revise based on comment except chinease comment

modelscope/models/nlp/bert_for_sequence_classification.py

@@ -4,8 +4,8 @@ from typing import Any, Dict
 import json
 import numpy as np
 
-from modelscope.metainfo import Models
-from modelscope.utils.constant import Tasks
+from ...metainfo import Models
+from ...utils.constant import Tasks
 from ..base import Model
 from ..builder import MODELS
 

modelscope/models/nlp/sbert_for_sentence_similarity.py

@@ -1,5 +1,5 @@
-from modelscope.metainfo import Models
-from modelscope.utils.constant import Tasks
+from ...metainfo import Models
+from ...utils.constant import Tasks
 from ..builder import MODELS
 from .sbert_for_sequence_classification import \
     SbertForSequenceClassificationBase

modelscope/models/nlp/sbert_for_sentiment_classification.py

@@ -1,5 +1,5 @@
-from modelscope.metainfo import Models
-from modelscope.utils.constant import Tasks
+from ...metainfo import Models
+from ...utils.constant import Tasks
 from ..builder import MODELS
 from .sbert_for_sequence_classification import \
     SbertForSequenceClassificationBase

modelscope/models/nlp/sbert_for_token_classification.py

@@ -3,8 +3,8 @@ from typing import Any, Dict, Union
 import numpy as np
 import torch
 
-from modelscope.metainfo import Models
-from modelscope.utils.constant import Tasks
+from ...metainfo import Models
+from ...utils.constant import Tasks
 from ..base import Model, Tensor
 from ..builder import MODELS
 

modelscope/models/nlp/space/dialog_intent_prediction_model.py

@@ -2,19 +2,19 @@ import os
 from typing import Any, Dict
 
 from ....preprocessors.space.fields.intent_field import IntentBPETextField
+from ....trainers.nlp.space.trainer.intent_trainer import IntentTrainer
 from ....utils.config import Config
-from ....utils.constant import Tasks
+from ....utils.constant import ModelFile, Tasks
 from ...base import Model, Tensor
 from ...builder import MODELS
-from .application.intent_app import IntentTrainer
 from .model.generator import Generator
-from .model.model_base import ModelBase
+from .model.model_base import SpaceModelBase
 
-__all__ = ['DialogIntentModel']
+__all__ = ['SpaceForDialogIntentModel']
 
 
 @MODELS.register_module(Tasks.dialog_intent_prediction, module_name=r'space')
-class DialogIntentModel(Model):
+class SpaceForDialogIntentModel(Model):
 
     def __init__(self, model_dir: str, *args, **kwargs):
         """initialize the test generation model from the `model_dir` path.
@@ -30,13 +30,13 @@ class DialogIntentModel(Model):
         self.config = kwargs.pop(
             'config',
             Config.from_file(
-                os.path.join(self.model_dir, 'configuration.json')))
+                os.path.join(self.model_dir, ModelFile.CONFIGURATION)))
         self.text_field = kwargs.pop(
             'text_field',
             IntentBPETextField(self.model_dir, config=self.config))
 
         self.generator = Generator.create(self.config, reader=self.text_field)
-        self.model = ModelBase.create(
+        self.model = SpaceModelBase.create(
             model_dir=model_dir,
             config=self.config,
             reader=self.text_field,

modelscope/models/nlp/space/dialog_modeling_model.py

@@ -2,19 +2,19 @@ import os
 from typing import Any, Dict, Optional
 
 from ....preprocessors.space.fields.gen_field import MultiWOZBPETextField
+from ....trainers.nlp.space.trainer.gen_trainer import MultiWOZTrainer
 from ....utils.config import Config
-from ....utils.constant import Tasks
+from ....utils.constant import ModelFile, Tasks
 from ...base import Model, Tensor
 from ...builder import MODELS
-from .application.gen_app import MultiWOZTrainer
 from .model.generator import Generator
-from .model.model_base import ModelBase
+from .model.model_base import SpaceModelBase
 
-__all__ = ['DialogModelingModel']
+__all__ = ['SpaceForDialogModelingModel']
 
