# Copyright 2019 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== import mindspore.dataset as ds from mindspore import log as logger from util import save_and_check_dict DATA_DIR = ["../data/dataset/testTFTestAllTypes/test.data"] SCHEMA_DIR = "../data/dataset/testTFTestAllTypes/datasetSchema.json" GENERATE_GOLDEN = False def test_2ops_repeat_shuffle(): """ Test Repeat then Shuffle """ logger.info("Test Repeat then Shuffle") # define parameters repeat_count = 2 buffer_size = 5 seed = 0 # apply dataset operations data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) data1 = data1.repeat(repeat_count) ds.config.set_seed(seed) data1 = data1.shuffle(buffer_size=buffer_size) filename = "test_2ops_repeat_shuffle.npz" save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN) def test_2ops_shuffle_repeat(): """ Test Shuffle then Repeat """ logger.info("Test Shuffle then Repeat") # define parameters repeat_count = 2 buffer_size = 5 seed = 0 # apply dataset operations data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) ds.config.set_seed(seed) data1 = data1.shuffle(buffer_size=buffer_size) data1 = data1.repeat(repeat_count) filename = "test_2ops_shuffle_repeat.npz" save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN) def test_2ops_repeat_batch(): """ Test Repeat then Batch """ logger.info("Test Repeat then Batch") # define parameters repeat_count = 2 batch_size = 5 # apply dataset operations data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) data1 = data1.repeat(repeat_count) data1 = data1.batch(batch_size, drop_remainder=True) filename = "test_2ops_repeat_batch.npz" save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN) def test_2ops_batch_repeat(): """ Test Batch then Repeat """ logger.info("Test Batch then Repeat") # define parameters repeat_count = 2 batch_size = 5 # apply dataset operations data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) data1 = data1.batch(batch_size, drop_remainder=True) data1 = data1.repeat(repeat_count) filename = "test_2ops_batch_repeat.npz" save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN) def test_2ops_batch_shuffle(): """ Test Batch then Shuffle """ logger.info("Test Batch then Shuffle") # define parameters buffer_size = 5 seed = 0 batch_size = 2 # apply dataset operations data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) data1 = data1.batch(batch_size, drop_remainder=True) ds.config.set_seed(seed) data1 = data1.shuffle(buffer_size=buffer_size) filename = "test_2ops_batch_shuffle.npz" save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN) def test_2ops_shuffle_batch(): """ Test Shuffle then Batch """ logger.info("Test Shuffle then Batch") # define parameters buffer_size = 5 seed = 0 batch_size = 2 # apply dataset operations data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) ds.config.set_seed(seed) data1 = data1.shuffle(buffer_size=buffer_size) data1 = data1.batch(batch_size, drop_remainder=True) filename = "test_2ops_shuffle_batch.npz" save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN) if __name__ == '__main__': test_2ops_repeat_shuffle() test_2ops_shuffle_repeat() test_2ops_repeat_batch() test_2ops_batch_repeat() test_2ops_batch_shuffle() test_2ops_shuffle_batch()