| @@ -147,7 +147,6 @@ class TestFdl: | |||||
| assert 'Parameter:prefetch_factor' in out[0] | assert 'Parameter:prefetch_factor' in out[0] | ||||
| @recover_logger | @recover_logger | ||||
| @pytest.mark.temp | |||||
| def test_version_111(self): | def test_version_111(self): | ||||
| if parse_version(torch.__version__) <= parse_version('1.7'): | if parse_version(torch.__version__) <= parse_version('1.7'): | ||||
| pytest.skip("Torch version smaller than 1.7") | pytest.skip("Torch version smaller than 1.7") | ||||
| @@ -8,7 +8,7 @@ from fastNLP.envs.imports import _NEED_IMPORT_TORCH | |||||
| if _NEED_IMPORT_TORCH: | if _NEED_IMPORT_TORCH: | ||||
| import torch | import torch | ||||
| from torch.utils.data import default_collate, SequentialSampler, RandomSampler | |||||
| from torch.utils.data import SequentialSampler, RandomSampler | |||||
| d1 = DataSet({"x": [[1, 2], [2, 3, 4], [4, 5, 6, 7]] * 10, "y": [1, 0, 1] * 10}) | d1 = DataSet({"x": [[1, 2], [2, 3, 4], [4, 5, 6, 7]] * 10, "y": [1, 0, 1] * 10}) | ||||
| @@ -28,6 +28,7 @@ def test_pad_val(tensor, val=0): | |||||
| return True | return True | ||||
| @pytest.mark.torch | |||||
| class TestMixDataLoader: | class TestMixDataLoader: | ||||
| def test_sequential_init(self): | def test_sequential_init(self): | ||||