mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 17:17:14 +08:00
Add Benchmark script for PPClas models (#187)
* first commit for yolov7 * pybind for yolov7 * CPP README.md * CPP README.md * modified yolov7.cc * README.md * python file modify * delete license in fastdeploy/ * repush the conflict part * README.md modified * README.md modified * file path modified * file path modified * file path modified * file path modified * file path modified * README modified * README modified * move some helpers to private * add examples for yolov7 * api.md modified * api.md modified * api.md modified * YOLOv7 * yolov7 release link * yolov7 release link * yolov7 release link * copyright * change some helpers to private * change variables to const and fix documents. * gitignore * Transfer some funtions to private member of class * Transfer some funtions to private member of class * Merge from develop (#9) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * first commit for yolor * for merge * Develop (#11) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * Yolor (#16) * Develop (#11) (#12) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * Develop (#13) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * Develop (#14) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason <928090362@qq.com> * add is_dynamic for YOLO series (#22) * git test * benchmark for ppclas * retrigger ci Co-authored-by: Jason <jiangjiajun@baidu.com> Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason <928090362@qq.com> Co-authored-by: ziqi-jin <>
This commit is contained in:
@@ -0,0 +1,178 @@
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import fastdeploy as fd
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import cv2
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import os
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from tqdm import trange
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import numpy as np
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import datetime
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import json
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def parse_arguments():
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import argparse
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import ast
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--model", required=True, help="Path of PaddleClas model.")
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parser.add_argument(
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"--image", type=str, required=False, help="Path of test image file.")
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parser.add_argument(
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"--input_name",
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type=str,
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required=False,
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default="inputs",
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help="input name of inference file.")
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parser.add_argument(
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"--topk", type=int, default=1, help="Return topk results.")
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parser.add_argument(
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"--cpu_num_thread",
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type=int,
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default=12,
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help="default number of cpu thread.")
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parser.add_argument(
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"--size",
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nargs='+',
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type=int,
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default=[1, 3, 224, 224],
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help="size of inference array.")
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parser.add_argument(
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"--iter_num",
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required=True,
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type=int,
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default=30,
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help="number of iterations for computing performace.")
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parser.add_argument(
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"--device",
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nargs='+',
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type=str,
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default=['cpu', 'cpu', 'cpu', 'gpu', 'gpu', 'gpu'],
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help="Type of inference device, support 'cpu' or 'gpu'.")
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parser.add_argument(
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"--backend",
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nargs='+',
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type=str,
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default=['ort', 'paddle', 'ov', 'ort', 'trt', 'paddle'],
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help="inference backend.")
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args = parser.parse_args()
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backend_list = ['ov', 'trt', 'ort', 'paddle']
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device_list = ['cpu', 'gpu']
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assert len(args.device) == len(
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args.backend), "the same number of --device and --backend is requested"
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assert args.iter_num > 10, "--iter_num has to bigger than 10"
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assert len(args.size
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) == 4, "size should include 4 values, e.g., --size 1 3 300 300"
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for b in args.backend:
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assert b in backend_list, "%s backend is not supported" % b
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for d in args.device:
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assert d in device_list, "%s device is not supported" % d
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return args
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def build_option(index, args):
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option = fd.RuntimeOption()
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device = args.device[index]
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backend = args.backend[index]
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option.set_cpu_thread_num(args.cpu_num_thread)
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if device == "gpu":
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option.use_gpu()
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if backend == "trt":
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assert device == "gpu", "the trt backend need device==gpu"
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option.use_trt_backend()
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option.set_trt_input_shape(args.input_name, args.size)
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elif backend == "ov":
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assert device == "cpu", "the openvino backend need device==cpu"
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option.use_openvino_backend()
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elif backend == "paddle":
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option.use_paddle_backend()
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elif backend == "ort":
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option.use_ort_backend()
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else:
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print("%s is an unsupported backend" % backend)
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print("============= inference using %s backend on %s device ============="
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% (args.backend[index], args.device[index]))
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return option
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args = parse_arguments()
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save_dict = dict()
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for index, device_name in enumerate(args.device):
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if device_name not in save_dict:
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save_dict[device_name] = dict()
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# 配置runtime,加载模型
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runtime_option = build_option(index, args)
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model_file = os.path.join(args.model, "inference.pdmodel")
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params_file = os.path.join(args.model, "inference.pdiparams")
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config_file = os.path.join(args.model, "inference_cls.yaml")
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model = fd.vision.classification.PaddleClasModel(
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model_file, params_file, config_file, runtime_option=runtime_option)
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# 创建要输入的向量
