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add pop for base class parameters

Browse Source 
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12622643
This commit is contained in:
yuze.zyz
2023-05-15 17:46:32 +08:00
parent b9c8c99776
commit e325862be8
15 changed files with 32 additions and 16 deletions
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3
modelscope/pipelines/nlp/dialog_intent_prediction_pipeline.py
View File

@@ -41,7 +41,8 @@ class DialogIntentPredictionPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
if preprocessor is None:
self.preprocessor = DialogIntentPredictionPreprocessor(
self.model.model_dir, **kwargs)

3
modelscope/pipelines/nlp/document_grounded_dialog_generate_pipeline.py
View File

@@ -47,7 +47,8 @@ class DocumentGroundedDialogGeneratePipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
if preprocessor is None:
self.preprocessor = DocumentGroundedDialogGeneratePreprocessor(

3
modelscope/pipelines/nlp/document_grounded_dialog_rerank_pipeline.py
View File

@@ -65,7 +65,8 @@ class DocumentGroundedDialogRerankPipeline(Pipeline):
device=device,
auto_collate=auto_collate,
seed=seed,
**kwarg)
compile=kwarg.pop('compile', False),
compile_options=kwarg.pop('compile_options', {}))
self.model = model
self.preprocessor = preprocessor
self.device = device

3
modelscope/pipelines/nlp/document_grounded_dialog_retrieval_pipeline.py
View File

@@ -56,7 +56,8 @@ class DocumentGroundedDialogRetrievalPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
if preprocessor is None:
self.preprocessor = DocumentGroundedDialogRetrievalPreprocessor(

3
modelscope/pipelines/nlp/feature_extraction_pipeline.py
View File

@@ -54,7 +54,8 @@ class FeatureExtractionPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/fill_mask_pipeline.py
View File

@@ -63,7 +63,8 @@ class FillMaskPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/named_entity_recognition_pipeline.py
View File

@@ -56,7 +56,8 @@ class NamedEntityRecognitionPipeline(TokenClassificationPipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/sentence_embedding_pipeline.py
View File

@@ -43,7 +43,8 @@ class SentenceEmbeddingPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

5
modelscope/pipelines/nlp/siamese_uie_pipeline.py
View File

@@ -21,7 +21,7 @@ from modelscope.outputs import OutputKeys
from modelscope.pipelines.base import Pipeline
from modelscope.pipelines.builder import PIPELINES
from modelscope.preprocessors import Preprocessor, SiameseUiePreprocessor
from modelscope.utils.constant import Tasks
from modelscope.utils.constant import ModelFile, Tasks
Input = Union[str, tuple, MsDataset, 'Image.Image', 'numpy.ndarray']
@@ -68,7 +68,8 @@ class SiameseUiePipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/table_question_answering_pipeline.py
View File

@@ -52,7 +52,8 @@ class TableQuestionAnsweringPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/text_generation_pipeline.py
View File

@@ -59,7 +59,8 @@ class TextGenerationPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/text_ranking_pipeline.py
View File

@@ -44,7 +44,8 @@ class TextRankingPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

4
modelscope/pipelines/nlp/token_classification_pipeline.py
View File

@@ -51,7 +51,9 @@ class TokenClassificationPipeline(Pipeline):
preprocessor=preprocessor,
config_file=config_file,
device=device,
auto_collate=auto_collate)
auto_collate=auto_collate,
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
assert isinstance(self.model, Model), \
f'please check whether model config exists in {ModelFile.CONFIGURATION}'

3
modelscope/pipelines/nlp/user_satisfaction_estimation_pipeline.py
View File

@@ -51,7 +51,8 @@ class UserSatisfactionEstimationPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
if hasattr(self.preprocessor, 'id2label'):
self.id2label = self.preprocessor.id2label

3
modelscope/pipelines/nlp/zero_shot_classification_pipeline.py
View File

@@ -67,7 +67,8 @@ class ZeroShotClassificationPipeline(Pipeline):
config_file=config_file,
device=device,
auto_collate=auto_collate,
**kwargs)
compile=kwargs.pop('compile', False),
compile_options=kwargs.pop('compile_options', {}))
self.entailment_id = 0
self.contradiction_id = 2