The test test_mm_plus_mm3_gpu_wrapper in inductor/test_gpu_cpp_wrapper.py fails with [XPASS(strict)] on CUDA because of the xfail.

Test Class: inductor/test_gpu_cpp_wrapper.py::TestGpuWrapper::test_mm_plus_mm3_gpu_wrapper
Platform: CUDA
Error: XPASS(strict) - test was expected to fail but passes

Steps to Reproduce

1. Build PyTorch with CUDA support.
2. Run:
   python test/run_test.py -i inductor/test_gpu_cpp_wrapper -k test_mm_plus_mm3
3. Observe TestGpuWrapper.test_mm_plus_mm3_gpu_wrapper failing with [XPASS(strict)] because it passes but is marked as expected to fail.

Root Cause
PR #172780 added an xfail on test_mm_plus_mm3 in test_select_algorithm.py with the reason "C++ wrapper dynamic shapes fails on CUDA, fixed on ROCm."
On CUDA, the test TestGpuWrapper.test_mm_plus_mm3_gpu_wrapper actually passes, so it fails with [XPASS(strict)] error. Only the dynamic shapes variant DynamicShapesGpuWrapperGpuTests.test_mm_plus_mm3_dynamic_shapes_gpu_wrapper fails on CUDA.
So the xfail is too broad: it marks both tests as expected to fail when only the dynamic shapes run fails.

Proposed fix:
Remove the xfail from test_mm_plus_mm3 and skip the dynamic shapes variant on CUDA in test_failures_gpu_wrapper (similar to test_mm_plus_mm2_dynamic_shapes). So that The TestGpuWrapper.test_mm_plus_mm3_gpu_wrapper test runs and passes on CUDA.
The dynamic shapes test is skipped on CUDA (where it fails) and runs on ROCm (where it passes).

Hence, for test_mm_plus_mm3, if we remove the xfail on the test and use a skip in test_failures_gpu_wrapper the dynamic variant which is known to fail on CUDA is skipped and the XPASS issue will be resolved.

I have a fix for this and if this is a good approach I can go ahead with this.

Code References
Base test: test/inductor/test_select_algorithm.py:299 (test_mm_plus_mm3)
GPU wrapper config: test/inductor/test_gpu_cpp_wrapper.py:107-125 (test_failures_gpu_wrapper)

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