prefecth变更为deprecated warning;

fastNLP/core/trainer.py

@@ -311,6 +311,7 @@ try:
     from tqdm.auto import tqdm
 except:
     from .utils import _pseudo_tqdm as tqdm
+import warnings
 
 from .batch import DataSetIter, BatchIter
 from .callback import CallbackManager, CallbackException
@@ -320,7 +321,6 @@ from .metrics import _prepare_metrics
 from .optimizer import Optimizer
 from .sampler import Sampler
 from .sampler import RandomSampler
-from .sampler import SequentialSampler
 from .tester import Tester
 from .utils import _CheckError
 from .utils import _build_args
@@ -395,11 +395,16 @@ class Trainer(object):
     """
     
     def __init__(self, train_data, model, optimizer=None, loss=None,
-                 batch_size=32, sampler=None, drop_last=False,update_every=1,
+                 batch_size=32, sampler=None, drop_last=False, update_every=1,
                  num_workers=0, n_epochs=10, print_every=5,
                  dev_data=None, metrics=None, metric_key=None,
-                 validate_every=-1, save_path=None, use_tqdm=True, device=None,
+                 validate_every=-1, save_path=None, use_tqdm=True, device=None, prefetch=False,
                  callbacks=None, check_code_level=0):
+        if prefetch and num_workers==0:
+            num_workers = 1
+        if prefetch:
+            warnings.warn("prefetch is deprecated, will be removed in version 0.5.0, please use num_workers instead.")
+
         super(Trainer, self).__init__()
         if not isinstance(model, nn.Module):
             raise TypeError(f"The type of model must be torch.nn.Module, got {type(model)}.")

reproduction/utils.py

@@ -13,7 +13,8 @@ def check_dataloader_paths(paths:Union[str, Dict[str, str]])->Dict[str, str]:
     }
     如果paths为不合法的，将直接进行raise相应的错误
 
-    :param paths: 路径
+    :param paths: 路径. 可以为一个文件路径(则认为该文件就是train的文件); 可以为一个文件目录，将在该目录下寻找train.txt,
+        test.txt, dev.txt; 可以为一个dict, 则key是用户自定义的某个文件的名称，value是这个文件的路径。
     :return:
     """
     if isinstance(paths, str):