/third_party/boost/libs/compute/test/ |
D | test_is_permutation.cpp | 30 bc::int_ dataset2[] = {3, 1, 5, 1, 2}; in BOOST_AUTO_TEST_CASE() local 31 bc::vector<bc::int_> vector2(dataset2, dataset2 + 5, queue); in BOOST_AUTO_TEST_CASE() 53 bc::char_ dataset2[] = "aadeb"; in BOOST_AUTO_TEST_CASE() local 54 bc::vector<bc::char_> vector2(dataset2, dataset2 + 5, queue); in BOOST_AUTO_TEST_CASE()
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D | test_set_symmetric_difference.cpp | 29 int dataset2[] = {0, 2, 2, 4, 5, 6, 8, 8, 9, 9, 9, 13}; in BOOST_AUTO_TEST_CASE() local 30 bc::vector<bc::int_> set2(dataset2, dataset2 + 12, queue); in BOOST_AUTO_TEST_CASE()
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D | test_set_difference.cpp | 29 int dataset2[] = {0, 2, 2, 4, 5, 6, 8, 8, 9, 9, 9, 13}; in BOOST_AUTO_TEST_CASE() local 30 bc::vector<bc::int_> set2(dataset2, dataset2 + 12, queue); in BOOST_AUTO_TEST_CASE()
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D | test_set_intersection.cpp | 29 int dataset2[] = {0, 2, 2, 4, 5, 6, 8, 8, 9, 9, 9, 13}; in BOOST_AUTO_TEST_CASE() local 30 bc::vector<bc::int_> set2(dataset2, dataset2 + 12, queue); in BOOST_AUTO_TEST_CASE()
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D | test_includes.cpp | 29 int dataset2[] = {2, 4, 5, 6}; in BOOST_AUTO_TEST_CASE() local 30 bc::vector<bc::int_> set2(dataset2, dataset2 + 4, queue); in BOOST_AUTO_TEST_CASE()
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D | test_set_union.cpp | 29 int dataset2[] = {0, 2, 2, 4, 5, 6, 8, 8, 9, 9, 9, 13}; in BOOST_AUTO_TEST_CASE() local 30 bc::vector<bc::int_> set2(dataset2, dataset2 + 12, queue); in BOOST_AUTO_TEST_CASE()
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/third_party/mindspore/tests/ut/python/dataset/ |
D | test_sync_wait.py | 145 dataset2 = ds.GeneratorDataset(gen, column_names=["input"]) 148 dataset2 = dataset2.sync_wait(condition_name="policy", callback=aug.update) 149 dataset2 = dataset2.map(operations=[aug.preprocess], input_columns=["input"]) 150 dataset2 = dataset2.batch(batch_size, drop_remainder=True) 153 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)): 158 dataset2.sync_update(condition_name="policy", data=data2)
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D | test_vertical_flip.py | 45 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 46 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 50 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_horizontal_flip.py | 45 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 46 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 50 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_slice_patches.py | 88 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) 89 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 90 dataset2 = dataset2.map(operations=resize_op, input_columns=["image"]) 93 dataset2 = dataset2.map(operations=func_slice_patches, 100 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_convertcolor.py | 43 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 44 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 48 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_filterop.py | 200 dataset2 = ds.GeneratorDataset(generator_1d_zip2, ["data2"]) 201 dataz = ds.zip((dataset1, dataset2)) 218 dataset2 = ds.GeneratorDataset(generator_1d_zip1, ["data2"]) 220 dt2 = dataset2.filter(predicate=filter_func_zip_after, num_parallel_workers=4) 368 dataset2 = ds.GeneratorDataset(source=generator_mc_p1(), column_names=["col3", "col4"]) 369 dataset_zip = ds.zip((dataset1, dataset2)) 381 dataset2 = ds.GeneratorDataset(source=generator_mc_p1(), column_names=["col3", "col4"]) 382 dataset_zip = ds.zip((dataset1, dataset2)) 395 dataset2 = ds.GeneratorDataset(source=generator_mc_p1(), column_names=["col3", "col4"]) 398 … dataset2f = dataset2.filter(input_columns=["col3"], predicate=lambda x: x not in [203, 207, 209], [all …]
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D | test_gaussian_blur.py | 45 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 46 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 50 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_crop.py | 45 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 46 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 50 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_rotate.py | 45 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 46 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 50 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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D | test_decode.py | 105 dataset2 = ds.GeneratorDataset(ImageDataset(data_path, data_type="bytes"), ["data", "label"]) 109 dataset2 = dataset2.map(operations=[decode_op, to_tensor], input_columns=["data"]) 111 for item1, item2 in zip(dataset1, dataset2):
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D | test_datasets_get_dataset_size.py | 262 dataset2 = ds.MnistDataset(MNIST_DATA_DIR, num_samples=3000, num_shards=4, shard_id=0) 263 assert dataset2.get_dataset_size() == 2500 266 for _ in dataset2.create_dict_iterator():
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D | test_datasets_voc.py | 175 dataset1, dataset2 = data1.split(sizes=sizes, randomize=randomize) 183 for _ in dataset2.create_dict_iterator(num_epochs=1, output_numpy=True):
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D | test_datasets_coco.py | 236 dataset1, dataset2 = data1.split(sizes=sizes, randomize=randomize) 243 for _ in dataset2.create_dict_iterator(num_epochs=1):
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/third_party/mindspore/tests/st/mix_precision/ |
D | test_mix_precision.py | 154 dataset2 = FakeData(size=32, 179 model_pynative.train(1, dataset2, dataset_sink_mode=False)
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