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49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
8 months ago
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# Copyright (c) 2021 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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from __future__ import division
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from __future__ import print_function
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import numpy as np
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import paddle
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__all__ = ["VQASerTokenMetric"]
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class VQASerTokenMetric(object):
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def __init__(self, main_indicator="hmean", **kwargs):
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self.main_indicator = main_indicator
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self.reset()
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def __call__(self, preds, batch, **kwargs):
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preds, labels = preds
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self.pred_list.extend(preds)
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self.gt_list.extend(labels)
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def get_metric(self):
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from seqeval.metrics import f1_score, precision_score, recall_score
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metrics = {
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"precision": precision_score(self.gt_list, self.pred_list),
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"recall": recall_score(self.gt_list, self.pred_list),
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"hmean": f1_score(self.gt_list, self.pred_list),
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}
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self.reset()
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return metrics
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def reset(self):
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self.pred_list = []
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self.gt_list = []
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