[to #42322933] refactor model name

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9068994

modelscope/models/nlp/text_generation_model.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 from ..base import Model, Tensor
 from ..builder import MODELS
 
-__all__ = ['PalmForTextGenerationModel']
+__all__ = ['PalmForTextGeneration']
 
 
 @MODELS.register_module(Tasks.text_generation, module_name=r'palm')
-class PalmForTextGenerationModel(Model):
+class PalmForTextGeneration(Model):
 
     def __init__(self, model_dir: str, *args, **kwargs):
         """initialize the text generation model from the `model_dir` path.

modelscope/pipelines/builder.py

@@ -16,7 +16,7 @@ DEFAULT_MODEL_FOR_PIPELINE = {
     Tasks.sentence_similarity:
     ('sbert-base-chinese-sentence-similarity',
      'damo/nlp_structbert_sentence-similarity_chinese-base'),
-    Tasks.image_matting: ('image-matting', 'damo/cv_unet_image-matting_damo'),
+    Tasks.image_matting: ('image-matting', 'damo/cv_unet_image-matting'),
     Tasks.text_classification:
     ('bert-sentiment-analysis', 'damo/bert-base-sst2'),
     Tasks.text_generation: ('palm', 'damo/nlp_palm_text-generation_chinese'),

modelscope/pipelines/nlp/text_generation_pipeline.py

@@ -1,7 +1,7 @@
 from typing import Dict, Optional, Union
 
 from modelscope.models import Model
-from modelscope.models.nlp import PalmForTextGenerationModel
+from modelscope.models.nlp import PalmForTextGeneration
 from modelscope.preprocessors import TextGenerationPreprocessor
 from modelscope.utils.constant import Tasks
 from ..base import Pipeline, Tensor
@@ -14,7 +14,7 @@ __all__ = ['TextGenerationPipeline']
 class TextGenerationPipeline(Pipeline):
 
     def __init__(self,
-                 model: Union[PalmForTextGenerationModel, str],
+                 model: Union[PalmForTextGeneration, str],
                  preprocessor: Optional[TextGenerationPreprocessor] = None,
                  **kwargs):
         """use `model` and `preprocessor` to create a nlp text classification pipeline for prediction
@@ -24,8 +24,7 @@ class TextGenerationPipeline(Pipeline):
             preprocessor (SequenceClassificationPreprocessor): a preprocessor instance
         """
         sc_model = model if isinstance(
-            model,
-            PalmForTextGenerationModel) else Model.from_pretrained(model)
+            model, PalmForTextGeneration) else Model.from_pretrained(model)
         if preprocessor is None:
             preprocessor = TextGenerationPreprocessor(
                 sc_model.model_dir,

tests/pipelines/test_image_matting.py

@@ -17,7 +17,7 @@ from modelscope.utils.test_utils import test_level
 class ImageMattingTest(unittest.TestCase):
 
     def setUp(self) -> None:
-        self.model_id = 'damo/cv_unet_image-matting_damo'
+        self.model_id = 'damo/cv_unet_image-matting'
         # switch to False if downloading everytime is not desired
         purge_cache = True
         if purge_cache:

tests/pipelines/test_text_generation.py

@@ -4,7 +4,7 @@ import unittest
 from maas_hub.snapshot_download import snapshot_download
 
 from modelscope.models import Model
-from modelscope.models.nlp import PalmForTextGenerationModel
+from modelscope.models.nlp import PalmForTextGeneration
 from modelscope.pipelines import TextGenerationPipeline, pipeline
 from modelscope.preprocessors import TextGenerationPreprocessor
 from modelscope.utils.constant import Tasks
@@ -21,7 +21,7 @@ class TextGenerationTest(unittest.TestCase):
         cache_path = snapshot_download(self.model_id)
         preprocessor = TextGenerationPreprocessor(
             cache_path, first_sequence='sentence', second_sequence=None)
-        model = PalmForTextGenerationModel(
+        model = PalmForTextGeneration(
             cache_path, tokenizer=preprocessor.tokenizer)
         pipeline1 = TextGenerationPipeline(model, preprocessor)
         pipeline2 = pipeline(