Repository: pytorch
Issue: [ARM] (Neoverse-N1) Tensor-likes are not close! for CPUReproTests.test_two_local_buffers_in_outer_loop_fusion
Labels: triaged,module: arm

### 🐛 Describe the bug

Identified on Arm Neoverse-N1

```
AssertionError: Tensor-likes are not close!

Mismatched elements: 1019 / 12570624 (0.0%)
Greatest absolute difference: 0.0009765625 at index (1, 5, 672, 24) (up to 1e-05 allowed)
Greatest relative difference: 1.4066824860492488e-06 at index (1, 5, 672, 24) (up to 1.3e-06 allowed)

To execute this test, run the following from the base repo dir:
    python test/inductor/test_cpu_repro.py CPUReproTests.test_two_local_buffers_in_outer_loop_fusion

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
```

Discovered #142230 whilst trying to debug this.

These types of unit test failures are difficult to debug as there is expected to be a difference between inductor and eager paths, and the error will increase the larger the tensor size and number of operations? There is also a statistical element as it's possible to find a manual seed that causes this test to pass.

`torch.manual_seed(1)` prior to the torch.randn call will cause the test to pass.

### Versions

Collecting environment information...
PyTorch version: 2.6.0a0+gitcc64ad6
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (aarch64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.31.1
Libc version: glibc-2.35

Python version: 3.10.16 | packaged by conda-forge | (main, Dec  5 2024, 14:08:42) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.5.0-1018-aws-aarch64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       aarch64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
CPU(s):                             48
On-line CPU(s) list:                0-47
Vendor ID:                          ARM
Model name:                         Neoverse-N1
Model:                              1
Thread(s) per core:                 1
Core(s) per cluster:                48
Socket(s):                          -
Cluster(s):                         1
Stepping:                           r3p1
BogoMIPS:                           243.75
Flags:                              fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop asimddp ssbs
L1d cache:                          3 MiB (48 instances)
L1i cache:                          3 MiB (48 instances)
L2 cache:                           48 MiB (48 instances)
L3 cache:                           32 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-47
Vulnerability Gather data sampling: 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 Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:           Mitigation; __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; CSV2, BHB
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] mypy==1.13.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.22.4
[pip3] onnx==1.17.0
[pip3] onnxscript==0.1.0.dev20240817
[pip3] optree==0.13.0
[pip3] torch==2.6.0a0+gitcc64ad6
[conda] No relevant packages

cc @malfet @snadampal @milpuz01