
| @@ -165,7 +165,7 @@ def test_random_vertical_invalid_prob_py(): | |||
| data = data.map(operations=transform, input_columns=["image"]) | |||
| except ValueError as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert 'Input prob is not within the required interval of (0.0 to 1.0).' in str(e) | |||
| assert 'Input prob is not within the required interval of [0.0, 1.0].' in str(e) | |||
| def test_random_vertical_comp(plot=False): | |||
| @@ -187,7 +187,7 @@ def test_random_vertical_flip_with_bbox_op_invalid_c(): | |||
| except ValueError as err: | |||
| logger.info("Got an exception in DE: {}".format(str(err))) | |||
| assert "Input prob is not within the required interval of (0.0 to 1.0)." in str(err) | |||
| assert "Input prob is not within the required interval of [0.0, 1.0]." in str(err) | |||
| def test_random_vertical_flip_with_bbox_op_bad_c(): | |||
| @@ -149,7 +149,7 @@ def test_shuffle_exception_01(): | |||
| except Exception as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input buffer_size is not within the required interval of (2 to 2147483647)" in str(e) | |||
| assert "Input buffer_size is not within the required interval of [2, 2147483647]" in str(e) | |||
| def test_shuffle_exception_02(): | |||
| @@ -167,7 +167,7 @@ def test_shuffle_exception_02(): | |||
| except Exception as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input buffer_size is not within the required interval of (2 to 2147483647)" in str(e) | |||
| assert "Input buffer_size is not within the required interval of [2, 2147483647]" in str(e) | |||
| def test_shuffle_exception_03(): | |||
| @@ -185,7 +185,7 @@ def test_shuffle_exception_03(): | |||
| except Exception as e: | |||
| logger.info("Got an exception in DE: {}".format(str(e))) | |||
| assert "Input buffer_size is not within the required interval of (2 to 2147483647)" in str(e) | |||
| assert "Input buffer_size is not within the required interval of [2, 2147483647]" in str(e) | |||
| def test_shuffle_exception_05(): | |||
| @@ -146,7 +146,7 @@ def test_ten_crop_invalid_size_error_msg(): | |||
| vision.TenCrop(0), | |||
| lambda images: np.stack([vision.ToTensor()(image) for image in images]) # 4D stack of 10 images | |||
| ] | |||
| error_msg = "Input is not within the required interval of (1 to 16777216)." | |||
| error_msg = "Input is not within the required interval of [1, 16777216]." | |||
| assert error_msg == str(info.value) | |||
| with pytest.raises(ValueError) as info: | |||