modify model name

modelscope/models/__init__.py

@@ -10,6 +10,5 @@ from .multi_modal import OfaForImageCaptioning
 from .nlp import (BertForMaskedLM, BertForSequenceClassification, SbertForNLI,
                   SbertForSentenceSimilarity, SbertForSentimentClassification,
                   SbertForTokenClassification, SpaceForDialogIntentModel,
-                  SpaceForDialogModelingModel,
-                  SpaceForDialogStateTrackingModel, StructBertForMaskedLM,
-                  VecoForMaskedLM)
+                  SpaceForDialogModelingModel, SpaceForDialogStateTracking,
+                  StructBertForMaskedLM, VecoForMaskedLM)

modelscope/models/nlp/space/dialog_state_tracking_model.py

@@ -6,11 +6,11 @@ from ....utils.nlp.space.utils_dst import batch_to_device
 from ...base import Model, Tensor
 from ...builder import MODELS
 
-__all__ = ['SpaceForDialogStateTrackingModel']
+__all__ = ['SpaceForDialogStateTracking']
 
 
 @MODELS.register_module(Tasks.dialog_state_tracking, module_name=r'space')
-class SpaceForDialogStateTrackingModel(Model):
+class SpaceForDialogStateTracking(Model):
 
     def __init__(self, model_dir: str, *args, **kwargs):
         """initialize the test generation model from the `model_dir` path.

modelscope/pipelines/nlp/dialog_state_tracking_pipeline.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict
 
 from ...metainfo import Pipelines
-from ...models import SpaceForDialogStateTrackingModel
+from ...models import SpaceForDialogStateTracking
 from ...preprocessors import DialogStateTrackingPreprocessor
 from ...utils.constant import Tasks
 from ..base import Pipeline
@@ -14,7 +14,7 @@ __all__ = ['DialogStateTrackingPipeline']
     Tasks.dialog_state_tracking, module_name=Pipelines.dialog_state_tracking)
 class DialogStateTrackingPipeline(Pipeline):
 
-    def __init__(self, model: SpaceForDialogStateTrackingModel,
+    def __init__(self, model: SpaceForDialogStateTracking,
                  preprocessor: DialogStateTrackingPreprocessor, **kwargs):
         """use `model` and `preprocessor` to create a nlp text classification pipeline for prediction
 

tests/pipelines/nlp/test_dialog_state_tracking.py

@@ -5,7 +5,7 @@ import tempfile
 import unittest
 
 from modelscope.hub.snapshot_download import snapshot_download
-from modelscope.models import Model, SpaceForDialogStateTrackingModel
+from modelscope.models import Model, SpaceForDialogStateTracking
 from modelscope.pipelines import DialogStateTrackingPipeline, pipeline
 from modelscope.preprocessors import DialogStateTrackingPreprocessor
 from modelscope.utils.constant import Tasks
@@ -81,7 +81,7 @@ class DialogStateTrackingTest(unittest.TestCase):
         cache_path = '/Users/yangliu/Space/maas_model/nlp_space_dialog-state-tracking'
         # cache_path = snapshot_download(self.model_id)
 
-        model = SpaceForDialogStateTrackingModel(cache_path)
+        model = SpaceForDialogStateTracking(cache_path)
         preprocessor = DialogStateTrackingPreprocessor(model_dir=cache_path)
         pipelines = [
             DialogStateTrackingPipeline(
@@ -94,20 +94,19 @@ class DialogStateTrackingTest(unittest.TestCase):
 
         pipelines_len = len(pipelines)
         import json
-        for _test_case in self.test_case:
-            history_states = [{}]
-            utter = {}
-            for step, item in enumerate(_test_case):
-                utter.update(item)
-                result = pipelines[step % pipelines_len]({
-                    'utter':
-                    utter,
-                    'history_states':
-                    history_states
-                })
-                print(json.dumps(result))
+        history_states = [{}]
+        utter = {}
+        for step, item in enumerate(self.test_case):
+            utter.update(item)
+            result = pipelines[step % pipelines_len]({
+                'utter':
+                utter,
+                'history_states':
+                history_states
+            })
+            print(json.dumps(result))
 
-                history_states.extend([result['dialog_states'], {}])
+            history_states.extend([result['dialog_states'], {}])
 
     @unittest.skip('test with snapshot_download')
     def test_run_with_model_from_modelhub(self):