[to #42322933] modify space task name

modelscope/metainfo.py

@@ -26,7 +26,9 @@ class Models(object):
     structbert = 'structbert'
     veco = 'veco'
     translation = 'csanmt-translation'
-    space = 'space'
+    space_dst = 'space-dst'
+    space_intent = 'space-intent'
+    space_modeling = 'space-modeling'
     tcrf = 'transformer-crf'
     bart = 'bart'
     gpt3 = 'gpt3'
@@ -116,7 +118,7 @@ class Pipelines(object):
     csanmt_translation = 'csanmt-translation'
     nli = 'nli'
     dialog_intent_prediction = 'dialog-intent-prediction'
-    task_oriented_conversation = 'task-oriented-conversation'
+    dialog_modeling = 'dialog-modeling'
     dialog_state_tracking = 'dialog-state-tracking'
     zero_shot_classification = 'zero-shot-classification'
     text_error_correction = 'text-error-correction'

modelscope/models/nlp/space/space_for_dialog_intent_prediction.py

@@ -16,7 +16,7 @@ __all__ = ['SpaceForDialogIntent']
 
 
 @MODELS.register_module(
-    Tasks.dialog_intent_prediction, module_name=Models.space)
+    Tasks.task_oriented_conversation, module_name=Models.space_intent)
 class SpaceForDialogIntent(TorchModel):
 
     def __init__(self, model_dir: str, *args, **kwargs):

modelscope/models/nlp/space/space_for_dialog_modeling.py

@@ -16,7 +16,7 @@ __all__ = ['SpaceForDialogModeling']
 
 
 @MODELS.register_module(
-    Tasks.task_oriented_conversation, module_name=Models.space)
+    Tasks.task_oriented_conversation, module_name=Models.space_modeling)
 class SpaceForDialogModeling(TorchModel):
 
     def __init__(self, model_dir: str, *args, **kwargs):
@@ -34,8 +34,10 @@ class SpaceForDialogModeling(TorchModel):
             Config.from_file(
                 os.path.join(self.model_dir, ModelFile.CONFIGURATION)))
 
-        self.config.use_gpu = True if 'device' not in kwargs or kwargs[
-            'device'] == 'gpu' else False
+        import torch
+        self.config.use_gpu = True if (
+            'device' not in kwargs or kwargs['device']
+            == 'gpu') and torch.cuda.is_available() else False
 
         self.text_field = kwargs.pop(
             'text_field',

modelscope/models/nlp/space/space_for_dialog_state_tracking.py

@@ -9,7 +9,8 @@ from modelscope.utils.constant import Tasks
 __all__ = ['SpaceForDialogStateTracking']
 
 
-@MODELS.register_module(Tasks.dialog_state_tracking, module_name=Models.space)
+@MODELS.register_module(
+    Tasks.task_oriented_conversation, module_name=Models.space_dst)
 class SpaceForDialogStateTracking(TorchModel):
 
     def __init__(self, model_dir: str, *args, **kwargs):

modelscope/outputs.py

@@ -320,7 +320,7 @@ TASK_OUTPUTS = {
     Tasks.fill_mask: [OutputKeys.TEXT],
 
     # (Deprecated) dialog intent prediction result for single sample
-    # {'pred': array([2.62349960e-03, 4.12110658e-03, 4.12748595e-05, 3.77560973e-05,
+    # {'output': {'prediction': array([2.62349960e-03, 4.12110658e-03, 4.12748595e-05, 3.77560973e-05,
     #        1.08599677e-04, 1.72710388e-05, 2.95618793e-05, 1.93638436e-04,
     #        6.45841064e-05, 1.15997791e-04, 5.11605394e-05, 9.87020373e-01,
     #        2.66957268e-05, 4.72324500e-05, 9.74208378e-05, 4.18022355e-05,
@@ -339,50 +339,49 @@ TASK_OUTPUTS = {
     #        3.61441926e-05, 3.38475402e-05, 3.44323053e-05, 5.70138109e-05,
     #        4.31488479e-05, 4.94503947e-05, 4.30105974e-05, 1.00963116e-04,
     #        2.82062047e-05, 1.15582036e-04, 4.48261271e-05, 3.99339879e-05,
-    #        7.27692823e-05], dtype=float32), 'label_pos': array([11]), 'label': 'lost_or_stolen_card'}
-    Tasks.dialog_intent_prediction:
-    [OutputKeys.PREDICTION, OutputKeys.LABEL_POS, OutputKeys.LABEL],
+    #        7.27692823e-05], dtype=float32), 'label_pos': array([11]), 'label': 'lost_or_stolen_card'}}
 
