# 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 ChunkEvaluator

class TestChunk(unittest.TestCase):

def test_metrics(self):

label_list = ["O", "B-Person", "I-Person"]

evaluator = ChunkEvaluator(label_list)

evaluator.reset()

lengths = paddle.to_tensor([5])

predictions = paddle.to_tensor([[0, 1, 2, 1, 2]])

labels = paddle.to_tensor([[0, 1, 2, 1, 1]])

num_infer_chunks, num_label_chunks, num_correct_chunks = evaluator.compute(

lengths=lengths, predictions=predictions, labels=labels

)

evaluator.update(num_infer_chunks.numpy(), num_label_chunks.numpy(), num_correct_chunks.numpy())

precision, recall, f1 = evaluator.accumulate()

self.assertEqual(precision, 0.5)

self.assertEqual(recall, 0.3333333333333333)

self.assertEqual(f1, 0.4)