[Bug Skip]: UT failures 2026-8-16

@dominikjastrzebskix is already working on this.

Since Sep 15, 2026.

### 🐛 Describe the bug with skip template

Cases:
op_ut,third_party.torch-xpu-ops.test.xpu.functorch.test_control_flow_xpu.TestControlFlowTraced,test_while_loop_autograd_simple
op_ut,third_party.torch-xpu-ops.test.xpu.higher_order_ops.test_invoke_subgraph_xpu.TestInvokeSubgraphCompile,test_different_strides_in_backward
~~op_ut,third_party.torch-xpu-ops.test.xpu.profiler.test_profiler_xpu.TestProfiler,test_profiler_cuda_sync_events~~
~~op_ut,third_party.torch-xpu-ops.test.xpu.profiler.test_profiler_xpu.TestProfiler,test_disable_external_correlation~~
~~op_ut,third_party.torch-xpu-ops.test.xpu.test_cuda_multigpu_xpu.TestCudaMultiGPU,test_mem_get_info~~

## Detailed Failure Analysis

### 1. functorch/test_control_flow_xpu.py

#### test_while_loop_autograd_simple

**Test Class:** `TestControlFlowTraced`

**Error Type:** `AssertionError`

**Error Message:**
```
AssertionError: 'clas[2133 chars] sub_1: "i64[]" = torch.ops.aten.sub.Tensor(r[1655 chars]1)\n' != 'clas[2133 chars] sub: "i64[]" = torch.ops.aten.sub.Tensor(rsu[1645 chars]6)\n'
```

**Details:** The test failed due to a graph output mismatch. The expected output has `sub_1` variable name but the actual output has `sub` variable name. This is likely a variable naming inconsistency in the compiled graph output.

**Reproduction Command:**
```bash
PYTORCH_TEST_WITH_SLOW=1 python test/xpu/functorch/test_control_flow_xpu.py TestControlFlowTraced.test_while_loop_autograd_simple
```

---

### 2. higher_order_ops/test_invoke_subgraph_xpu.py

#### test_different_strides_in_backward

**Test Class:** `TestInvokeSubgraphCompile`

**Error Type:** `AssertionError`

**Error Message:**
```
AssertionError: 'clas[2221 chars] add_15: "f32[]" = torch.ops.aten.add.Tensor([769 chars]s_0)' != 'clas[2221 chars] add: "f32[]" = torch.ops.aten.add.Tensor(sum[763 chars]s_0)'
```

**Details:** Similar to the first failure, this is a graph output naming mismatch. The expected output has `add_15` but actual has `add`. This indicates inconsistent variable naming in the compiled graph for backward pass with different strides.

**Reproduction Command:**
```bash
PYTORCH_TEST_WITH_SLOW=1 python test/xpu/higher_order_ops/test_invoke_subgraph_xpu.py TestInvokeSubgraphCompile.test_different_strides_in_backward
```

---

### 3. profiler/test_profiler_xpu.py

#### test_profiler_cuda_sync_events

**Test Class:** `TestProfiler`

**Error Type:** `AssertionError`

**Error Message:**
```
AssertionError: False is not true : Expected to find sync event found = {'PyTorch Profiler (0)', 'thread_sort_index', 'process_labels', 'process_sort_index', 'Record Window End', 'aten::add', 'process_name', 'thread_name', 'Iteration Start: PyTorch Profiler'}
```

**Details:** The test expects to find specific CUDA sync events in the profiler output, but the expected events are not being detected. The profiler is only finding basic events like 'PyTorch Profiler', 'aten::add', etc., but missing the CUDA sync-specific events.

**Reproduction Command:**
```bash
PYTORCH_TEST_WITH_SLOW=1 python test/xpu/profiler/test_profiler_xpu.py TestProfiler.test_profiler_cuda_sync_events
```

---

### 4. profiler/test_profiler_xpu.py

#### test_disable_external_correlation

**Test Class:** `TestProfiler`

**Error Type:** `AssertionError`

**Error Message:**
```
AssertionError: False is not true
```

**Assertion:**
```python
self.assertTrue({"gpu_memcpy", "kernel"}.issubset(seen_event_types))
```

**Details:** When external correlation is disabled, the profiler should still detect `gpu_memcpy` and `kernel` event types. The test failure indicates these event types are not being captured properly.

