diff --git a/modelscope/models/__init__.py b/modelscope/models/__init__.py index 62d91c20..629f2270 100644 --- a/modelscope/models/__init__.py +++ b/modelscope/models/__init__.py @@ -5,13 +5,7 @@ from .audio.tts.vocoder import Hifigan16k from .base import Model from .builder import MODELS, build_model from .multi_model import OfaForImageCaptioning -from .nlp import ( - BertForSequenceClassification, - SbertForNLI, - SbertForSentenceSimilarity, - SbertForSentimentClassification, - SbertForZeroShotClassification, - StructBertForMaskedLM, - VecoForMaskedLM, - SbertForTokenClassification, -) +from .nlp import (BertForSequenceClassification, SbertForNLI, + SbertForSentenceSimilarity, SbertForSentimentClassification, + SbertForTokenClassification, SbertForZeroShotClassification, + StructBertForMaskedLM, VecoForMaskedLM) diff --git a/modelscope/models/nlp/__init__.py b/modelscope/models/nlp/__init__.py index f57ea320..78b087e6 100644 --- a/modelscope/models/nlp/__init__.py +++ b/modelscope/models/nlp/__init__.py @@ -1,10 +1,10 @@ from .bert_for_sequence_classification import * # noqa F403 from .masked_language_model import * # noqa F403 -from .sbert_for_nli import * # noqa F403 from .palm_for_text_generation import * # noqa F403 +from .sbert_for_nli import * # noqa F403 from .sbert_for_sentence_similarity import * # noqa F403 -from .sbert_for_token_classification import * # noqa F403 from .sbert_for_sentiment_classification import * # noqa F403 +from .sbert_for_token_classification import * # noqa F403 +from .sbert_for_zero_shot_classification import * # noqa F403 from .space.dialog_intent_prediction_model import * # noqa F403 from .space.dialog_modeling_model import * # noqa F403 -from .sbert_for_zero_shot_classification import * # noqa F403 diff --git a/modelscope/models/nlp/masked_language_model.py b/modelscope/models/nlp/masked_language_model.py index 6a8c6626..0e488381 100644 --- a/modelscope/models/nlp/masked_language_model.py +++ b/modelscope/models/nlp/masked_language_model.py @@ -2,10 +2,10 @@ from typing import Any, Dict, Optional, Union import numpy as np +from ...metainfo import Models from ...utils.constant import Tasks from ..base import Model, Tensor from ..builder import MODELS -from ...metainfo import Models __all__ = ['StructBertForMaskedLM', 'VecoForMaskedLM', 'MaskedLMModelBase'] @@ -27,7 +27,7 @@ class MaskedLMModelBase(Model): @property def config(self): - if hasattr(self.model, "config"): + if hasattr(self.model, 'config'): return self.model.config return None diff --git a/modelscope/models/nlp/sbert_for_nli.py b/modelscope/models/nlp/sbert_for_nli.py index 1d7fc86b..a5a76b34 100644 --- a/modelscope/models/nlp/sbert_for_nli.py +++ b/modelscope/models/nlp/sbert_for_nli.py @@ -1,7 +1,8 @@ -from ...utils.constant import Tasks -from .sbert_for_sequence_classification import SbertForSequenceClassificationBase -from ..builder import MODELS from ...metainfo import Models +from ...utils.constant import Tasks +from ..builder import MODELS +from .sbert_for_sequence_classification import \ + SbertForSequenceClassificationBase __all__ = ['SbertForNLI'] @@ -17,5 +18,6 @@ class SbertForNLI(SbertForSequenceClassificationBase): model_cls (Optional[Any], optional): model loader, if None, use the default loader to load model weights, by default None. """ - super().__init__(model_dir, *args, model_args={"num_labels": 3}, **kwargs) + super().