mirror of
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54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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import os
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import argparse
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import paddle
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import paddle.nn.functional as F
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from paddle.jit import to_static
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import backbones
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument("--network", type=str)
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parser.add_argument("--pretrained_model", type=str)
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parser.add_argument("--output_path", type=str, default="./inference")
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return parser.parse_args()
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def load_dygraph_pretrain(model, path=None):
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if not os.path.exists(path):
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raise ValueError(f"The path of pretrained model file does not exists: {path}.")
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param_state_dict = paddle.load(path)
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model.set_dict(param_state_dict)
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return
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def main():
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args = parse_args()
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net = eval("backbones.{}".format(args.network))()
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load_dygraph_pretrain(net, path=args.pretrained_model)
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net.eval()
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net = to_static(net, input_spec=[paddle.static.InputSpec(shape=[None, 3, 112, 112], dtype='float32')])
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paddle.jit.save(net, os.path.join(args.output_path, "inference"))
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if __name__ == "__main__":
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main() |