 
 @MODELS.register_module(Tasks.dialog_modeling, module_name=r'space')
-class DialogModelingModel(Model):
+class SpaceForDialogModelingModel(Model):
 
     def __init__(self, model_dir: str, *args, **kwargs):
         """initialize the test generation model from the `model_dir` path.
@@ -30,12 +30,12 @@ class DialogModelingModel(Model):
         self.config = kwargs.pop(
             'config',
             Config.from_file(
-                os.path.join(self.model_dir, 'configuration.json')))
+                os.path.join(self.model_dir, ModelFile.CONFIGURATION)))
         self.text_field = kwargs.pop(
             'text_field',
             MultiWOZBPETextField(self.model_dir, config=self.config))
         self.generator = Generator.create(self.config, reader=self.text_field)
-        self.model = ModelBase.create(
+        self.model = SpaceModelBase.create(
             model_dir=model_dir,
             config=self.config,
             reader=self.text_field,

modelscope/models/nlp/space/model/model_base.py

@@ -5,8 +5,10 @@ import os
 
 import torch.nn as nn
 
+from .....utils.constant import ModelFile
 
-class ModelBase(nn.Module):
+
+class SpaceModelBase(nn.Module):
     """
     Basic model wrapper for static graph and dygrpah.
     """
@@ -14,21 +16,22 @@ class ModelBase(nn.Module):
 
     @classmethod
     def register(cls, name):
-        ModelBase._registry[name] = cls
+        SpaceModelBase._registry[name] = cls
         return
 
     @staticmethod
     def by_name(name):
-        return ModelBase._registry[name]
+        return SpaceModelBase._registry[name]
 
     @staticmethod
     def create(model_dir, config, *args, **kwargs):
-        model_cls = ModelBase.by_name(config.Model.model)
+        model_cls = SpaceModelBase.by_name(config.Model.model)
         return model_cls(model_dir, config, *args, **kwargs)
 
     def __init__(self, model_dir, config):
-        super(ModelBase, self).__init__()
-        self.init_checkpoint = os.path.join(model_dir, 'pytorch_model.bin')
+        super(SpaceModelBase, self).__init__()
+        self.init_checkpoint = os.path.join(model_dir,
+                                            ModelFile.TORCH_MODEL_BIN_FILE)
         self.abandon_label = config.Dataset.abandon_label
         self.use_gpu = config.use_gpu
         self.gpu = config.Trainer.gpu

modelscope/models/nlp/space/model/unified_transformer.py

@@ -9,10 +9,10 @@ import torch.nn.functional as F
 
 from ..modules.embedder import Embedder
 from ..modules.transformer_block import TransformerBlock
-from .model_base import ModelBase
+from .model_base import SpaceModelBase
 
 
-class UnifiedTransformer(ModelBase):
+class UnifiedTransformer(SpaceModelBase):
     """
     Implement unified transformer.
     """

modelscope/pipelines/nlp/dialog_intent_prediction_pipeline.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict
 
 from ...metainfo import Pipelines
-from ...models.nlp import DialogIntentModel
+from ...models.nlp import SpaceForDialogIntentModel
 from ...preprocessors import DialogIntentPredictionPreprocessor
 from ...utils.constant import Tasks
 from ..base import Pipeline
@@ -15,7 +15,7 @@ __all__ = ['DialogIntentPredictionPipeline']
     module_name=Pipelines.dialog_intent_prediction)
 class DialogIntentPredictionPipeline(Pipeline):
 
-    def __init__(self, model: DialogIntentModel,
+    def __init__(self, model: SpaceForDialogIntentModel,
                  preprocessor: DialogIntentPredictionPreprocessor, **kwargs):
         """use `model` and `preprocessor` to create a nlp text classification pipeline for prediction
 

modelscope/pipelines/nlp/dialog_modeling_pipeline.py

@@ -1,9 +1,9 @@
 from typing import Any, Dict, Optional
 
-from modelscope.models.nlp import DialogModelingModel
-from modelscope.preprocessors import DialogModelingPreprocessor
-from modelscope.utils.constant import Tasks
 from ...metainfo import Pipelines
+from ...models.nlp import SpaceForDialogModelingModel
+from ...preprocessors import DialogModelingPreprocessor
+from ...utils.constant import Tasks
 from ..base import Pipeline, Tensor
 from ..builder import PIPELINES
 
