PaddleClas/ppcls/metric/__init__.py

55 lines
1.9 KiB
Python

#copyright (c) 2021 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.
from paddle import nn
import copy
from collections import OrderedDict
from .metrics import TopkAcc, mAP, mINP, Recallk, RetriMetric
from .metrics import DistillationTopkAcc
class CombinedMetrics(nn.Layer):
def __init__(self, config_list):
super().__init__()
self.metric_func_list = []
assert isinstance(config_list, list), (
'operator config should be a list')
self.retri_config = dict() # retrieval metrics config
for config in config_list:
assert isinstance(config,
dict) and len(config) == 1, "yaml format error"
metric_name = list(config)[0]
if metric_name in ["Recallk", "mAP", "mINP"]:
self.retri_config[metric_name] = config[metric_name]
continue
metric_params = config[metric_name]
self.metric_func_list.append(eval(metric_name)(**metric_params))
if self.retri_config:
self.metric_func_list.append(RetriMetric(self.retri_config))
def __call__(self, *args, **kwargs):
metric_dict = OrderedDict()
for idx, metric_func in enumerate(self.metric_func_list):
metric_dict.update(metric_func(*args, **kwargs))
return metric_dict
def build_metrics(config):
metrics_list = CombinedMetrics(copy.deepcopy(config))
return metrics_list