fiux

tests/test_booster/test_mixed_precision/test_fp16_torch.py

@@ -1,4 +1,3 @@
-import pytest
 import torch
 from torch.optim import Adam
 
@@ -36,7 +35,6 @@ def run_torch_amp(rank, world_size, port):
         del model, optimizer, criterion, data, output, mixed_precision
 
 
-@pytest.mark.skip(reason="Skip because assertion may fail for CI devices")
 @rerun_if_address_is_in_use()
 def test_torch_ddp_plugin():
     spawn(run_torch_amp, 1)

tests/test_infer/test_kernels/cuda/test_flash_decoding_attention.py

@@ -11,7 +11,6 @@ from tests.test_infer.test_kernels.triton.test_context_attn_unpad import generat
 
 inference_ops = InferenceOpsLoader().load()
 
-from colossalai.testing import clear_cache_before_run
 from tests.test_infer.test_kernels.triton.kernel_utils import (
     convert_kv_unpad_to_padded,
     create_attention_mask,
@@ -57,7 +56,6 @@ def numpy_allclose(x, y, rtol, atol):
     np.testing.assert_allclose(x_numpy, y_numpy, rtol=rtol, atol=atol)
 
 
-@clear_cache_before_run()
 @pytest.mark.parametrize("BATCH_SIZE", [1, 4, 7, 32])
 @pytest.mark.parametrize("BLOCK_SIZE", [8, 16, 32])
 @pytest.mark.parametrize("MAX_NUM_BLOCKS_PER_SEQ", [1, 8, 32, 256, 512])