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- # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- import os
- import tempfile
- from ..cls import ClsRunner
- from ...base.utils.subprocess import CompletedProcess
- class ShiTuRecRunner(ClsRunner):
- """ShiTuRec Runner"""
- pass
- def _extract_eval_metrics(stdout: str) -> dict:
- """extract evaluation metrics from training log
- Args:
- stdout (str): the training log
- Returns:
- dict: the training metric
- """
- import re
- _DP = r"[-+]?[0-9]*\.?[0-9]+(?:[eE][-+]?[0-9]+)?"
- patterns = [
- r"\[Eval\]\[Epoch 0\]\[Avg\].*top1: (_dp), top5: (_dp)".replace("_dp", _DP),
- r"\[Eval\]\[Epoch 0\]\[Avg\].*recall1: (_dp), recall5: (_dp), mAP: (_dp)".replace(
- "_dp", _DP
- ),
- ]
- keys = [["val.top1", "val.top5"], ["recall1", "recall5", "mAP"]]
- metric_dict = dict()
- for pattern, key in zip(patterns, keys):
- pattern = re.compile(pattern)
- for line in stdout.splitlines():
- match = pattern.search(line)
- if match:
- for k, v in zip(key, map(float, match.groups())):
- metric_dict[k] = v
- return metric_dict
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