2020-05-14 07:31:55 +08:00
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# Copyright 2019 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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import numpy as np
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import mindspore.dataset as ds
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2020-08-28 03:30:21 +08:00
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from util import config_get_set_seed, config_get_set_num_parallel_workers
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2020-05-14 07:31:55 +08:00
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2020-05-22 13:23:13 +08:00
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2020-05-14 07:31:55 +08:00
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# Generate 1d int numpy array from 0 - 63
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def generator_1d():
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2020-08-28 03:30:21 +08:00
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for i in range(4):
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2020-05-14 07:31:55 +08:00
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yield (np.array([i]),)
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def test_case_0():
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"""
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2020-08-28 03:30:21 +08:00
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Test 1D Generator.
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Test without explicit kwargs for input args.
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2020-05-14 07:31:55 +08:00
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"""
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2020-08-28 03:30:21 +08:00
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original_seed = config_get_set_seed(55)
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original_num_parallel_workers = config_get_set_num_parallel_workers(1)
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2020-05-14 07:31:55 +08:00
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2020-08-28 03:30:21 +08:00
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# apply dataset qoperations
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2020-05-14 07:31:55 +08:00
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data1 = ds.GeneratorDataset(generator_1d, ["data"])
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data1 = data1.shuffle(2)
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2020-08-28 03:30:21 +08:00
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data1 = data1.map((lambda x: x), ["data"])
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2020-05-14 07:31:55 +08:00
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data1 = data1.batch(2)
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2020-08-28 03:30:21 +08:00
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expected_data = np.array([[[1], [2]], [[3], [0]]])
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2021-09-21 06:26:05 +08:00
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for i, data_row in enumerate(data1.create_tuple_iterator(num_epochs=1, output_numpy=True)):
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2020-08-28 03:30:21 +08:00
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np.testing.assert_array_equal(data_row[0], expected_data[i])
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# Restore configuration
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ds.config.set_seed(original_seed)
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ds.config.set_num_parallel_workers((original_num_parallel_workers))
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2020-05-14 07:31:55 +08:00
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if __name__ == "__main__":
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2020-05-22 13:23:13 +08:00
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test_case_0()
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