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# Copyright 2020 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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"""export""" |
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import argparse |
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import numpy as np |
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from mindspore import context |
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from mindspore import Tensor |
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from mindspore.train.serialization import load_checkpoint, load_param_into_net, export |
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from src.resnet_thor import resnet50 as resnet |
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from src.config import config |
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parser = argparse.ArgumentParser(description='checkpoint export') |
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parser.add_argument('--checkpoint_path', type=str, default=None, help='Checkpoint file path') |
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args_opt = parser.parse_args() |
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if __name__ == '__main__': |
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context.set_context(mode=context.GRAPH_MODE, save_graphs=False) |
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# define net |
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net = resnet(class_num=config.class_num) |
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net.add_flags_recursive(thor=False) |
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# load checkpoint |
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param_dict = load_checkpoint(args_opt.checkpoint_path) |
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keys = list(param_dict.keys()) |
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for key in keys: |
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if "damping" in key: |
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param_dict.pop(key) |
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load_param_into_net(net, param_dict) |
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inputs = np.random.uniform(0.0, 1.0, size=[1, 3, 224, 224]).astype(np.float32) |
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export(net, Tensor(inputs), file_name='resnet-42_5004.air', file_format='AIR') |