test

example/ner/few-shot/predict.py

@@ -11,7 +11,7 @@ from torch.utils.data import DataLoader
 from deepke.name_entity_re.few_shot.models.model import PromptBartModel, PromptGeneratorModel
 from deepke.name_entity_re.few_shot.module.datasets import ConllNERProcessor, ConllNERDataset
 from deepke.name_entity_re.few_shot.module.train import Trainer
-from deepke.name_entity_re.few_shot.utils.utils import set_seed
+from deepke.name_entity_re.few_shot.utils.util import set_seed
 from deepke.name_entity_re.few_shot.module.mapping_type import mit_movie_mapping, mit_restaurant_mapping, atis_mapping
 
 import warnings

example/ner/few-shot/run.py

@@ -13,7 +13,7 @@ from deepke.name_entity_re.few_shot.models.model import PromptBartModel, PromptG
 from deepke.name_entity_re.few_shot.module.datasets import ConllNERProcessor, ConllNERDataset
 from deepke.name_entity_re.few_shot.module.train import Trainer
 from deepke.name_entity_re.few_shot.module.metrics import Seq2SeqSpanMetric
-from deepke.name_entity_re.few_shot.utils.utils import get_loss, set_seed
+from deepke.name_entity_re.few_shot.utils.util import get_loss, set_seed
 from deepke.name_entity_re.few_shot.module.mapping_type import mit_movie_mapping, mit_restaurant_mapping, atis_mapping
 
 import warnings

setup.py

@@ -1,7 +1,7 @@
 from setuptools import setup, find_packages
 setup(
     name='deepke',  # 打包后的包文件名
-    version='0.2.40',    #版本号
+    version='0.2.60',    #版本号
     keywords=["pip", "RE","NER","AE"],    # 关键字
     description='DeepKE 是基于 Pytorch 的深度学习中文关系抽取处理套件。',  # 说明
     long_description="client",  #详细说明

src/deepke/name_entity_re/few_shot/__init__.py

@@ -1 +1,3 @@
-from .few_shot import *
+from .models import *
+from .module import *
+from .utils import *

src/deepke/name_entity_re/few_shot/models/model.py

@@ -4,7 +4,7 @@ from torch.nn import functional as F
 from transformers.configuration_bart import BartConfig
 from .modeling_bart import BartModel, _prepare_bart_decoder_inputs
 
-from ..utils.utils import avg_token_embeddings, seq_to_mask, _get_model_device
+from ..utils import avg_token_embeddings, seq_to_mask,get_model_device
 from functools import partial
 from typing import Union
 

src/deepke/name_entity_re/few_shot/module/train.py

@@ -1,7 +1,7 @@
 import torch
 from torch import optim
 from tqdm import tqdm
-from ..utils.utils import convert_preds_to_outputs, write_predictions
+from ..utils import convert_preds_to_outputs, write_predictions
 import random
 
 class Trainer(object):

src/deepke/name_entity_re/few_shot/utils/__init__.py

@@ -1 +1 @@
-from utils import *
+from .util import *

src/deepke/name_entity_re/few_shot/utils/util.py

@@ -63,7 +63,7 @@ def get_loss(tgt_tokens, tgt_seq_len, pred):
     loss = F.cross_entropy(target=tgt_tokens, input=pred.transpose(1, 2))
     return loss
 
-def _get_model_device(model):
+def get_model_device(model):
     assert isinstance(model, nn.Module)
 
     parameters = list(model.parameters())

src/deepke/name_entity_re/standard/__init__.py

@@ -0,0 +1,2 @@
+from .models import *
+from .tools import *

src/deepke/name_entity_re/standard/models/__init__.py

@@ -1,2 +1,2 @@
-from .BasicNer import TrainNer
-from .InferBert import InferNer
+from .BasicNer import *
+from .InferBert import *

src/deepke/name_entity_re/standard/tools/__init__.py

@@ -1,3 +1,3 @@
 from .dataset import *
 from .preprocess import *
-from .trainer import train
+from .trainer import *

src/deepke/name_entity_re/standard/tools/trainer.py

@@ -32,7 +32,7 @@ from hydra import utils
 from .dataset import *
 from .preprocess import *
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../")))
-from models.BasicNer import TrainNer
+from ..models import TrainNer
 
 logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s -   %(message)s',
                     datefmt = '%m/%d/%Y %H:%M:%S',