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https://github.com/PaddlePaddle/FastDeploy.git
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f73a538f61
* [backend] support bechmark mode for runtime and backend * [backend] support bechmark mode for runtime and backend * [pybind11] add benchmark methods pybind * [pybind11] add benchmark methods pybind * [Other] Update build scripts * [Other] Update cmake/summary.cmake * [Other] update build scripts * [Other] add ENABLE_BENCHMARK option -> setup.py * optimize backend time recording * optimize backend time recording * optimize trt backend time record * [backend] optimze backend_time recording for trt * [benchmark] remove redundant logs * fixed ov_backend confilct * [benchmark] fixed paddle_backend conflicts * [benchmark] fixed paddle_backend conflicts * [benchmark] fixed paddle_backend conflicts * [benchmark] remove use_gpu option from ort backend option * [benchmark] update benchmark_ppdet.py * [benchmark] update benchmark_ppcls.py * fixed lite backend conflicts * [Lite] fixed lite xpu * add benchmark macro * add RUNTIME_PROFILE_LOOP macros * add comments for RUNTIME_PROFILE macros * add comments for new apis * add comments for new apis * update benchmark_ppdet.py * afixed bugs * remove unused codes * optimize RUNTIME_PROFILE_LOOP macros * optimize RUNTIME_PROFILE_LOOP macros * add comments for benchmark option and result * add docs for benchmark namespace
71 lines
2.4 KiB
Python
71 lines
2.4 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 __future__ import absolute_import
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import logging
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from . import c_lib_wrap as C
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class FastDeployModel:
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def __init__(self, option):
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self._model = None
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if option is None:
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self._runtime_option = C.RuntimeOption()
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else:
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self._runtime_option = option._option
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def model_name(self):
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return self._model.model_name()
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def num_inputs_of_runtime(self):
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return self._model.num_inputs_of_runtime()
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def num_outputs_of_runtime(self):
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return self._model.num_outputs_of_runtime()
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def input_info_of_runtime(self, index):
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assert index < self.num_inputs_of_runtime(
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), "The index:{} must be less than number of inputs:{}.".format(
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index, self.num_inputs_of_runtime())
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return self._model.input_info_of_runtime(index)
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def output_info_of_runtime(self, index):
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assert index < self.num_outputs_of_runtime(
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), "The index:{} must be less than number of outputs:{}.".format(
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index, self.num_outputs_of_runtime())
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return self._model.output_info_of_runtime(index)
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def enable_record_time_of_runtime(self):
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self._model.enable_record_time_of_runtime()
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def disable_record_time_of_runtime(self):
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self._model.disable_record_time_of_runtime()
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def print_statis_info_of_runtime(self):
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return self._model.print_statis_info_of_runtime()
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def get_profile_time(self):
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"""Get profile time of Runtime after the profile process is done.
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"""
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return self._model.get_profile_time()
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@property
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def runtime_option(self):
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return self._model.runtime_option if self._model is not None else None
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@property
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def initialized(self):
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if self._model is None:
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return False
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return self._model.initialized()
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