     # (Deprecated) dialog modeling prediction result for single sample
-    # sys : ['you', 'are', 'welcome', '.', 'have', 'a', 'great', 'day', '!']
-    Tasks.task_oriented_conversation: [OutputKeys.RESPONSE],
+    # {'output' : ['you', 'are', 'welcome', '.', 'have', 'a', 'great', 'day', '!']}
 
     # (Deprecated) dialog state tracking result for single sample
     # {
-    #     "dialog_states": {
-    #         "taxi-leaveAt": "none",
-    #         "taxi-destination": "none",
-    #         "taxi-departure": "none",
-    #         "taxi-arriveBy": "none",
-    #         "restaurant-book_people": "none",
-    #         "restaurant-book_day": "none",
-    #         "restaurant-book_time": "none",
-    #         "restaurant-food": "none",
-    #         "restaurant-pricerange": "none",
-    #         "restaurant-name": "none",
-    #         "restaurant-area": "none",
-    #         "hotel-book_people": "none",
-    #         "hotel-book_day": "none",
-    #         "hotel-book_stay": "none",
-    #         "hotel-name": "none",
-    #         "hotel-area": "none",
-    #         "hotel-parking": "none",
-    #         "hotel-pricerange": "cheap",
-    #         "hotel-stars": "none",
-    #         "hotel-internet": "none",
-    #         "hotel-type": "true",
-    #         "attraction-type": "none",
-    #         "attraction-name": "none",
-    #         "attraction-area": "none",
-    #         "train-book_people": "none",
-    #         "train-leaveAt": "none",
-    #         "train-destination": "none",
-    #         "train-day": "none",
-    #         "train-arriveBy": "none",
-    #         "train-departure": "none"
+    #     "output":{
+    #         "dialog_states": {
+    #             "taxi-leaveAt": "none",
+    #             "taxi-destination": "none",
+    #             "taxi-departure": "none",
+    #             "taxi-arriveBy": "none",
+    #             "restaurant-book_people": "none",
+    #             "restaurant-book_day": "none",
+    #             "restaurant-book_time": "none",
+    #             "restaurant-food": "none",
+    #             "restaurant-pricerange": "none",
+    #             "restaurant-name": "none",
+    #             "restaurant-area": "none",
+    #             "hotel-book_people": "none",
+    #             "hotel-book_day": "none",
+    #             "hotel-book_stay": "none",
+    #             "hotel-name": "none",
+    #             "hotel-area": "none",
+    #             "hotel-parking": "none",
+    #             "hotel-pricerange": "cheap",
+    #             "hotel-stars": "none",
+    #             "hotel-internet": "none",
+    #             "hotel-type": "true",
+    #             "attraction-type": "none",
+    #             "attraction-name": "none",
+    #             "attraction-area": "none",
+    #             "train-book_people": "none",
+    #             "train-leaveAt": "none",
+    #             "train-destination": "none",
+    #             "train-day": "none",
+    #             "train-arriveBy": "none",
+    #             "train-departure": "none"
+    #         }
     #     }
     # }
-    Tasks.dialog_state_tracking: [OutputKeys.DIALOG_STATES],
+    Tasks.task_oriented_conversation: [OutputKeys.OUTPUT],
 
     # ============ audio tasks ===================
     # asr result for single sample

modelscope/pipelines/builder.py

@@ -48,13 +48,8 @@ DEFAULT_MODEL_FOR_PIPELINE = {
     Tasks.zero_shot_classification:
     (Pipelines.zero_shot_classification,
      'damo/nlp_structbert_zero-shot-classification_chinese-base'),
-    Tasks.dialog_intent_prediction:
-    (Pipelines.dialog_intent_prediction,
-     'damo/nlp_space_dialog-intent-prediction'),
-    Tasks.task_oriented_conversation: (Pipelines.task_oriented_conversation,
+    Tasks.task_oriented_conversation: (Pipelines.dialog_modeling,
                                        'damo/nlp_space_dialog-modeling'),
-    Tasks.dialog_state_tracking: (Pipelines.dialog_state_tracking,
-                                  'damo/nlp_space_dialog-state-tracking'),
     Tasks.text_error_correction:
     (Pipelines.text_error_correction,
      'damo/nlp_bart_text-error-correction_chinese'),