__init__( + model_dir, *args, model_args={'num_labels': 3}, **kwargs) assert self.model.config.num_labels == 3 diff --git a/modelscope/models/nlp/sbert_for_sentence_similarity.py b/modelscope/models/nlp/sbert_for_sentence_similarity.py index e893a301..25c38a2e 100644 --- a/modelscope/models/nlp/sbert_for_sentence_similarity.py +++ b/modelscope/models/nlp/sbert_for_sentence_similarity.py @@ -1,7 +1,8 @@ from modelscope.metainfo import Models from modelscope.utils.constant import Tasks -from .sbert_for_sequence_classification import SbertForSequenceClassificationBase from ..builder import MODELS +from .sbert_for_sequence_classification import \ + SbertForSequenceClassificationBase __all__ = ['SbertForSentenceSimilarity'] @@ -18,6 +19,7 @@ class SbertForSentenceSimilarity(SbertForSequenceClassificationBase): model_cls (Optional[Any], optional): model loader, if None, use the default loader to load model weights, by default None. """ - super().__init__(model_dir, *args, model_args={"num_labels": 2}, **kwargs) + super().__init__( + model_dir, *args, model_args={'num_labels': 2}, **kwargs) self.model_dir = model_dir assert self.model.config.num_labels == 2 diff --git a/modelscope/models/nlp/sbert_for_sentiment_classification.py b/modelscope/models/nlp/sbert_for_sentiment_classification.py index 10bfaa0f..72fb92f0 100644 --- a/modelscope/models/nlp/sbert_for_sentiment_classification.py +++ b/modelscope/models/nlp/sbert_for_sentiment_classification.py @@ -1,14 +1,14 @@ -from modelscope.utils.constant import Tasks -from .sbert_for_sequence_classification import SbertForSequenceClassificationBase -from ..builder import MODELS from modelscope.metainfo import Models +from modelscope.utils.constant import Tasks +from ..builder import MODELS +from .sbert_for_sequence_classification import \ + SbertForSequenceClassificationBase __all__ = ['SbertForSentimentClassification'] @MODELS.register_module( - Tasks.sentiment_classification, - module_name=Models.structbert) + Tasks.sentiment_classification, module_name=Models.structbert) class SbertForSentimentClassification(SbertForSequenceClassificationBase): def __init__(self, model_dir: str, *args, **kwargs): @@ -19,5 +19,6 @@ class SbertForSentimentClassification(SbertForSequenceClassificationBase): model_cls (Optional[Any], optional): model loader, if None, use the default loader to load model weights, by default None. """ - super().__init__(model_dir, *args, model_args={"num_labels": 2}, **kwargs) + super().__init__( + model_dir, *args, model_args={'num_labels': 2}, **kwargs) assert self.model.config.num_labels == 2 diff --git a/modelscope/models/nlp/sbert_for_sequence_classification.py b/modelscope/models/nlp/sbert_for_sequence_classification.py index 2e84d4cc..861b6fe2 100644 --- a/modelscope/models/nlp/sbert_for_sequence_classification.py +++ b/modelscope/models/nlp/sbert_for_sequence_classification.py @@ -1,11 +1,13 @@ -from torch import nn -from typing import Any, Dict -from ..base import Model -import numpy as np -import json import os +from typing import Any, Dict + +import json +import numpy as np import torch -from sofa.models.sbert.modeling_sbert import SbertPreTrainedModel, SbertModel +from sofa.models.sbert.modeling_sbert import SbertModel, SbertPreTrainedModel +from torch import nn + +from ..base import Model class SbertTextClassfier(SbertPreTrainedModel): @@ -27,9 +29,7 @@ class SbertTextClassfier(SbertPreTrainedModel): pooled_output = outputs[1] pooled_output = self.dropout(pooled_output) logits = self.classifier(pooled_output) - return { - "logits": logits - } + return {'logits': logits} class SbertForSequenceClassificationBase(Model): @@ -38,13 +38,17 @@ class SbertForSequenceClassificationBase(Model): super().