mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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7c9bf11c44
* Optimize Poros backend * fix error * Add more pybind * fix conflicts * add some deprecate notices
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
# Copyright (c) 2022 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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from fastdeploy import ModelFormat
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import fastdeploy as fd
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import numpy as np
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def load_example_input_datas():
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"""prewarm datas"""
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data_list = []
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# max size
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input_1 = np.ones((1, 3, 224, 224), dtype=np.float32)
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max_inputs = [input_1]
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data_list.append(tuple(max_inputs))
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# min size
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input_1 = np.ones((1, 3, 224, 224), dtype=np.float32)
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min_inputs = [input_1]
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data_list.append(tuple(min_inputs))
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# opt size
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input_1 = np.ones((1, 3, 224, 224), dtype=np.float32)
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opt_inputs = [input_1]
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data_list.append(tuple(opt_inputs))
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return data_list
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if __name__ == '__main__':
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# prewarm_datas
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prewarm_datas = load_example_input_datas()
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# download model
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model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/std_resnet50_script.pt"
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fd.download(model_url, path=".")
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option = fd.RuntimeOption()
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option.use_gpu(0)
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option.use_poros_backend()
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option.set_model_path(
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"std_resnet50_script.pt", model_format=ModelFormat.TORCHSCRIPT)
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# compile
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runtime = fd.Runtime(option)
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runtime.compile(prewarm_datas)
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# infer
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input_data_0 = np.random.rand(1, 3, 224, 224).astype("float32")
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result = runtime.forward(input_data_0)
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print(result[0].shape)
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