modelscope/pipelines/nlp/__init__.py

@@ -5,7 +5,7 @@ from modelscope.utils.import_utils import LazyImportModule
 
 if TYPE_CHECKING:
     from .dialog_intent_prediction_pipeline import DialogIntentPredictionPipeline
-    from .task_oriented_conversation_pipeline import TaskOrientedConversationPipeline
+    from .dialog_modeling_pipeline import DialogModelingPipeline
     from .dialog_state_tracking_pipeline import DialogStateTrackingPipeline
     from .fill_mask_pipeline import FillMaskPipeline
     from .named_entity_recognition_pipeline import NamedEntityRecognitionPipeline
@@ -24,8 +24,7 @@ else:
     _import_structure = {
         'dialog_intent_prediction_pipeline':
         ['DialogIntentPredictionPipeline'],
-        'task_oriented_conversation_pipeline':
-        ['TaskOrientedConversationPipeline'],
+        'dialog_modeling_pipeline': ['DialogModelingPipeline'],
         'dialog_state_tracking_pipeline': ['DialogStateTrackingPipeline'],
         'fill_mask_pipeline': ['FillMaskPipeline'],
         'single_sentence_classification_pipeline':

modelscope/pipelines/nlp/dialog_intent_prediction_pipeline.py

@@ -15,7 +15,7 @@ __all__ = ['DialogIntentPredictionPipeline']
 
 
 @PIPELINES.register_module(
-    Tasks.dialog_intent_prediction,
+    Tasks.task_oriented_conversation,
     module_name=Pipelines.dialog_intent_prediction)
 class DialogIntentPredictionPipeline(Pipeline):
 
@@ -51,10 +51,10 @@ class DialogIntentPredictionPipeline(Pipeline):
         pred = inputs['pred']
         pos = np.where(pred == np.max(pred))
 
-        result = {
-            OutputKeys.PREDICTION: pred,
-            OutputKeys.LABEL_POS: pos[0],
-            OutputKeys.LABEL: self.categories[pos[0][0]]
+        return {
+            OutputKeys.OUTPUT: {
+                OutputKeys.PREDICTION: pred,
+                OutputKeys.LABEL_POS: pos[0],
+                OutputKeys.LABEL: self.categories[pos[0][0]]
+            }
         }
-
-        return result

modelscope/pipelines/nlp/task_oriented_conversation_pipeline.py → modelscope/pipelines/nlp/dialog_modeling_pipeline.py

@@ -11,13 +11,12 @@ from modelscope.pipelines.builder import PIPELINES
 from modelscope.preprocessors import DialogModelingPreprocessor
 from modelscope.utils.constant import Tasks
 
-__all__ = ['TaskOrientedConversationPipeline']
+__all__ = ['DialogModelingPipeline']
 
 
 @PIPELINES.register_module(
-    Tasks.task_oriented_conversation,
-    module_name=Pipelines.task_oriented_conversation)
-class TaskOrientedConversationPipeline(Pipeline):
+    Tasks.task_oriented_conversation, module_name=Pipelines.dialog_modeling)
+class DialogModelingPipeline(Pipeline):
 
     def __init__(self,
                  model: Union[SpaceForDialogModeling, str],
@@ -51,6 +50,6 @@ class TaskOrientedConversationPipeline(Pipeline):
             inputs['resp'])
         assert len(sys_rsp) > 2
         sys_rsp = sys_rsp[1:len(sys_rsp) - 1]
-        inputs[OutputKeys.RESPONSE] = sys_rsp
+        inputs[OutputKeys.OUTPUT] = sys_rsp
 
         return inputs

modelscope/pipelines/nlp/dialog_state_tracking_pipeline.py

@@ -13,7 +13,8 @@ __all__ = ['DialogStateTrackingPipeline']
 
 
 @PIPELINES.register_module(
-    Tasks.dialog_state_tracking, module_name=Pipelines.dialog_state_tracking)
+    Tasks.task_oriented_conversation,
+    module_name=Pipelines.dialog_state_tracking)
 class DialogStateTrackingPipeline(Pipeline):
 
     def __init__(self,
@@ -63,7 +64,7 @@ class DialogStateTrackingPipeline(Pipeline):
                                 _outputs[5], unique_ids, input_ids_unmasked,
                                 values, inform, prefix, ds)
 