__init__(model_dir, *args, **kwargs) if model_args is None: model_args = {} - self.model = SbertTextClassfier.from_pretrained(model_dir, **model_args) + self.model = SbertTextClassfier.from_pretrained( + model_dir, **model_args) self.id2label = {} self.label_path = os.path.join(self.model_dir, 'label_mapping.json') if os.path.exists(self.label_path): with open(self.label_path) as f: self.label_mapping = json.load(f) - self.id2label = {idx: name for name, idx in self.label_mapping.items()} + self.id2label = { + idx: name + for name, idx in self.label_mapping.items() + } def train(self): return self.model.train() @@ -59,7 +63,7 @@ class SbertForSequenceClassificationBase(Model): return self.model.forward(input_ids, token_type_ids) def postprocess(self, input, **kwargs): - logits = input["logits"] + logits = input['logits'] probs = logits.softmax(-1).numpy() pred = logits.argmax(-1).numpy() logits = logits.numpy() diff --git a/modelscope/models/nlp/sbert_for_token_classification.py b/modelscope/models/nlp/sbert_for_token_classification.py index 80d99283..fd175033 100644 --- a/modelscope/models/nlp/sbert_for_token_classification.py +++ b/modelscope/models/nlp/sbert_for_token_classification.py @@ -34,7 +34,7 @@ class SbertForTokenClassification(Model): def eval(self): return self.model.eval() - + def forward(self, input: Dict[str, Any]) -> Dict[str, Union[str, np.ndarray]]: """return the result by the model @@ -54,8 +54,9 @@ class SbertForTokenClassification(Model): input_ids = torch.tensor(input['input_ids']).unsqueeze(0) return {**self.model(input_ids), 'text': input['text']} - def postprocess(self, input: Dict[str, Tensor], **kwargs) -> Dict[str, Tensor]: - logits = input["logits"] + def postprocess(self, input: Dict[str, Tensor], + **kwargs) -> Dict[str, Tensor]: + logits = input['logits'] pred = torch.argmax(logits[0], dim=-1) pred = pred.numpy() rst = {'predictions': pred, 'logits': logits, 'text': input['text']} diff --git a/modelscope/models/nlp/sbert_for_zero_shot_classification.py b/modelscope/models/nlp/sbert_for_zero_shot_classification.py index 5a6e8d86..837bb41e 100644 --- a/modelscope/models/nlp/sbert_for_zero_shot_classification.py +++ b/modelscope/models/nlp/sbert_for_zero_shot_classification.py @@ -3,16 +3,15 @@ from typing import Any, Dict import numpy as np from modelscope.utils.constant import Tasks +from ...metainfo import Models from ..base import Model from ..builder import MODELS -from ...metainfo import Models __all__ = ['SbertForZeroShotClassification'] @MODELS.register_module( - Tasks.zero_shot_classification, - module_name=Models.structbert) + Tasks.zero_shot_classification, module_name=Models.structbert) class SbertForZeroShotClassification(Model): def __init__(self, model_dir: str, *args, **kwargs): @@ -31,7 +30,7 @@ class SbertForZeroShotClassification(Model): def eval(self): return self.model.eval() - + def forward(self, input: Dict[str, Any]) -> Dict[str, np.ndarray]: """return the result by the model diff --git a/modelscope/models/nlp/space/model/gen_unified_transformer.py b/modelscope/models/nlp/space/model/gen_unified_transformer.py index 157beaf5..0f1b1a83 100644 --- a/modelscope/models/nlp/space/model/gen_unified_transformer.py +++ b/modelscope/models/nlp/space/model/gen_unified_transformer.py @@ -3,8 +3,7 @@ IntentUnifiedTransformer """ import torch -from .unified_transformer import \ - UnifiedTransformer +from .unified_transformer import UnifiedTransformer class GenUnifiedTransformer(UnifiedTransformer): diff --git