change sentiment-classification branch

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9662406

    * bug fix for nlp backbone-head trainers

tests/pipelines/test_sentiment_classification.py

@@ -3,7 +3,8 @@ import unittest
 
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.models import Model
-from modelscope.models.nlp import SbertForSequenceClassification
+from modelscope.models.nlp.task_models.sequence_classification import \
+    SequenceClassificationModel
 from modelscope.pipelines import pipeline
 from modelscope.pipelines.nlp import SingleSentenceClassificationPipeline
 from modelscope.preprocessors import SingleSentenceClassificationPreprocessor
@@ -11,15 +12,15 @@ from modelscope.utils.constant import Tasks
 from modelscope.utils.test_utils import test_level
 
 
-class SentimentClassificationTest(unittest.TestCase):
-    model_id = 'damo/nlp_structbert_sentiment-classification_chinese-tiny'
+class SentimentClassificationTaskModelTest(unittest.TestCase):
+    model_id = 'damo/nlp_structbert_sentiment-classification_chinese-base'
     sentence1 = '启动的时候很大声音，然后就会听到1.2秒的卡察的声音，类似齿轮摩擦的声音'
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_direct_file_download(self):
         cache_path = snapshot_download(self.model_id)
         tokenizer = SingleSentenceClassificationPreprocessor(cache_path)
-        model = SbertForSequenceClassification.from_pretrained(
+        model = SequenceClassificationModel.from_pretrained(
             self.model_id, num_labels=2)
         pipeline1 = SingleSentenceClassificationPipeline(
             model, preprocessor=tokenizer)
@@ -32,10 +33,6 @@ class SentimentClassificationTest(unittest.TestCase):
         print()
         print(f'sentence1: {self.sentence1}\n'
               f'pipeline1: {pipeline2(input=self.sentence1)}')
-        self.assertTrue(
-            isinstance(pipeline1.model, SbertForSequenceClassification))
-        self.assertTrue(
-            isinstance(pipeline2.model, SbertForSequenceClassification))
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_model_from_modelhub(self):
@@ -47,23 +44,22 @@ class SentimentClassificationTest(unittest.TestCase):
             preprocessor=tokenizer)
         print(pipeline_ins(input=self.sentence1))
         self.assertTrue(
-            isinstance(pipeline_ins.model, SbertForSequenceClassification))
+            isinstance(pipeline_ins.model, SequenceClassificationModel))
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_model_name(self):
         pipeline_ins = pipeline(
             task=Tasks.sentiment_classification, model=self.model_id)
         print(pipeline_ins(input=self.sentence1))
-        print(pipeline_ins.model.__class__)
         self.assertTrue(
-            isinstance(pipeline_ins.model, SbertForSequenceClassification))
+            isinstance(pipeline_ins.model, SequenceClassificationModel))
 
-    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_default_model(self):
         pipeline_ins = pipeline(task=Tasks.sentiment_classification)
         print(pipeline_ins(input=self.sentence1))
         self.assertTrue(
-            isinstance(pipeline_ins.model, SbertForSequenceClassification))
+            isinstance(pipeline_ins.model, SequenceClassificationModel))
 
 
 if __name__ == '__main__':

tests/pipelines/test_sentiment_classification_task_model.py

@@ -1,70 +0,0 @@
-# Copyright (c) Alibaba, Inc. and its affiliates.
-import unittest
-
-from modelscope.hub.snapshot_download import snapshot_download
-from modelscope.models import Model
-from modelscope.models.nlp.task_models.sequence_classification import \
-    SequenceClassificationModel
-from modelscope.pipelines import pipeline
-from modelscope.pipelines.nlp import SingleSentenceClassificationPipeline
-from modelscope.preprocessors import SingleSentenceClassificationPreprocessor
-from modelscope.utils.constant import Tasks
-from modelscope.utils.test_utils import test_level
-
-
-class SentimentClassificationTaskModelTest(unittest.TestCase):
-    model_id = 'damo/nlp_structbert_sentiment-classification_chinese-base'
-    sentence1 = '启动的时候很大声音，然后就会听到1.2秒的卡察的声音，类似齿轮摩擦的声音'
-
-    @unittest.skip
-    def test_run_with_direct_file_download(self):
-        cache_path = snapshot_download(self.model_id)
-        tokenizer = SingleSentenceClassificationPreprocessor(cache_path)
-        model = SequenceClassificationModel.from_pretrained(
-            self.model_id, num_labels=2)
-        pipeline1 = SingleSentenceClassificationPipeline(
-            model, preprocessor=tokenizer)
-        pipeline2 = pipeline(
-            Tasks.sentiment_classification,
-            model=model,
-            preprocessor=tokenizer,
-            model_revision='beta')
-        print(f'sentence1: {self.sentence1}\n'
-              f'pipeline1:{pipeline1(input=self.sentence1)}')
-        print()
-        print(f'sentence1: {self.sentence1}\n'
-              f'pipeline1: {pipeline2(input=self.sentence1)}')
-
-    @unittest.skip
-    def test_run_with_model_from_modelhub(self):
-        model = Model.from_pretrained(self.model_id, revision='beta')
-        tokenizer = SingleSentenceClassificationPreprocessor(model.model_dir)
-        pipeline_ins = pipeline(
-            task=Tasks.sentiment_classification,
-            model=model,
-            preprocessor=tokenizer)
-        print(pipeline_ins(input=self.sentence1))
-        self.assertTrue(
-            isinstance(pipeline_ins.model, SequenceClassificationModel))
-
-    @unittest.skip
-    def test_run_with_model_name(self):
-        pipeline_ins = pipeline(
-            task=Tasks.sentiment_classification,
-            model=self.model_id,
-            model_revision='beta')
-        print(pipeline_ins(input=self.sentence1))
-        self.assertTrue(
-            isinstance(pipeline_ins.model, SequenceClassificationModel))
-
-    @unittest.skip
-    def test_run_with_default_model(self):
-        pipeline_ins = pipeline(
-            task=Tasks.sentiment_classification, model_revision='beta')
-        print(pipeline_ins(input=self.sentence1))
-        self.assertTrue(
-            isinstance(pipeline_ins.model, SequenceClassificationModel))
-
-
-if __name__ == '__main__':
-    unittest.main()

tests/trainers/test_trainer_with_nlp.py

@@ -53,8 +53,7 @@ class TestTrainerWithNlp(unittest.TestCase):
             model=model_id,
             train_dataset=self.dataset,
             eval_dataset=self.dataset,
-            work_dir=self.tmp_dir,
-            model_revision='beta')
+            work_dir=self.tmp_dir)
 
         trainer = build_trainer(default_args=kwargs)
         trainer.train()
@@ -70,7 +69,7 @@ class TestTrainerWithNlp(unittest.TestCase):
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_trainer_with_user_defined_config(self):
         model_id = 'damo/nlp_structbert_sentiment-classification_chinese-base'
-        cfg = read_config(model_id, revision='beta')
+        cfg = read_config(model_id)
         cfg.train.max_epochs = 20
         cfg.train.work_dir = self.tmp_dir
         cfg_file = os.path.join(self.tmp_dir, 'config.json')
@@ -79,8 +78,7 @@ class TestTrainerWithNlp(unittest.TestCase):
             model=model_id,
             train_dataset=self.dataset,
             eval_dataset=self.dataset,
-            cfg_file=cfg_file,
-            model_revision='beta')
+            cfg_file=cfg_file)
 
         trainer = build_trainer(default_args=kwargs)
         trainer.train()