Merge remote-tracking branch 'origin' into feat/fill_mask

tests/pipelines/test_image_matting.py

@@ -52,7 +52,7 @@ class ImageMattingTest(unittest.TestCase):
         cv2.imwrite('result.png', result['output_png'])
         print(f'Output written to {osp.abspath("result.png")}')
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_modelhub_default_model(self):
         img_matting = pipeline(Tasks.image_matting)
 

tests/pipelines/test_person_image_cartoon.py

@@ -42,7 +42,7 @@ class ImageCartoonTest(unittest.TestCase):
         img_cartoon = pipeline(Tasks.image_generation, model=self.model_id)
         self.pipeline_inference(img_cartoon, self.test_image)
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_modelhub_default_model(self):
         img_cartoon = pipeline(Tasks.image_generation)
         self.pipeline_inference(img_cartoon, self.test_image)

tests/pipelines/test_sentence_similarity.py

@@ -16,7 +16,7 @@ class SentenceSimilarityTest(unittest.TestCase):
     sentence1 = '今天气温比昨天高么？'
     sentence2 = '今天湿度比昨天高么？'
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run(self):
         cache_path = snapshot_download(self.model_id)
         tokenizer = SequenceClassificationPreprocessor(cache_path)
@@ -32,7 +32,7 @@ class SentenceSimilarityTest(unittest.TestCase):
             f'sentence1: {self.sentence1}\nsentence2: {self.sentence2}\n'
             f'pipeline1: {pipeline2(input=(self.sentence1, self.sentence2))}')
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_model_from_modelhub(self):
         model = Model.from_pretrained(self.model_id)
         tokenizer = SequenceClassificationPreprocessor(model.model_dir)
@@ -48,7 +48,7 @@ class SentenceSimilarityTest(unittest.TestCase):
             task=Tasks.sentence_similarity, model=self.model_id)
         print(pipeline_ins(input=(self.sentence1, self.sentence2)))
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_default_model(self):
         pipeline_ins = pipeline(task=Tasks.sentence_similarity)
         print(pipeline_ins(input=(self.sentence1, self.sentence2)))

tests/pipelines/test_speech_signal_process.py

@@ -6,6 +6,7 @@ from modelscope.fileio import File
 from modelscope.metainfo import Pipelines
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
+from modelscope.utils.test_utils import test_level
 
 NEAREND_MIC_URL = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/AEC/sample_audio/nearend_mic.wav'
 FAREND_SPEECH_URL = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/AEC/sample_audio/farend_speech.wav'
@@ -33,6 +34,7 @@ class SpeechSignalProcessTest(unittest.TestCase):
         # A temporary hack to provide c++ lib. Download it first.
         download(AEC_LIB_URL, AEC_LIB_FILE)
 
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run(self):
         download(NEAREND_MIC_URL, NEAREND_MIC_FILE)
         download(FAREND_SPEECH_URL, FAREND_SPEECH_FILE)

tests/pipelines/test_text_classification.py

@@ -1,12 +1,8 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 import shutil
 import unittest
-import zipfile
-from pathlib import Path
 
-from modelscope.fileio import File
 from modelscope.models import Model
-from modelscope.models.nlp import BertForSequenceClassification
 from modelscope.pipelines import SequenceClassificationPipeline, pipeline
 from modelscope.preprocessors import SequenceClassificationPreprocessor
 from modelscope.pydatasets import PyDataset
@@ -62,7 +58,7 @@ class SequenceClassificationTest(unittest.TestCase):
                 hub=Hubs.huggingface))
         self.printDataset(result)
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_default_model(self):
         text_classification = pipeline(task=Tasks.text_classification)
         result = text_classification(
@@ -74,7 +70,7 @@ class SequenceClassificationTest(unittest.TestCase):
                 hub=Hubs.huggingface))
         self.printDataset(result)
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_dataset(self):
         model = Model.from_pretrained(self.model_id)
         preprocessor = SequenceClassificationPreprocessor(

tests/pipelines/test_text_generation.py

@@ -68,7 +68,7 @@ class TextGenerationTest(unittest.TestCase):
             pipeline_ins = pipeline(task=Tasks.text_generation, model=model_id)
             print(pipeline_ins(input))
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_default_model(self):
         pipeline_ins = pipeline(task=Tasks.text_generation)
         print(pipeline_ins(self.input_zh))

tests/pipelines/test_text_to_speech.py

@@ -1,7 +1,5 @@
-import time
 import unittest
 
-import json
 import tensorflow as tf
 # NOTICE: Tensorflow 1.15 seems not so compatible with pytorch.
 #         A segmentation fault may be raise by pytorch cpp library
@@ -10,21 +8,20 @@ import tensorflow as tf
 import torch
 from scipy.io.wavfile import write
 
-from modelscope.fileio import File
 from modelscope.metainfo import Pipelines, Preprocessors
-from modelscope.models import Model, build_model
-from modelscope.models.audio.tts.am import SambertNetHifi16k
-from modelscope.models.audio.tts.vocoder import AttrDict, Hifigan16k
+from modelscope.models import Model
 from modelscope.pipelines import pipeline
 from modelscope.preprocessors import build_preprocessor
-from modelscope.utils.constant import Fields, InputFields, Tasks
+from modelscope.utils.constant import Fields
 from modelscope.utils.logger import get_logger
+from modelscope.utils.test_utils import test_level
 
 logger = get_logger()
 
 
 class TextToSpeechSambertHifigan16kPipelineTest(unittest.TestCase):
 
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_pipeline(self):
         lang_type = 'pinyin'
         text = '明天天气怎么样'

tests/pipelines/test_word_segmentation.py

@@ -37,13 +37,13 @@ class WordSegmentationTest(unittest.TestCase):
             task=Tasks.word_segmentation, model=model, preprocessor=tokenizer)
         print(pipeline_ins(input=self.sentence))
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_model_name(self):
         pipeline_ins = pipeline(
             task=Tasks.word_segmentation, model=self.model_id)
         print(pipeline_ins(input=self.sentence))
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_default_model(self):
         pipeline_ins = pipeline(task=Tasks.word_segmentation)
         print(pipeline_ins(input=self.sentence))

tests/preprocessors/test_image.py

@@ -5,7 +5,6 @@ import unittest
 import PIL
 
 from modelscope.preprocessors import load_image
-from modelscope.utils.logger import get_logger
 
 
 class ImagePreprocessorTest(unittest.TestCase):

tests/pydatasets/test_py_dataset.py

@@ -33,6 +33,7 @@ class ImgPreprocessor(Preprocessor):
 
 class PyDatasetTest(unittest.TestCase):
 
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_ds_basic(self):
         ms_ds_full = PyDataset.load('squad')
         ms_ds_full_hf = hfdata.load_dataset('squad')
@@ -82,7 +83,7 @@ class PyDatasetTest(unittest.TestCase):
             drop_remainder=True)
         print(next(iter(tf_dataset)))
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     @require_torch
     def test_to_torch_dataset_img(self):
         ms_image_train = PyDataset.from_hf_dataset(
@@ -94,7 +95,7 @@ class PyDatasetTest(unittest.TestCase):
         dataloader = torch.utils.data.DataLoader(pt_dataset, batch_size=5)
         print(next(iter(dataloader)))
 
-    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     @require_tf
     def test_to_tf_dataset_img(self):
         import tensorflow as tf