a/modelscope/models/nlp/space/model/unified_transformer.py b/modelscope/models/nlp/space/model/unified_transformer.py index 611c1bb8..2636553d 100644 --- a/modelscope/models/nlp/space/model/unified_transformer.py +++ b/modelscope/models/nlp/space/model/unified_transformer.py @@ -7,10 +7,9 @@ import torch import torch.nn as nn import torch.nn.functional as F -from .model_base import ModelBase from ..modules.embedder import Embedder -from ..modules.transformer_block import \ - TransformerBlock +from ..modules.transformer_block import TransformerBlock +from .model_base import ModelBase class UnifiedTransformer(ModelBase): diff --git a/modelscope/models/nlp/space/modules/transformer_block.py b/modelscope/models/nlp/space/modules/transformer_block.py index 45559297..5b6c79a5 100644 --- a/modelscope/models/nlp/space/modules/transformer_block.py +++ b/modelscope/models/nlp/space/modules/transformer_block.py @@ -6,8 +6,7 @@ import torch import torch.nn as nn from .feedforward import FeedForward -from .multihead_attention import \ - MultiheadAttention +from .multihead_attention import MultiheadAttention class TransformerBlock(nn.Module): diff --git a/modelscope/pipelines/nlp/fill_mask_pipeline.py b/modelscope/pipelines/nlp/fill_mask_pipeline.py index 22c80c05..b3dab177 100644 --- a/modelscope/pipelines/nlp/fill_mask_pipeline.py +++ b/modelscope/pipelines/nlp/fill_mask_pipeline.py @@ -1,15 +1,14 @@ -from typing import Dict, Optional, Union, Any +from typing import Any, Dict, Optional, Union 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 MaskedLMModelBase from ...preprocessors import FillMaskPreprocessor from ...utils.constant import Tasks from ..base import Pipeline, Tensor from ..builder import PIPELINES -from ...metainfo import Pipelines __all__ = ['FillMaskPipeline'] @@ -20,7 +19,7 @@ class FillMaskPipeline(Pipeline): def __init__(self, model: Union[MaskedLMModelBase, str], preprocessor: Optional[FillMaskPreprocessor] = None, - first_sequence="sentense", + first_sequence='sentense', **kwargs): """use `model` and `preprocessor` to create a nlp fill mask pipeline for prediction @@ -38,7 +37,8 @@ class FillMaskPipeline(Pipeline): first_sequence=first_sequence, second_sequence=None) fill_mask_model.eval() - super().__init__(model=fill_mask_model, preprocessor=preprocessor, **kwargs) + super().__init__( + model=fill_mask_model, preprocessor=preprocessor, **kwargs) self.preprocessor = preprocessor self.tokenizer = preprocessor.tokenizer self.mask_id = {'veco': 250001, 'sbert': 103} diff --git a/modelscope/pipelines/nlp/nli_pipeline.py b/modelscope/pipelines/nlp/nli_pipeline.py index b2358644..df065c05 100644 --- a/modelscope/pipelines/nlp/nli_pipeline.py +++ b/modelscope/pipelines/nlp/nli_pipeline.py @@ -1,31 +1,28 @@ import uuid from typing import Any, Dict, Union -import torch -import uuid -from typing import Any, Dict, Union import numpy as np +import torch -from ..base import Pipeline -from ..builder import PIPELINES from ...metainfo import Pipelines from ...models import Model from ...models.nlp import SbertForNLI from ...preprocessors import NLIPreprocessor from ...utils.constant import Tasks +from ..base import Pipeline +from ..builder import PIPELINES __all__ = ['NLIPipeline'] -@PIPELINES.register_module( - Tasks.nli, module_name=Pipelines.nli) +@PIPELINES.register_module(Tasks.nli, module_name=Pipelines.nli) class NLIPipeline(Pipeline): def __init__(self, model: Union[SbertForNLI, str], preprocessor: NLIPreprocessor = None, - first_sequence="first_sequence", - second_sequence="second_sequence", + first_sequence='first_sequence', + second_sequence='second_sequence', **kwargs): """use `model` and `preprocessor` to create a nlp text classification pipeline for prediction @@ -51,7 +48,8 @@ class NLIPipeline(Pipeline): with torch.no_grad(): return super().forward(inputs, **forward_params) - def postprocess(self, inputs: Dict[str, Any], **postprocess_params) -> Dict[str, str]: + def postprocess(self, inputs: Dict[str, Any], + **postprocess_params) -> Dict[str, str]: """process the prediction results Args: diff --git a/modelscope/pipelines/nlp/sentence_similarity_pipeline.py b/modelscope/pipelines/nlp/sentence_similarity_pipeline.py index 778f85ef..f6bcd72e 100644 --- a/modelscope/pipelines/nlp/sentence_similarity_pipeline.py +++ b/modelscope/pipelines/nlp/sentence_similarity_pipeline.py @@ -2,11 +2,12 @@ from typing import Any, Dict, Union import numpy as np import torch + from ...metainfo import Pipelines +from ...models import Model from ...models.nlp import SbertForSentenceSimilarity from ...preprocessors import SequenceClassificationPreprocessor from ...utils.constant import Tasks -from ...models import Model from ..base import Input, Pipeline from ..builder import PIPELINES @@ -20,8 +21,8 @@ class SentenceSimilarityPipeline(Pipeline): def __init__(self, model: Union[Model, str], preprocessor: SequenceClassificationPreprocessor = None, - first_sequence="first_sequence", - second_sequence="second_sequence", + first_sequence='first_sequence', + second_sequence='second_sequence', **kwargs): """use `model` and `preprocessor` to create a nlp sentence similarity pipeline for prediction @@ -50,7 +51,8 @@ class SentenceSimilarityPipeline(Pipeline): with torch.no_grad(): return super().forward(inputs, **forward_params) - def postprocess(self, inputs: Dict[str, Any], **postprocess_params) -> Dict[str, str]: + def postprocess(self, inputs: Dict[str, Any], + **postprocess_params) -> Dict[str, str]: """process the prediction results Args: diff --git a/modelscope/pipelines/nlp/sentiment_classification_pipeline.py b/modelscope/pipelines/nlp/sentiment_classification_pipeline.py index 8e458cf3..1f19cd8b 100644 --- a/modelscope/pipelines/nlp/sentiment_classification_pipeline.py +++ b/modelscope/pipelines/nlp/sentiment_classification_pipeline.py @@ -1,17 +1,18 @@ import os import uuid from typing import Any, Dict, Union -import torch + import json import numpy as np +import torch +from ...metainfo import Pipelines +from ...models import Model from ...models.nlp import SbertForSentimentClassification from ...preprocessors import SentimentClassificationPreprocessor from ...utils.constant import Tasks -from ...models import Model from ..base import Input, Pipeline from ..builder import PIPELINES -from ...metainfo import Pipelines __all__ = ['SentimentClassificationPipeline'] @@ -24,8 +25,8 @@ class SentimentClassificationPipeline(Pipeline): def __init__(self, model: Union[SbertForSentimentClassification, str], preprocessor: SentimentClassificationPreprocessor = None, - first_sequence="first_sequence", - second_sequence="second_sequence", + first_sequence='first_sequence', + second_sequence='second_sequence', **kwargs): """use `model` and `preprocessor` to create a nlp text classification pipeline for prediction @@ -52,7 +53,8 @@ class SentimentClassificationPipeline(Pipeline): with torch.no_grad(): return super().forward(inputs, **forward_params) - def postprocess(self, inputs: Dict[str, Any], **postprocess_params) -> Dict[str, str]: + def postprocess(self, inputs: Dict[str, Any], + **postprocess_params) -> Dict[str, str]: """process the prediction results Args: diff --git a/modelscope/pipelines/nlp/text_generation_pipeline.py b/modelscope/pipelines/nlp/text_generation_pipeline.py index 812b133d..8f55cce0 100644 --- a/modelscope/pipelines/nlp/text_generation_pipeline.py +++ b/modelscope/pipelines/nlp/text_generation_pipeline.py @@ -1,5 +1,7 @@ -from typing import Dict, Optional, Union, Any +from typing import Any, Dict, Optional, Union + import torch + from ...metainfo import Pipelines from ...models import Model from ...models.nlp import PalmForTextGeneration @@ -42,7 +44,8 @@ class TextGenerationPipeline(Pipeline): with torch.no_grad(): return super().forward(inputs, **forward_params) - def postprocess(self, inputs: Dict[str, Tensor], **postprocess_params) -> Dict[str, str]: + def postprocess(self, inputs: Dict[str, Tensor], + **postprocess_params) -> Dict[str, str]: """process the prediction results Args: diff --git a/modelscope/pipelines/nlp/word_segmentation_pipeline.py b/modelscope/pipelines/nlp/word_segmentation_pipeline.py index eee5cdf0..9501efb7 100644 --- a/modelscope/pipelines/nlp/word_segmentation_pipeline.py +++ b/modelscope/pipelines/nlp/word_segmentation_pipeline.py @@ -1,5 +1,7 @@ from typing import Any, Dict, Optional, Union + import torch + from ...metainfo import Pipelines from ...models import Model from ...models.nlp import SbertForTokenClassification @@ -42,7 +44,8 @@ class WordSegmentationPipeline(Pipeline): with torch.no_grad(): return super().forward(inputs, **forward_params) - def postprocess(self, inputs: Dict[str, Any], **postprocess_params) -> Dict[str, str]: + def postprocess(self, inputs: Dict[str, Any], + **postprocess_params) -> Dict[str, str]: """process the prediction results Args: diff --git a/modelscope/pipelines/nlp/zero_shot_classification_pipeline.py b/modelscope/pipelines/nlp/zero_shot_classification_pipeline.py index c2cbf54e..13ac5d52 100644 --- a/modelscope/pipelines/nlp/zero_shot_classification_pipeline.py +++ b/modelscope/pipelines/nlp/zero_shot_classification_pipeline.py @@ -1,16 +1,17 @@ import os import uuid from typing import Any, Dict, Union -import torch + import json import numpy as np +import torch from scipy.special import softmax +from ...metainfo import Pipelines +from ...models import Model from ...models.nlp import SbertForZeroShotClassification from ...preprocessors import ZeroShotClassificationPreprocessor from ...utils.constant import Tasks -from ...models import Model -from ...metainfo import Pipelines from ..base import Input, Pipeline from ..builder import PIPELINES diff --git a/modelscope/preprocessors/nlp.py b/modelscope/preprocessors/nlp.py index 397d25eb..8346402c 100644 --- a/modelscope/preprocessors/nlp.py +++ b/modelscope/preprocessors/nlp.py @@ -5,8 +5,7 @@ from typing import Any, Dict, Union from transformers import AutoTokenizer -from ..metainfo import Preprocessors -from ..metainfo import Models +from ..metainfo import Models, Preprocessors from ..utils.constant import Fields, InputFields from ..utils.type_assert import type_assert from .base import Preprocessor diff --git a/modelscope/preprocessors/space/dialog_intent_prediction_preprocessor.py b/modelscope/preprocessors/space/dialog_intent_prediction_preprocessor.py index 5c164480..733abf24 100644 --- a/modelscope/preprocessors/space/dialog_intent_prediction_preprocessor.py +++ b/modelscope/preprocessors/space/dialog_intent_prediction_preprocessor.py @@ -3,13 +3,12 @@ import os from typing import Any, Dict -from .fields.intent_field import \ - IntentBPETextField from ...utils.config import Config from ...utils.constant import Fields from ...utils.type_assert import type_assert from ..base import Preprocessor from ..builder import PREPROCESSORS +from .fields.intent_field import IntentBPETextField __all__ = ['DialogIntentPredictionPreprocessor'] diff --git a/modelscope/preprocessors/space/dialog_modeling_preprocessor.py b/modelscope/preprocessors/space/dialog_modeling_preprocessor.py index 96e5152e..b0758b40 100644 --- a/modelscope/preprocessors/space/dialog_modeling_preprocessor.py +++ b/modelscope/preprocessors/space/dialog_modeling_preprocessor.py @@ -3,13 +3,12 @@ import os from typing import Any, Dict -from .fields.gen_field import \ - MultiWOZBPETextField -from ..base import Preprocessor -from ..builder import PREPROCESSORS from ...utils.config import Config from ...utils.constant import Fields from ...utils.type_assert import type_assert +from ..base import Preprocessor +from ..builder import PREPROCESSORS +from .fields.gen_field import MultiWOZBPETextField __all__ = ['DialogModelingPreprocessor'] diff --git a/modelscope/preprocessors/space/fields/gen_field.py b/modelscope/preprocessors/space/fields/gen_field.py index 9b3434f1..49a30e8f 100644 --- a/modelscope/preprocessors/space/fields/gen_field.py +++ b/modelscope/preprocessors/space/fields/gen_field.py @@ -8,10 +8,10 @@ from itertools import chain import numpy as np -from ..tokenizer import Tokenizer from ....utils.nlp.space import ontology, utils from ....utils.nlp.space.db_ops import MultiWozDB from ....utils.nlp.space.utils import list2np +from ..tokenizer import Tokenizer class BPETextField(object): diff --git a/modelscope/preprocessors/space/fields/intent_field.py b/modelscope/preprocessors/space/fields/intent_field.py index fde351f0..35e1693c 100644 --- a/modelscope/preprocessors/space/fields/intent_field.py +++ b/modelscope/preprocessors/space/fields/intent_field.py @@ -14,10 +14,10 @@ import json import numpy as np from tqdm import tqdm -from ..tokenizer import Tokenizer from ....utils.nlp.space import ontology, utils from ....utils.nlp.space.scores import hierarchical_set_score from ....utils.nlp.space.utils import list2np +from ..tokenizer import Tokenizer class BPETextField(object): diff --git a/modelscope/trainers/nlp/space/trainers/intent_trainer.py b/modelscope/trainers/nlp/space/trainers/intent_trainer.py index 1bd1f8cb..2c5081d7 100644 --- a/modelscope/trainers/nlp/space/trainers/intent_trainer.py +++ b/modelscope/trainers/nlp/space/trainers/intent_trainer.py @@ -14,8 +14,7 @@ import torch from tqdm import tqdm from transformers.optimization import AdamW, get_linear_schedule_with_warmup -from ..metrics.metrics_tracker import \ - MetricsTracker +from ..metrics.metrics_tracker import MetricsTracker def get_logger(log_path, name='default'): diff --git a/tests/pipelines/test_word_segmentation.py b/tests/pipelines/test_word_segmentation.py index e720ff39..d9a2b412 100644 --- a/tests/pipelines/test_word_segmentation.py +++ b/tests/pipelines/test_word_segmentation.py @@ -19,8 +19,7 @@ class WordSegmentationTest(unittest.TestCase): def test_run_by_direct_model_download(self): cache_path = snapshot_download(self.model_id) tokenizer = TokenClassifcationPreprocessor(cache_path) - model = SbertForTokenClassification( - cache_path, tokenizer=tokenizer) + model = SbertForTokenClassification(cache_path, tokenizer=tokenizer) pipeline1 = WordSegmentationPipeline(model, preprocessor=tokenizer) pipeline2 = pipeline( Tasks.word_segmentation, model=model, preprocessor=tokenizer)