def test_cutmix_batch_fail1(): """ Test CutMixBatch Fail 1 We expect this to fail because the images and labels are not batched """ logger.info("test_cutmix_batch_fail1") # CutMixBatch Images data1 = ds.Cifar10Dataset(DATA_DIR, num_samples=10, shuffle=False) one_hot_op = data_trans.OneHot(num_classes=10) data1 = data1.map(operations=one_hot_op, input_columns=["label"]) cutmix_batch_op = vision.CutMixBatch(mode.ImageBatchFormat.NHWC) with pytest.raises(RuntimeError) as error: data1 = data1.map(operations=cutmix_batch_op, input_columns=["image", "label"]) for idx, (image, _) in enumerate(data1): if idx == 0: images_cutmix = image.asnumpy() else: images_cutmix = np.append(images_cutmix, image.asnumpy(), axis=0) error_message = "You must make sure images are HWC or CHW and batch " assert error_message in str(error.value)
def test_cutmix_batch_fail7(): """ Test CutMixBatch op We expect this to fail because labels are not in one-hot format """ logger.info("test_cutmix_batch_fail7") # CutMixBatch Images data1 = ds.Cifar10Dataset(DATA_DIR, num_samples=10, shuffle=False) cutmix_batch_op = vision.CutMixBatch(mode.ImageBatchFormat.NHWC) data1 = data1.batch(5, drop_remainder=True) data1 = data1.map(operations=cutmix_batch_op, input_columns=["image", "label"]) with pytest.raises(RuntimeError) as error: images_cutmix = np.array([]) for idx, (image, _) in enumerate(data1): if idx == 0: images_cutmix = image.asnumpy() else: images_cutmix = np.append(images_cutmix, image.asnumpy(), axis=0) error_message = "wrong labels shape. The second column (labels) must have a shape of NC or NLC" assert error_message in str(error.value)
def test_cutmix_batch_nhwc_md5(): """ Test CutMixBatch on a batch of HWC images with MD5: """ logger.info("test_cutmix_batch_nhwc_md5") original_seed = config_get_set_seed(0) original_num_parallel_workers = config_get_set_num_parallel_workers(1) # CutMixBatch Images data = ds.Cifar10Dataset(DATA_DIR, num_samples=10, shuffle=False) one_hot_op = data_trans.OneHot(num_classes=10) data = data.map(operations=one_hot_op, input_columns=["label"]) cutmix_batch_op = vision.CutMixBatch(mode.ImageBatchFormat.NHWC) data = data.batch(5, drop_remainder=True) data = data.map(operations=cutmix_batch_op, input_columns=["image", "label"]) filename = "cutmix_batch_c_nhwc_result.npz" save_and_check_md5(data, filename, generate_golden=GENERATE_GOLDEN) # Restore config setting ds.config.set_seed(original_seed) ds.config.set_num_parallel_workers(original_num_parallel_workers)