wehub-resource-sync
65 lines
1.8 KiB
Python
Executable File
65 lines
1.8 KiB
Python
Executable File
#!/usr/bin/env python3.8
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# Copyright (c) 2020 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 numpy as np
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from paddle.base.core import AnalysisConfig, create_paddle_predictor
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def main():
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config = set_config()
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predictor = create_paddle_predictor(config)
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data, result = parse_data()
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input_names = predictor.get_input_names()
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input_tensor = predictor.get_input_tensor(input_names[0])
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shape = (1, 3, 300, 300)
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input_data = data[:-4].astype(np.float32).reshape(shape)
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input_tensor.copy_from_cpu(input_data)
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predictor.zero_copy_run()
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output_names = predictor.get_output_names()
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output_tensor = predictor.get_output_tensor(output_names[0])
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output_data = output_tensor.copy_to_cpu()
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def set_config():
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config = AnalysisConfig("")
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config.set_model("model/__model__", "model/__params__")
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config.switch_use_feed_fetch_ops(False)
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config.switch_specify_input_names(True)
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config.enable_profile()
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return config
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def parse_data():
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"""parse input and output data"""
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with open('data/data.txt', 'r') as fr:
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data = np.array([float(_) for _ in fr.read().split()])
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with open('data/result.txt', 'r') as fr:
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result = np.array([float(_) for _ in fr.read().split()])
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return (data, result)
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if __name__ == "__main__":
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main()
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