[to #42322933]fix token classification bugs

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10550136

modelscope/metainfo.py

@@ -254,6 +254,7 @@ class Pipelines(object):
     translation_en_to_de = 'translation_en_to_de'  # keep it underscore
     translation_en_to_ro = 'translation_en_to_ro'  # keep it underscore
     translation_en_to_fr = 'translation_en_to_fr'  # keep it underscore
+    token_classification = 'token-classification'
 
     # audio tasks
     sambert_hifigan_tts = 'sambert-hifigan-tts'

modelscope/models/nlp/task_models/token_classification.py

@@ -66,7 +66,6 @@ class TokenClassificationModel(SingleBackboneTaskModelBase):
             attentions=outputs.attentions,
             offset_mapping=input['offset_mapping'],
         )
-        return outputs
 
     def extract_logits(self, outputs):
         return outputs[OutputKeys.LOGITS].cpu().detach()

modelscope/pipelines/nlp/token_classification_pipeline.py

@@ -17,6 +17,8 @@ from modelscope.utils.tensor_utils import (torch_nested_detach,
 __all__ = ['TokenClassificationPipeline']
 
 
+@PIPELINES.register_module(
+    Tasks.token_classification, module_name=Pipelines.token_classification)
 @PIPELINES.register_module(
     Tasks.token_classification, module_name=Pipelines.part_of_speech)
 @PIPELINES.register_module(
@@ -41,7 +43,7 @@ class TokenClassificationPipeline(Pipeline):
                                                            str) else model
 
         if preprocessor is None:
-            preprocessor = Model.from_pretrained(
+            preprocessor = Preprocessor.from_pretrained(
                 model.model_dir,
                 sequence_length=kwargs.pop('sequence_length', 128))
         model.eval()