wehub-resource-sync
75 lines
3.0 KiB
Python
75 lines
3.0 KiB
Python
# Copyright (c) 2023 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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import os
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import unittest
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from tempfile import TemporaryDirectory
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from paddlenlp.dataaug import (
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SentenceBackTranslate,
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SentenceContinue,
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SentenceGenerate,
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SentenceSummarize,
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)
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from paddlenlp.transformers import AutoModelForConditionalGeneration, AutoTokenizer
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class TestSentAug(unittest.TestCase):
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def setUp(self):
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self.sequences = ["人类语言是抽象的信息符号。", "而计算机只能处理数值化的信息。"]
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self.max_length = 3
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def test_sent_generate(self):
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aug = SentenceGenerate(model_name="__internal_testing__/tiny-random-roformer-sim", max_length=self.max_length)
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augmented = aug.augment(self.sequences)
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self.assertEqual(len(self.sequences), len(augmented))
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self.assertEqual(aug.create_n, len(augmented[0]))
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self.assertEqual(aug.create_n, len(augmented[1]))
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def test_sent_summarize(self):
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model = AutoModelForConditionalGeneration.from_pretrained(
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"__internal_testing__/tiny-random-mbart", max_length=self.max_length
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)
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tokenizer = AutoTokenizer.from_pretrained("__internal_testing__/tiny-random-mbart")
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model_path = os.path.join(TemporaryDirectory().name, "model")
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model.save_pretrained(model_path)
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tokenizer.save_pretrained(model_path)
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aug = SentenceSummarize(task_path=model_path)
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augmented = aug.augment(self.sequences)
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self.assertEqual(len(self.sequences), len(augmented))
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self.assertEqual(aug.create_n, len(augmented[0]))
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self.assertEqual(aug.create_n, len(augmented[1]))
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def test_sent_backtranslate(self):
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aug = SentenceBackTranslate(
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from_model_name="__internal_testing__/tiny-random-mbart",
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to_model_name="__internal_testing__/tiny-random-mbart",
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max_length=self.max_length,
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)
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augmented = aug.augment(self.sequences)
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self.assertEqual(len(self.sequences), len(augmented))
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self.assertEqual(1, len(augmented[0]))
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self.assertEqual(1, len(augmented[1]))
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def test_sent_continue(self):
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aug = SentenceContinue(model_name="__internal_testing__/tiny-random-gpt", max_length=self.max_length)
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augmented = aug.augment(self.sequences)
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self.assertEqual(len(self.sequences), len(augmented))
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self.assertEqual(aug.create_n, len(augmented[0]))
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self.assertEqual(aug.create_n, len(augmented[1]))
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if __name__ == "__main__":
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unittest.main()
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