wehub-resource-sync
184 lines
7.7 KiB
Python
184 lines
7.7 KiB
Python
# Copyright (c) 2022 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 unittest
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from tempfile import TemporaryDirectory
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from paddlenlp.taskflow import Taskflow
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from paddlenlp.taskflow.text_similarity import TextSimilarityTask
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class TestTextSimilarityTask(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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cls.temp_dir = TemporaryDirectory()
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cls.max_seq_len = 32
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cls.model = "__internal_testing__/tiny-random-rocketqa-cross-encoder"
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@classmethod
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def tearDownClass(cls):
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cls.temp_dir.cleanup()
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def test_bert_model(self):
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# static simbert test
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similarity = Taskflow(
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task="text_similarity",
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model="__internal_testing__/tiny-random-bert",
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)
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results = similarity([["世界上什么东西最小", "世界上什么东西最小？"]])
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self.assertTrue(len(results) == 1)
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self.assertTrue("text1" in results[0])
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self.assertTrue("text2" in results[0])
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self.assertIsInstance(results[0]["similarity"], float)
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results = similarity([["光眼睛大就好看吗", "眼睛好看吗？"], ["小蝌蚪找妈妈怎么样", "小蝌蚪找妈妈是谁画的"]])
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self.assertTrue(len(results) == 2)
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for result in results:
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self.assertTrue("text1" in result)
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self.assertTrue("text2" in result)
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self.assertIsInstance(result["similarity"], float)
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def test_text_similarity_task(self):
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# static rocketqa test
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input_text = ([["世界上什么东西最小", "世界上什么东西最小？"]],)
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static_taskflow = TextSimilarityTask(
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model="rocketqa-zh-dureader-cross-encoder",
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task="text_similarity",
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task_path=self.model,
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max_seq_len=self.max_seq_len,
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device_id=0,
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)
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static_results = static_taskflow(input_text)
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self.assertTrue(len(static_results) == 1)
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self.assertTrue("text1" in static_results[0])
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self.assertTrue("text2" in static_results[0])
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self.assertIsInstance(static_results[0]["similarity"], float)
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input_text = ([["光眼睛大就好看吗", "眼睛好看吗？"], ["小蝌蚪找妈妈怎么样", "小蝌蚪找妈妈是谁画的"]],)
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results = static_taskflow(input_text)
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self.assertTrue(len(results) == 2)
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for result in results:
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self.assertTrue("text1" in result)
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self.assertTrue("text2" in result)
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self.assertIsInstance(result["similarity"], float)
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# static rocketqav2 test
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input_text = ([["Tomorrow is another day", "Today is a sunny day"]],)
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static_taskflow = TextSimilarityTask(
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model="rocketqav2-en-marco-cross-encoder",
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task="text_similarity",
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task_path=self.model,
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max_seq_len=self.max_seq_len,
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device_id=0,
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)
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static_results = static_taskflow(input_text)
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self.assertTrue(len(static_results) == 1)
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self.assertTrue("text1" in static_results[0])
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self.assertTrue("text2" in static_results[0])
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self.assertIsInstance(static_results[0]["similarity"], float)
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input_text = (
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[["Tomorrow is another day", "Today is a sunny day"], ["This is my dream", "This is my father"]],
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)
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results = static_taskflow(input_text)
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self.assertTrue(len(results) == 2)
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for result in results:
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self.assertTrue("text1" in result)
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self.assertTrue("text2" in result)
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self.assertIsInstance(result["similarity"], float)
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# static ernie-search test
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input_text = ([["Tomorrow is another day", "Today is a sunny day"]],)
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static_taskflow = TextSimilarityTask(
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model="ernie-search-large-cross-encoder-marco-en",
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task="text_similarity",
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task_path=self.model,
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max_seq_len=self.max_seq_len,
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device_id=0,
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)
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static_results = static_taskflow(input_text)
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self.assertTrue(len(static_results) == 1)
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self.assertTrue("text1" in static_results[0])
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self.assertTrue("text2" in static_results[0])
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self.assertIsInstance(static_results[0]["similarity"], float)
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input_text = (
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[["Tomorrow is another day", "Today is a sunny day"], ["This is my dream", "This is my father"]],
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)
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results = static_taskflow(input_text)
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self.assertTrue(len(results) == 2)
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for result in results:
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self.assertTrue("text1" in result)
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self.assertTrue("text2" in result)
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self.assertIsInstance(result["similarity"], float)
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def test_taskflow_task(self):
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# static rocketqav1 test
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input_text = [["世界上什么东西最小", "世界上什么东西最小？"]]
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static_taskflow = Taskflow(
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model="rocketqa-zh-dureader-cross-encoder",
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task="text_similarity",
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task_path=self.model,
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max_seq_len=self.max_seq_len,
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)
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static_results = static_taskflow(input_text)
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self.assertTrue(len(static_results) == 1)
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self.assertTrue("text1" in static_results[0])
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self.assertTrue("text2" in static_results[0])
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self.assertIsInstance(static_results[0]["similarity"], float)
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# static rocketqav2 test
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input_text = [["Tomorrow is another day", "Today is a sunny day"]]
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static_taskflow = Taskflow(
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model="rocketqav2-en-marco-cross-encoder",
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task="text_similarity",
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task_path=self.model,
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max_seq_len=self.max_seq_len,
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)
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static_results = static_taskflow(input_text)
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self.assertTrue(len(static_results) == 1)
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self.assertTrue("text1" in static_results[0])
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self.assertTrue("text2" in static_results[0])
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self.assertIsInstance(static_results[0]["similarity"], float)
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input_text = [["Tomorrow is another day", "Today is a sunny day"], ["This is my dream", "This is my father"]]
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results = static_taskflow(input_text)
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self.assertTrue(len(results) == 2)
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for result in results:
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self.assertTrue("text1" in result)
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self.assertTrue("text2" in result)
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self.assertIsInstance(result["similarity"], float)
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# static ernie-search test
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input_text = [["Tomorrow is another day", "Today is a sunny day"]]
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static_taskflow = Taskflow(
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model="ernie-search-large-cross-encoder-marco-en",
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task="text_similarity",
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task_path=self.model,
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max_seq_len=self.max_seq_len,
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)
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static_results = static_taskflow(input_text)
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self.assertTrue(len(static_results) == 1)
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self.assertTrue("text1" in static_results[0])
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self.assertTrue("text2" in static_results[0])
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self.assertIsInstance(static_results[0]["similarity"], float)
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input_text = [["Tomorrow is another day", "Today is a sunny day"], ["This is my dream", "This is my father"]]
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results = static_taskflow(input_text)
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self.assertTrue(len(results) == 2)
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for result in results:
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self.assertTrue("text1" in result)
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self.assertTrue("text2" in result)
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self.assertIsInstance(result["similarity"], float)
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