wehub-resource-sync
36 lines
1.4 KiB
Python
36 lines
1.4 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# 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 unittest
|
|
|
|
import paddle
|
|
|
|
from paddlenlp.metrics import SpanEvaluator
|
|
|
|
|
|
class TestSpanEvaluator(unittest.TestCase):
|
|
def test_metrics(self):
|
|
metric = SpanEvaluator()
|
|
metric.reset()
|
|
start_prob = paddle.to_tensor([[0.1, 0.1, 0.6, 0.2], [0.0, 0.9, 0.1, 0.0]])
|
|
end_prob = paddle.to_tensor([[0.1, 0.1, 0.2, 0.6], [0.0, 0.9, 0.1, 0.0]])
|
|
start_ids = paddle.to_tensor([[0, 0, 1, 0], [0, 0, 1, 0]])
|
|
end_ids = paddle.to_tensor([[0, 0, 0, 1], [0, 0, 1, 0]])
|
|
num_correct, num_infer, num_label = metric.compute(start_prob, end_prob, start_ids, end_ids)
|
|
metric.update(num_correct, num_infer, num_label)
|
|
precision, recall, f1 = metric.accumulate()
|
|
self.assertEqual(precision, 0.5)
|
|
self.assertEqual(recall, 0.5)
|
|
self.assertEqual(f1, 0.5)
|