**Reproduction Command:**
```bash
PYTORCH_TEST_WITH_SLOW=1 python test/xpu/profiler/test_profiler_xpu.py TestProfiler.test_disable_external_correlation
```

---

### 5. test_cuda_multigpu_xpu.py

#### test_mem_get_info

**Test Class:** `TestCudaMultiGPU`

**Error Type:** `AssertionError`

**Error Message:**
```
AssertionError: 68702699520 not less than 68702699520
```

**Details:** The test checks that memory is properly freed after allocation and deallocation. The failure indicates that `after_free_bytes` is not less than `before_free_bytes`, suggesting either:
- Memory is not being properly released
- The memory measurement is not accurate
- There might be a timing issue with memory statistics

**Reproduction Command:**
```bash
PYTORCH_TEST_WITH_SLOW=1 python test/xpu/test_cuda_multigpu_xpu.py TestCudaMultiGPU.test_mem_get_info
```
## Pytorch Version
latest good : b5540e0ee69e8c2c170b3a65c913411b7a7cc0a9
current : 8f988c9c6b3586efbc00a981d9d8cac11f26bcdb

### Versions

Detail
Collecting environment information...
PyTorch version: 2.15.0a0+git8f988c9
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.4 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
Clang version: Could not collect
CMake version: version 3.31.6
Libc version: glibc-2.39

Python version: 3.10.21 (main, Aug 14 2026, 15:33:52) [Clang 22.1.3 ] (64-bit runtime)
Python platform: Linux-6.8.0-110-generic-x86_64-with-glibc2.39
Is CUDA available: False
CUDA runtime version: No CUDA
Model: 143
Thread(s) per core: 2
Core(s) per socket: 48
Socket(s): 2
Stepping: 8
CPU(s) scaling MHz: 99%
CPU max MHz: 3800.0000
CPU min MHz: 800.0000
BogoMIPS: 4800.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hfi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities ibpb_exit_to_user
L1d cache: 4.5 MiB (96 instances)
L1i cache: 3 MiB (96 instances)
L2 cache: 192 MiB (96 instances)
L3 cache: 195 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-47,96-143
NUMA node1 CPU(s): 48-95,144-191
Vulnerability Gather data sampling: Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

Versions of relevant libraries:
[pip3] dpcpp-cpp-rt==2026.1.0
[pip3] impi-rt==2021.18.1
[pip3] intel-cmplr-lib-rt==2026.1.0
[pip3] intel-cmplr-lib-ur==2026.1.0
[pip3] intel-cmplr-lic-rt==2026.1.0
[pip3] intel-opencl-rt==2026.1.0
[pip3] intel-openmp==2026.1.0
[pip3] intel-pti==1.0.1
[pip3] intel-sycl-rt==2026.1.0
[pip3] mkl==2026.1.0
[pip3] mypy==1.16.0
[pip3] mypy_extensions==1.1.0
[pip3] numpy==1.24.4
[pip3] nvidia-cuda-cupti==13.3.75
[pip3] oneccl==2022.1.1
[pip3] oneccl-devel==2022.1.1
[pip3] onemkl-license==2026.1.0
[pip3] onemkl-sycl-blas==2026.1.0
[pip3] onemkl-sycl-dft==2026.1.0
[pip3] onemkl-sycl-lapack==2026.1.0
[pip3] onemkl-sycl-rng==2026.1.0
[pip3] onemkl-sycl-sparse==2026.1.0
[pip3] onnx==1.21.0
[pip3] onnx-ir==0.1.16
[pip3] onnxscript==0.6.2
[pip3] optree==0.13.0
[pip3] tbb==2023.1.0
[pip3] tcmlib==1.5.0
[pip3] torch==2.15.0a0+git8f988c9
[pip3] torchao==0.19.0.dev20260816+xpu
[pip3] torchaudio==2.11.0a0+4e3e282
[pip3] torchvision==0.30.0a0+af77a7c
[pip3] triton-xpu==3.8.0+git1e2d42a0
[pip3] umf==1.1.0
[conda] No relevant packages