forked from mindspore-Ecosystem/mindspore
91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
# 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 mindspore.common.dtype as mstype
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import mindspore.dataset as ds
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from mindspore import log as logger
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# just a basic test with parallel random data op
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def test_randomdataset_basic1():
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logger.info("Test randomdataset basic 1")
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schema = ds.Schema()
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schema.add_column('image', de_type=mstype.uint8, shape=[2])
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schema.add_column('label', de_type=mstype.uint8, shape=[1])
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# apply dataset operations
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ds1 = ds.RandomDataset(schema=schema, total_rows=50, num_parallel_workers=4)
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ds1 = ds1.repeat(4)
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num_iter = 0
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for data in ds1.create_dict_iterator(num_epochs=1): # each data is a dictionary
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# in this example, each dictionary has keys "image" and "label"
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logger.info("{} image: {}".format(num_iter, data["image"]))
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logger.info("{} label: {}".format(num_iter, data["label"]))
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num_iter += 1
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logger.info("Number of data in ds1: {}".format(num_iter))
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assert num_iter == 200
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logger.info("Test randomdataset basic 1 complete")
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# Another simple test
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def test_randomdataset_basic2():
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logger.info("Test randomdataset basic 2")
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schema = ds.Schema()
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schema.add_column('image', de_type=mstype.uint8,
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shape=[640, 480, 3]) # 921600 bytes (a bit less than 1 MB per image)
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schema.add_column('label', de_type=mstype.uint8, shape=[1])
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# Make up 10 rows
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ds1 = ds.RandomDataset(schema=schema, total_rows=10, num_parallel_workers=1)
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ds1 = ds1.repeat(4)
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num_iter = 0
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for data in ds1.create_dict_iterator(num_epochs=1): # each data is a dictionary
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# in this example, each dictionary has keys "image" and "label"
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# logger.info(data["image"])
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logger.info("printing the label: {}".format(data["label"]))
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num_iter += 1
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logger.info("Number of data in ds1: {}".format(num_iter))
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assert num_iter == 40
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logger.info("Test randomdataset basic 2 complete")
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# Another simple test
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def test_randomdataset_basic3():
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logger.info("Test randomdataset basic 3")
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# Make up 10 samples, but here even the schema is randomly created
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# The columns are named like this "c0", "c1", "c2" etc
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# But, we will use a tuple iterator instead of dict iterator so the column names
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# are not needed to iterate
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ds1 = ds.RandomDataset(total_rows=10, num_parallel_workers=1)
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ds1 = ds1.repeat(2)
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num_iter = 0
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for _ in ds1.create_tuple_iterator(num_epochs=1):
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num_iter += 1
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logger.info("Number of data in ds1: {}".format(num_iter))
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assert num_iter == 20
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logger.info("Test randomdataset basic 3 Complete")
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if __name__ == '__main__':
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test_randomdataset_basic1()
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test_randomdataset_basic2()
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test_randomdataset_basic3()
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