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channel = args.size[1]
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height = args.size[2]
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width = args.size[3]
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input_array = np.random.randint(
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0, high=255, size=(height, width, channel), dtype=np.uint8)
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# 如果有输入图片,则使用输入的图片进行推理
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if args.image:
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input_array = cv2.imread(args.image)
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model_name = args.model.split('/')
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model_name = model_name[-1] if model_name[-1] else model_name[-2]
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print(" Model: ", model_name, " Input shape: ", input_array.shape)
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start_time = datetime.datetime.now()
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model.enable_record_time_of_runtime()
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warmup_iter = args.iter_num // 5
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warmup_end2end_time = 0
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if "iter_num" not in save_dict:
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save_dict["iter_num"] = args.iter_num
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if "warmup_iter" not in save_dict:
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save_dict["warmup_iter"] = warmup_iter
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if "cpu_num_thread" not in save_dict:
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save_dict["cpu_num_thread"] = args.cpu_num_thread
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for i in trange(args.iter_num, desc="Inference Progress"):
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if i == warmup_iter:
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# 计算warmup端到端总时间(s)
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warmup_time = datetime.datetime.now()
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warmup_end2end_time = warmup_time - start_time
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warmup_end2end_time = (
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warmup_end2end_time.days * 24 * 60 * 60 +
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warmup_end2end_time.seconds
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) * 1000 + warmup_end2end_time.microseconds / 1000
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result = model.predict(input_array, args.topk)
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end_time = datetime.datetime.now()
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# 计算端到端(前处理,推理,后处理)的总时间
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statis_info_of_runtime_dict = model.print_statis_info_of_runtime()
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end2end_time = end_time - start_time
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end2end_time = (end2end_time.days * 24 * 60 * 60 + end2end_time.seconds
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) * 1000 + end2end_time.microseconds / 1000
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remain_end2end_time = end2end_time - warmup_end2end_time
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pre_post_process = end2end_time - statis_info_of_runtime_dict[
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"total_time"] * 1000
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end2end = remain_end2end_time / (args.iter_num - warmup_iter)
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runtime = statis_info_of_runtime_dict["avg_time"] * 1000
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print("Total time of end2end: %s ms" % str(end2end_time))
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print("Average time of end2end exclude warmup step: %s ms" % str(end2end))
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print("Total time of preprocess and postprocess in warmup step: %s ms" %
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str(warmup_end2end_time - statis_info_of_runtime_dict["warmup_time"]
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* 1000))
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print(
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"Average time of preprocess and postprocess exclude warmup step: %s ms"
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% str((remain_end2end_time - statis_info_of_runtime_dict["remain_time"]
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* 1000) / (args.iter_num - warmup_iter)))
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# 结构化输出
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backend_name = args.backend[index]
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save_dict[device_name][backend_name] = {
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"end2end": end2end,
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"runtime": runtime
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}
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json_str = json.dumps(save_dict)
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with open("%s.json" % model_name, 'w', encoding='utf-8') as fw:
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json.dump(json_str, fw, indent=4, ensure_ascii=False)
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@@ -162,12 +162,13 @@ bool FastDeployModel::Infer(std::vector<FDTensor>& input_tensors,
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return ret;
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}
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void FastDeployModel::PrintStatisInfoOfRuntime() {
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std::map<std::string, float> FastDeployModel::PrintStatisInfoOfRuntime() {
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std::map<std::string, float> statis_info_of_runtime_dict;
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if (time_of_runtime_.size() < 10) {
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FDWARNING << "PrintStatisInfoOfRuntime require the runtime ran 10 times at "
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"least, but now you only ran "
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<< time_of_runtime_.size() << " times." << std::endl;
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return;
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}
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double warmup_time = 0.0;
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double remain_time = 0.0;
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@@ -188,8 +189,16 @@ void FastDeployModel::PrintStatisInfoOfRuntime() {
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std::cout << "Warmup iterations: " << warmup_iter << std::endl;
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std::cout << "Total time of runtime in warmup step: " << warmup_time << "s."
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<< std::endl;
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std::cout << "Average time of runtime exclude warmup step: " << avg_time
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<< "s." << std::endl;
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std::cout << "Average time of runtime exclude warmup step: "
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<< avg_time * 1000 << "ms." << std::endl;
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statis_info_of_runtime_dict["total_time"] = warmup_time + remain_time;
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statis_info_of_runtime_dict["warmup_time"] = warmup_time;
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statis_info_of_runtime_dict["remain_time"] = remain_time;
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statis_info_of_runtime_dict["warmup_iter"] = warmup_iter;
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statis_info_of_runtime_dict["avg_time"] = avg_time;
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statis_info_of_runtime_dict["iterations"] = time_of_runtime_.size();
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return statis_info_of_runtime_dict;
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}
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void FastDeployModel::EnableDebug() {
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@@ -53,8 +53,7 @@ class FASTDEPLOY_DECL FastDeployModel {
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enable_record_time_of_runtime_ = false;
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}
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virtual void PrintStatisInfoOfRuntime();
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virtual std::map<std::string, float> PrintStatisInfoOfRuntime();
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virtual void EnableDebug();
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virtual bool DebugEnabled();
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@@ -52,7 +52,7 @@ class FastDeployModel:
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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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self._model.print_statis_info_of_runtime()
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return self._model.print_statis_info_of_runtime()
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@property
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def runtime_option(self):
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