offline st testcases for cuda-11.1

tests/st/nccl/test_nccl_all.py

@@ -16,7 +16,7 @@ import os
 import pytest
 
 
-@pytest.mark.level0
+@pytest.mark.level2
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_single
 def test_nccl_lenet():

tests/st/networks/test_gpu_resnet.py

@@ -352,7 +352,7 @@ def test_trainTensor(num_classes=10, epoch=8, batch_size=1):
     assert (losses[-1].asnumpy() < 1)
 
 
-@pytest.mark.level0
+@pytest.mark.level2
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_trainTensor_big_batchSize(num_classes=10, epoch=8, batch_size=338):

tests/st/ops/gpu/test_tensordot_op.py

@@ -105,7 +105,7 @@ def test_tensor_dot_fp32():
     np.allclose(ms_result_np, np_result)
 
 
-@pytest.mark.level0
+@pytest.mark.level2
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_tensor_dot_fp16():

tests/st/quantization/mobilenetv2_quant/test_mobilenetv2_quant_gpu.py

@@ -54,7 +54,7 @@ config_ascend_quant = ed({
 
 dataset_path = "/home/workspace/mindspore_dataset/cifar-10-batches-bin/"
 
-@pytest.mark.level0
+@pytest.mark.level2
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_single
 def test_mobilenetv2_quant():