Files
FastDeploy/tests/release_task/compare_with_gt.py
huangjianhui c18a9e32f9 [Bug Fix] Fix bugs in publish task scripts (#693)
* Fix release_task cpp_run.sh

 Author:    felixhjh <852142024@qq.com>
 Date:      Thu Nov 10 07:26:48 2022 +0000

* Add option for infer_ppyoloe.cc

  author:    felixhjh <852142024@qq.com>

* Fix bug in release task scripts

* Add error check function

* Format code

* Add new download dir for release version

* Fix precision diff for osx-arm64

Co-authored-by: root <root@bjyz-sys-gpu-kongming2.bjyz.baidu.com>
2022-11-24 18:51:13 +08:00

156 lines
5.3 KiB
Python

import numpy as np
import re
diff_score_threshold = {
"linux-x64": {
"label_diff": 0,
"score_diff": 1e-4,
"boxes_diff_ratio": 1e-4,
"boxes_diff": 1e-3
},
"linux-aarch64": {
"label_diff": 0,
"score_diff": 1e-4,
"boxes_diff_ratio": 1e-4,
"boxes_diff": 1e-3
},
"osx-x86_64": {
"label_diff": 0,
"score_diff": 1e-4,
"boxes_diff_ratio": 2e-4,
"boxes_diff": 1e-3
},
"osx-arm64": {
"label_diff": 0,
"score_diff": 1e-3,
"boxes_diff_ratio": 5e-4,
"boxes_diff": 1e-3
},
"win-x64": {
"label_diff": 0,
"score_diff": 5e-4,
"boxes_diff_ratio": 1e-3,
"boxes_diff": 1e-3
}
}
def all_sort(x):
x1 = x.T
y = np.split(x1, len(x1))
z = list(reversed(y))
index = np.lexsort(z)
return np.squeeze(x[index])
def parse_arguments():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"--gt_path",
type=str,
required=True,
help="Path of ground truth result path.")
parser.add_argument(
"--result_path",
type=str,
required=True,
help="Path of inference result path.")
parser.add_argument(
"--platform", type=str, required=True, help="Testcase platform.")
parser.add_argument(
"--device", type=str, required=True, help="Testcase device.")
parser.add_argument(
"--conf_threshold",
type=float,
required=False,
default=0,
help="The threshold to filter inference result.")
args = parser.parse_args()
return args
def convert2numpy(result_file, conf_threshold):
result = []
with open(result_file, "r+") as f:
for line in f.readlines():
data = re.findall(r"\d+\.?\d*", line)
if len(data) == 6:
if float(data[-2]) < conf_threshold:
continue
else:
result.append([float(num) for num in data])
return np.array(result)
def write2file(error_file):
import os
if not os.path.exists(error_file):
with open(error_file, "w+") as f:
f.write("Failed Cases:\n")
with open(error_file, "a+") as f:
from platform import python_version
py_version = python_version()
f.write(args.platform + " " + py_version + " " +
args.result_path.split(".")[0] + "\n")
def save_numpy_result(file_path, error_msg):
np.savetxt(file_path, error_msg, fmt='%f', delimiter=',')
def check_result(gt_result, infer_result, args):
platform = args.platform
if len(gt_result) != len(infer_result):
infer_result = infer_result[-len(gt_result):]
diff = np.abs(gt_result - infer_result)
label_diff = diff[:, -1]
score_diff = diff[:, -2]
boxes_diff = diff[:, :-2]
boxes_diff_ratio = boxes_diff / (infer_result[:, :-2] + 1e-6)
label_diff_threshold = diff_score_threshold[platform]["label_diff"]
score_diff_threshold = diff_score_threshold[platform]["score_diff"]
boxes_diff_threshold = diff_score_threshold[platform]["boxes_diff"]
boxes_diff_ratio_threshold = diff_score_threshold[platform][
"boxes_diff_ratio"]
is_diff = False
backend = args.result_path.split(".")[0]
if (label_diff > label_diff_threshold).any():
print(args.platform, args.device, "label diff ", label_diff)
is_diff = True
label_diff_bool_file = args.platform + "_" + backend + "_" + "label_diff_bool.txt"
save_numpy_result(label_diff_bool_file,
label_diff > label_diff_threshold)
if (score_diff > score_diff_threshold).any():
print(args.platform, args.device, "score diff ", score_diff)
is_diff = True
score_diff_bool_file = args.platform + "_" + backend + "_" + "score_diff_bool.txt"
save_numpy_result(score_diff_bool_file,
score_diff > score_diff_threshold)
if (boxes_diff_ratio > boxes_diff_ratio_threshold).any() and (
boxes_diff > boxes_diff_threshold).any():
print(args.platform, args.device, "boxes diff ", boxes_diff_ratio)
is_diff = True
boxes_diff_bool_file = args.platform + "_" + backend + "_" + "boxes_diff_bool.txt"
boxes_diff_ratio_file = args.platform + "_" + backend + "_" + "boxes_diff_ratio.txt"
boxes_diff_ratio_bool_file = args.platform + "_" + backend + "_" + "boxes_diff_ratio_bool.txt"
save_numpy_result(boxes_diff_bool_file,
boxes_diff > boxes_diff_threshold)
save_numpy_result(boxes_diff_ratio_file, boxes_diff_ratio)
save_numpy_result(boxes_diff_ratio_bool_file,
boxes_diff_ratio > boxes_diff_ratio_threshold)
if is_diff:
write2file("result.txt")
else:
print(args.platform, args.device, "No diff")
if __name__ == '__main__':
args = parse_arguments()
gt_numpy = convert2numpy(args.gt_path, args.conf_threshold)
infer_numpy = convert2numpy(args.result_path, args.conf_threshold)
gt_numpy = all_sort(gt_numpy)
infer_numpy = all_sort(infer_numpy)
check_result(gt_numpy, infer_numpy, args)