[CI/Build] Automatically retry flaky tests (#17856)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

tests/kernels/moe/test_moe.py

@@ -286,6 +286,7 @@ def test_mixtral_moe(dtype: torch.dtype, padding: bool, use_rocm_aiter: bool,
                                    atol=mixtral_moe_tol[dtype])
 
 
+@pytest.mark.flaky(reruns=2)
 @pytest.mark.parametrize("m", [1, 123, 666])
 @pytest.mark.parametrize("n", [128, 1024])
 @pytest.mark.parametrize("k", [256, 2048])

tests/tensorizer_loader/conftest.py

 # SPDX-License-Identifier: Apache-2.0
-
-import functools
-import gc
-from typing import Callable, TypeVar
-
 import pytest
-import torch
-from typing_extensions import ParamSpec
 
 from vllm.distributed import cleanup_dist_env_and_memory
 from vllm.model_executor.model_loader.tensorizer import TensorizerConfig
@@ -25,32 +18,6 @@ def cleanup():
     cleanup_dist_env_and_memory(shutdown_ray=True)
 
 
-_P = ParamSpec("_P")
-_R = TypeVar("_R")
-
-
-def retry_until_skip(n: int):
-
-    def decorator_retry(func: Callable[_P, _R]) -> Callable[_P, _R]:
-
-        @functools.wraps(func)
-        def wrapper_retry(*args: _P.args, **kwargs: _P.kwargs) -> _R:
-            for i in range(n):
-                try:
-                    return func(*args, **kwargs)
-                except AssertionError:
-                    gc.collect()
-                    torch.cuda.empty_cache()
-                    if i == n - 1:
-                        pytest.skip(f"Skipping test after {n} attempts.")
-
-            raise AssertionError("Code should not be reached")
-
-        return wrapper_retry
-
-    return decorator_retry
-
-
 @pytest.fixture(autouse=True)
 def tensorizer_config():
     config = TensorizerConfig(tensorizer_uri="vllm")

tests/tensorizer_loader/test_tensorizer.py

@@ -28,7 +28,6 @@ from vllm.model_executor.model_loader.tensorizer import (TensorizerConfig,
 from vllm.utils import PlaceholderModule, import_from_path
 
 from ..utils import VLLM_PATH, RemoteOpenAIServer
-from .conftest import retry_until_skip
 
 try:
     from tensorizer import EncryptionParams
@@ -325,7 +324,7 @@ def test_deserialized_encrypted_vllm_model_with_tp_has_same_outputs(
     assert outputs == deserialized_outputs
 
 
-@retry_until_skip(3)
+@pytest.mark.flaky(reruns=3)
 def test_vllm_tensorized_model_has_same_outputs(vllm_runner, tmp_path):
     gc.collect()
     torch.cuda.empty_cache()