PaddleDataLoader 1、初始化时如果 batch_sampler 为 None 时重置 shuffle 等参数 2、测试例中删除了不必要的 test_v2

fastNLP/core/dataloaders/paddle_dataloader/fdl.py

@@ -8,11 +8,12 @@ from typing import Callable, List, Optional, Union, Dict, Sequence
 from fastNLP.envs.imports import _NEED_IMPORT_PADDLE
 
 if _NEED_IMPORT_PADDLE:
-    from paddle.io import DataLoader, Dataset
+    from paddle.io import DataLoader, Dataset, Sampler
     from paddle.fluid.dataloader.collate import default_collate_fn
 else:
     from fastNLP.core.utils.dummy_class import DummyClass as Dataset
     from fastNLP.core.utils.dummy_class import DummyClass as DataLoader
+    from fastNLP.core.utils.dummy_class import DummyClass as Sampler
 
 from fastNLP.core.collators.collator import Collator
 from fastNLP.core.dataloaders.utils import indice_collate_wrapper
@@ -58,6 +59,9 @@ class PaddleDataLoader(DataLoader):
         if batch_sampler is None:
             batch_sampler = RandomBatchSampler(dataset, batch_size=batch_size, shuffle=shuffle,
                                                drop_last=drop_last)
+            batch_size = 1
+            shuffle = False
+            drop_last = False
 
         super(PaddleDataLoader, self).__init__(dataset=dataset, feed_list=feed_list, places=places,
                                                return_list=return_list, batch_sampler=batch_sampler,

tests/core/dataloaders/paddle_dataloader/test_fdl.py

@@ -58,11 +58,3 @@ class TestPaddle:
         for batch in fdl1:
             assert batch['image'].shape == [4, 10, 5]
             print(batch)
-
-    def test_v2(self):
-        from fastNLP.core.collators import Collator
-        logger.setLevel("DEBUG")
-        data = [paddle.Tensor(np.random.random((10, 5)).astype('float32')), paddle.Tensor(np.random.random((10, 5)).astype('float32'))]
-        col = Collator(backend="jittor")
-        res = col(data)
-        print(res)