-        return {OutputKeys.DIALOG_STATES: ds}
+        return {OutputKeys.OUTPUT: ds}
 
 
 def predict_and_format(config, tokenizer, features, per_slot_class_logits,

tests/pipelines/test_dialog_intent_prediction.py

@@ -20,7 +20,7 @@ class DialogIntentPredictionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_by_direct_model_download(self):
-        cache_path = snapshot_download(self.model_id)
+        cache_path = snapshot_download(self.model_id, revision='update')
         preprocessor = DialogIntentPredictionPreprocessor(model_dir=cache_path)
         model = SpaceForDialogIntent(
             model_dir=cache_path,
@@ -31,7 +31,7 @@ class DialogIntentPredictionTest(unittest.TestCase):
             DialogIntentPredictionPipeline(
                 model=model, preprocessor=preprocessor),
             pipeline(
-                task=Tasks.dialog_intent_prediction,
+                task=Tasks.task_oriented_conversation,
                 model=model,
                 preprocessor=preprocessor)
         ]
@@ -41,7 +41,7 @@ class DialogIntentPredictionTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_model_from_modelhub(self):
-        model = Model.from_pretrained(self.model_id)
+        model = Model.from_pretrained(self.model_id, revision='update')
         preprocessor = DialogIntentPredictionPreprocessor(
             model_dir=model.model_dir)
 
@@ -49,7 +49,7 @@ class DialogIntentPredictionTest(unittest.TestCase):
             DialogIntentPredictionPipeline(
                 model=model, preprocessor=preprocessor),
             pipeline(
-                task=Tasks.dialog_intent_prediction,
+                task=Tasks.task_oriented_conversation,
                 model=model,
                 preprocessor=preprocessor)
         ]
@@ -60,17 +60,14 @@ class DialogIntentPredictionTest(unittest.TestCase):
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_model_name(self):
         pipelines = [
-            pipeline(task=Tasks.dialog_intent_prediction, model=self.model_id)
+            pipeline(
+                task=Tasks.task_oriented_conversation,
+                model=self.model_id,
+                model_revision='update')
         ]
         for my_pipeline, item in list(zip(pipelines, self.test_case)):
             print(my_pipeline(item))
 
-    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
-    def test_run_with_default_model(self):
-        pipelines = [pipeline(task=Tasks.dialog_intent_prediction)]
-        for my_pipeline, item in list(zip(pipelines, self.test_case)):
-            print(my_pipeline(item))
-
 
 if __name__ == '__main__':
     unittest.main()

tests/pipelines/test_task_oriented_conversation.py → tests/pipelines/test_dialog_modeling.py

@@ -5,14 +5,15 @@ from typing import List
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.models import Model
 from modelscope.models.nlp import SpaceForDialogModeling
+from modelscope.outputs import OutputKeys
 from modelscope.pipelines import pipeline
-from modelscope.pipelines.nlp import TaskOrientedConversationPipeline
+from modelscope.pipelines.nlp import DialogModelingPipeline
 from modelscope.preprocessors import DialogModelingPreprocessor
 from modelscope.utils.constant import Tasks
 from modelscope.utils.test_utils import test_level
 
 
-class TaskOrientedConversationTest(unittest.TestCase):
+class DialogModelingTest(unittest.TestCase):
     model_id = 'damo/nlp_space_dialog-modeling'
     test_case = {
         'sng0073': {
@@ -92,23 +93,25 @@ class TaskOrientedConversationTest(unittest.TestCase):
     }
 
     def generate_and_print_dialog_response(
-            self, pipelines: List[TaskOrientedConversationPipeline]):
+            self, pipelines: List[DialogModelingPipeline]):
 
         result = {}
+        pipeline_len = len(pipelines)
         for step, item in enumerate(self.test_case['sng0073']['log']):
             user = item['user']
             print('user: {}'.format(user))
 
-            result = pipelines[step % 2]({
+            result = pipelines[step % pipeline_len]({
                 'user_input': user,
                 'history': result
             })
-            print('response : {}'.format(result['response']))
+            print('response : {}'.format(result[OutputKeys.OUTPUT]))
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_by_direct_model_download(self):
 
-        cache_path = snapshot_download(self.model_id)
+        cache_path = snapshot_download(
+            self.model_id, revision='task_oriented_conversation')
 
         preprocessor = DialogModelingPreprocessor(model_dir=cache_path)
         model = SpaceForDialogModeling(
@@ -116,27 +119,18 @@ class TaskOrientedConversationTest(unittest.TestCase):
             text_field=preprocessor.text_field,
             config=preprocessor.config)
         pipelines = [
-            TaskOrientedConversationPipeline(
-                model=model, preprocessor=preprocessor),
-            pipeline(
-                task=Tasks.task_oriented_conversation,
-                model=model,
-                preprocessor=preprocessor)
+            DialogModelingPipeline(model=model, preprocessor=preprocessor)
         ]
         self.generate_and_print_dialog_response(pipelines)
 
