forked from huawei/mindspore2022
48 lines
1.9 KiB
Python
Executable File
48 lines
1.9 KiB
Python
Executable File
# Copyright 2021 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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"""train resnet."""
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import os
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import argparse
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from src.dataset import create_dataset1 as create_dataset
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parser = argparse.ArgumentParser(description='preprocess data')
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parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path')
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parser.add_argument('--output_path', type=str, default=None, help='output path')
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args_opt = parser.parse_args()
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if __name__ == '__main__':
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# create dataset
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dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=False, batch_size=1,
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target="Ascend")
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step_size = dataset.get_dataset_size()
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img_path = os.path.join(args_opt.output_path, "img_data")
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label_path = os.path.join(args_opt.output_path, "label")
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os.makedirs(img_path)
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os.makedirs(label_path)
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for idx, data in enumerate(dataset.create_dict_iterator(output_numpy=True, num_epochs=1)):
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img_data = data["image"]
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img_label = data["label"]
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file_name = "google_cifar10_1_" + str(idx) + ".bin"
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img_file_path = os.path.join(img_path, file_name)
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img_data.tofile(img_file_path)
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label_file_path = os.path.join(label_path, file_name)
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img_label.tofile(label_file_path)
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print("=" * 20, "export bin files finished", "=" * 20)
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