diff --git a/benchmarks/test_sharded_parity.py b/benchmarks/test_sharded_parity.py
index a5fd6c2eff..231556079e 100644
--- a/benchmarks/test_sharded_parity.py
+++ b/benchmarks/test_sharded_parity.py
@@ -13,7 +13,6 @@
 # limitations under the License.
 
 import os
-import platform
 import time
 from typing import Type
 
@@ -22,14 +21,12 @@ import torch
 
 from pytorch_lightning import seed_everything, Trainer
 from pytorch_lightning.plugins import DDPSpawnShardedPlugin
-from pytorch_lightning.utilities import _FAIRSCALE_AVAILABLE, _NATIVE_AMP_AVAILABLE
 from tests.accelerators import DDPLauncher
 from tests.helpers.boring_model import BoringModel, RandomDataset
+from tests.helpers.runif import RunIf
 
 
-@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires GPU machine")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=1, skip_windows=True, fairscale=True)
 def test_ddp_sharded_plugin_correctness_one_gpu():
     plugin_parity_test(
         gpus=1,
@@ -37,10 +34,7 @@ def test_ddp_sharded_plugin_correctness_one_gpu():
     )
 
 
-@pytest.mark.skipif(not _NATIVE_AMP_AVAILABLE, reason="Requires native AMP")
-@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires GPU machine")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=1, skip_windows=True, fairscale=True, amp_native=True)
 def test_ddp_sharded_plugin_correctness_amp_one_gpu():
     plugin_parity_test(
         gpus=1,
@@ -50,9 +44,7 @@ def test_ddp_sharded_plugin_correctness_amp_one_gpu():
 
 
 @pytest.mark.skip(reason="Not a critical test, skip till drone CI performance improves.")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=2, skip_windows=True, fairscale=True)
 def test_ddp_sharded_plugin_correctness_multi_gpu():
     plugin_parity_test(
         gpus=2,
@@ -61,10 +53,7 @@ def test_ddp_sharded_plugin_correctness_multi_gpu():
     )
 
 
-@pytest.mark.skipif(not _NATIVE_AMP_AVAILABLE, reason="Requires native AMP")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=2, skip_windows=True, fairscale=True, amp_native=True)
 def test_ddp_sharded_plugin_correctness_amp_multi_gpu():
     plugin_parity_test(
         gpus=2,
@@ -74,10 +63,7 @@ def test_ddp_sharded_plugin_correctness_amp_multi_gpu():
     )
 
 
-@pytest.mark.skipif(not _NATIVE_AMP_AVAILABLE, reason="Requires native AMP")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=2, skip_windows=True, fairscale=True, amp_native=True)
 def test_ddp_string_sharded_plugin_correctness_amp_multi_gpu():
     plugin_parity_test(
         gpus=2,
@@ -87,8 +73,7 @@ def test_ddp_string_sharded_plugin_correctness_amp_multi_gpu():
     )
 
 
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
+@RunIf(min_gpus=2, fairscale=True)
 @pytest.mark.skipif(
     not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
 )
@@ -101,8 +86,7 @@ def test_ddp_sharded_plugin_correctness_multi_gpu_ddp(tmpdir, args=None):
     )
 
 
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
+@RunIf(min_gpus=2, fairscale=True)
 @pytest.mark.skipif(
     not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
 )
@@ -116,9 +100,7 @@ def test_ddp_sharded_plugin_correctness_amp_multi_gpu_ddp(tmpdir, args=None):
 
 
 @pytest.mark.skip(reason="Current issue with multiple optimizers and FairScale.")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=2, skip_windows=True, fairscale=True)
 def test_ddp_sharded_plugin_correctness_multi_gpu_multi_optim():
     """
         Ensures same results using multiple optimizers across multiple GPUs
@@ -131,9 +113,7 @@ def test_ddp_sharded_plugin_correctness_multi_gpu_multi_optim():
 
 
 @pytest.mark.skip(reason="Current issue with multiple optimizers and FairScale.")
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
-@pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
+@RunIf(min_gpus=2, skip_windows=True, fairscale=True)
 def test_ddp_sharded_plugin_correctness_multi_gpu_multi_optim_manual(tmpdir):
     """
         Ensures using multiple optimizers across multiple GPUs with manual optimization