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_model_from_modelhub(self):
-        model = Model.from_pretrained(self.model_id)
+        model = Model.from_pretrained(
+            self.model_id, revision='task_oriented_conversation')
         preprocessor = DialogModelingPreprocessor(model_dir=model.model_dir)
 
         pipelines = [
-            TaskOrientedConversationPipeline(
-                model=model, preprocessor=preprocessor),
-            pipeline(
-                task=Tasks.task_oriented_conversation,
-                model=model,
-                preprocessor=preprocessor)
+            DialogModelingPipeline(model=model, preprocessor=preprocessor)
         ]
 
         self.generate_and_print_dialog_response(pipelines)
@@ -145,17 +139,18 @@ class TaskOrientedConversationTest(unittest.TestCase):
     def test_run_with_model_name(self):
         pipelines = [
             pipeline(
-                task=Tasks.task_oriented_conversation, model=self.model_id),
-            pipeline(
-                task=Tasks.task_oriented_conversation, model=self.model_id)
+                task=Tasks.task_oriented_conversation,
+                model=self.model_id,
+                model_revision='task_oriented_conversation')
         ]
         self.generate_and_print_dialog_response(pipelines)
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_with_default_model(self):
         pipelines = [
-            pipeline(task=Tasks.task_oriented_conversation),
-            pipeline(task=Tasks.task_oriented_conversation)
+            pipeline(
+                task=Tasks.task_oriented_conversation,
+                model_revision='task_oriented_conversation')
         ]
         self.generate_and_print_dialog_response(pipelines)
 

tests/pipelines/test_dialog_state_tracking.py

@@ -5,6 +5,7 @@ from typing import List
 from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.models import Model
 from modelscope.models.nlp import SpaceForDialogStateTracking
+from modelscope.outputs import OutputKeys
 from modelscope.pipelines import pipeline
 from modelscope.pipelines.nlp import DialogStateTrackingPipeline
 from modelscope.preprocessors import DialogStateTrackingPreprocessor
@@ -94,11 +95,11 @@ class DialogStateTrackingTest(unittest.TestCase):
             })
             print(json.dumps(result))
 
-            history_states.extend([result['dialog_states'], {}])
+            history_states.extend([result[OutputKeys.OUTPUT], {}])
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_by_direct_model_download(self):
-        cache_path = snapshot_download(self.model_id)
+        cache_path = snapshot_download(self.model_id, revision='update')
 
         model = SpaceForDialogStateTracking(cache_path)
         preprocessor = DialogStateTrackingPreprocessor(model_dir=cache_path)
@@ -106,7 +107,7 @@ class DialogStateTrackingTest(unittest.TestCase):
             DialogStateTrackingPipeline(
                 model=model, preprocessor=preprocessor),
             pipeline(
-                task=Tasks.dialog_state_tracking,
+                task=Tasks.task_oriented_conversation,
                 model=model,
                 preprocessor=preprocessor)
         ]
@@ -114,14 +115,15 @@ class DialogStateTrackingTest(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_model_from_modelhub(self):
-        model = Model.from_pretrained(self.model_id)
+        model = Model.from_pretrained(self.model_id, revision='update')
+
         preprocessor = DialogStateTrackingPreprocessor(
             model_dir=model.model_dir)
         pipelines = [
             DialogStateTrackingPipeline(
                 model=model, preprocessor=preprocessor),
             pipeline(
-                task=Tasks.dialog_state_tracking,
+                task=Tasks.task_oriented_conversation,
                 model=model,
                 preprocessor=preprocessor)
         ]
@@ -131,15 +133,13 @@ class DialogStateTrackingTest(unittest.TestCase):
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_model_name(self):
         pipelines = [
-            pipeline(task=Tasks.dialog_state_tracking, model=self.model_id)
+            pipeline(
+                task=Tasks.task_oriented_conversation,
+                model=self.model_id,
+                model_revision='update')
         ]
         self.tracking_and_print_dialog_states(pipelines)
 
-    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
-    def test_run_with_default_model(self):
-        pipelines = [pipeline(task=Tasks.dialog_state_tracking)]
-        self.tracking_and_print_dialog_states(pipelines)
-
 
 if __name__ == '__main__':
     unittest.main()