@@ -14,7 +14,7 @@ __all__ = ['DialogModelingPipeline']
     Tasks.dialog_modeling, module_name=Pipelines.dialog_modeling)
 class DialogModelingPipeline(Pipeline):
 
-    def __init__(self, model: DialogModelingModel,
+    def __init__(self, model: SpaceForDialogModelingModel,
                  preprocessor: DialogModelingPreprocessor, **kwargs):
         """use `model` and `preprocessor` to create a nlp text classification pipeline for prediction
 

modelscope/preprocessors/space/dialog_intent_prediction_preprocessor.py

@@ -4,7 +4,7 @@ import os
 from typing import Any, Dict
 
 from ...utils.config import Config
-from ...utils.constant import Fields
+from ...utils.constant import Fields, ModelFile
 from ...utils.type_assert import type_assert
 from ..base import Preprocessor
 from ..builder import PREPROCESSORS
@@ -26,7 +26,7 @@ class DialogIntentPredictionPreprocessor(Preprocessor):
 
         self.model_dir: str = model_dir
         self.config = Config.from_file(
-            os.path.join(self.model_dir, 'configuration.json'))
+            os.path.join(self.model_dir, ModelFile.CONFIGURATION))
         self.text_field = IntentBPETextField(
             self.model_dir, config=self.config)
 

modelscope/preprocessors/space/dialog_modeling_preprocessor.py

@@ -4,7 +4,7 @@ import os
 from typing import Any, Dict
 
 from ...utils.config import Config
-from ...utils.constant import Fields
+from ...utils.constant import Fields, ModelFile
 from ...utils.type_assert import type_assert
 from ..base import Preprocessor
 from ..builder import PREPROCESSORS
@@ -26,7 +26,7 @@ class DialogModelingPreprocessor(Preprocessor):
 
         self.model_dir: str = model_dir
         self.config = Config.from_file(
-            os.path.join(self.model_dir, 'configuration.json'))
+            os.path.join(self.model_dir, ModelFile.CONFIGURATION))
         self.text_field = MultiWOZBPETextField(
             self.model_dir, config=self.config)
 

modelscope/preprocessors/space/fields/gen_field.py

@@ -8,6 +8,7 @@ from itertools import chain
 
 import numpy as np
 
+from ....utils.constant import ModelFile
 from ....utils.nlp.space import ontology, utils
 from ....utils.nlp.space.db_ops import MultiWozDB
 from ....utils.nlp.space.utils import list2np

tests/pipelines/test_dialog_intent_prediction.py

@@ -3,7 +3,7 @@ import unittest
 
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.models import Model
-from modelscope.models.nlp import DialogIntentModel
+from modelscope.models.nlp import SpaceForDialogIntentModel
 from modelscope.pipelines import DialogIntentPredictionPipeline, pipeline
 from modelscope.preprocessors import DialogIntentPredictionPreprocessor
 from modelscope.utils.constant import Tasks
@@ -20,7 +20,7 @@ class DialogIntentPredictionTest(unittest.TestCase):
     def test_run(self):
         cache_path = snapshot_download(self.model_id)
         preprocessor = DialogIntentPredictionPreprocessor(model_dir=cache_path)
-        model = DialogIntentModel(
+        model = SpaceForDialogIntentModel(
             model_dir=cache_path,
             text_field=preprocessor.text_field,
             config=preprocessor.config)

tests/pipelines/test_dialog_modeling.py

@@ -6,7 +6,7 @@ import unittest
 
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.models import Model
-from modelscope.models.nlp import DialogModelingModel
+from modelscope.models.nlp import SpaceForDialogModelingModel
 from modelscope.pipelines import DialogModelingPipeline, pipeline
 from modelscope.preprocessors import DialogModelingPreprocessor
 from modelscope.utils.constant import Tasks
@@ -97,7 +97,7 @@ class DialogModelingTest(unittest.TestCase):
         cache_path = snapshot_download(self.model_id)
 
         preprocessor = DialogModelingPreprocessor(model_dir=cache_path)
-        model = DialogModelingModel(
+        model = SpaceForDialogModelingModel(
             model_dir=cache_path,
             text_field=preprocessor.text_field,
             config=preprocessor.config)