solve comment: 1. change MaskedLMModelBase to MaskedLanguageModelBase 2. remove a useless import

modelscope/models/nlp/masked_language_model.py

@@ -7,10 +7,10 @@ from ...utils.constant import Tasks
 from ..base import Model, Tensor
 from ..builder import MODELS
 
-__all__ = ['StructBertForMaskedLM', 'VecoForMaskedLM', 'MaskedLMModelBase']
+__all__ = ['StructBertForMaskedLM', 'VecoForMaskedLM', 'MaskedLanguageModelBase']
 
 
-class MaskedLMModelBase(Model):
+class MaskedLanguageModelBase(Model):
 
     def __init__(self, model_dir: str, *args, **kwargs):
         super().__init__(model_dir, *args, **kwargs)
@@ -48,7 +48,7 @@ class MaskedLMModelBase(Model):
 
 
 @MODELS.register_module(Tasks.fill_mask, module_name=Models.structbert)
-class StructBertForMaskedLM(MaskedLMModelBase):
+class StructBertForMaskedLM(MaskedLanguageModelBase):
 
     def build_model(self):
         from sofa import SbertForMaskedLM
@@ -56,7 +56,7 @@ class StructBertForMaskedLM(MaskedLMModelBase):
 
 
 @MODELS.register_module(Tasks.fill_mask, module_name=Models.veco)
-class VecoForMaskedLM(MaskedLMModelBase):
+class VecoForMaskedLM(MaskedLanguageModelBase):
 
     def build_model(self):
         from sofa import VecoForMaskedLM

modelscope/pipelines/nlp/fill_mask_pipeline.py

@@ -4,7 +4,7 @@ import torch
 
 from ...metainfo import Pipelines
 from ...models import Model
-from ...models.nlp.masked_language_model import MaskedLMModelBase
+from ...models.nlp.masked_language_model import MaskedLanguageModelBase
 from ...preprocessors import FillMaskPreprocessor
 from ...utils.constant import Tasks
 from ..base import Pipeline, Tensor
@@ -17,18 +17,18 @@ __all__ = ['FillMaskPipeline']
 class FillMaskPipeline(Pipeline):
 
     def __init__(self,
-                 model: Union[MaskedLMModelBase, str],
+                 model: Union[MaskedLanguageModelBase, str],
                  preprocessor: Optional[FillMaskPreprocessor] = None,
                  first_sequence='sentense',
                  **kwargs):
         """use `model` and `preprocessor` to create a nlp fill mask pipeline for prediction
 
         Args:
-            model (MaskedLMModelBase): a model instance
+            model (MaskedLanguageModelBase): a model instance
             preprocessor (FillMaskPreprocessor): a preprocessor instance
         """
         fill_mask_model = model if isinstance(
-            model, MaskedLMModelBase) else Model.from_pretrained(model)
+            model, MaskedLanguageModelBase) else Model.from_pretrained(model)
         assert fill_mask_model.config is not None
 
         if preprocessor is None: