[DCU] Skip some tests in test_cuda_graphs.py under L0

Signed-off-by: zhaochao <zhaochao1@sugon.com>

tests/pytorch/test_cuda_graphs.py

@@ -28,9 +28,9 @@ if IS_HIP_EXTENSION:
     from functools import cache
 
 # Check if FP8 is supported.
-fp8_available, _ = FP8GlobalStateManager.is_fp8_available()
-fp8_block_scaling_available, _ = FP8GlobalStateManager.is_fp8_block_scaling_available()
-mxfp8_available, _ = FP8GlobalStateManager.is_mxfp8_available()
+fp8_available, reason_for_no_fp8 = FP8GlobalStateManager.is_fp8_available()
+fp8_block_scaling_available, reason_for_no_fp8_block_scaling = FP8GlobalStateManager.is_fp8_block_scaling_available()
+mxfp8_available, reason_for_no_mxfp8 = FP8GlobalStateManager.is_mxfp8_available()
 
 # Reset RNG states.
 reset_rng_states()
@@ -310,6 +310,12 @@ def test_make_graphed_callables(
         pytest.skip("FP8 needed for FP8 parameters.")
     if fp8 and fp8_recipe.float8_block_scaling() and module == "linear_op":
         pytest.skip("Module not yet supported for float8_block_scaling with CUDA graphs")
+    if fp8 and not fp8_available:
+        pytest.skip(reason_for_no_fp8)
+    if fp8 and fp8_recipe.float8_block_scaling() and not fp8_block_scaling_available:
+        pytest.skip(reason_for_no_fp8_block_scaling)
+    if fp8 and fp8_recipe.mxfp8() and not mxfp8_available:
+        pytest.skip(reason_for_no_mxfp8)
 
     # Run model with different CUDA graph settings.
     model_config = model_configs[model_config]