Repository: pytorch
Issue: assert_size_strided hit on Conv1d with strided input
Labels: triaged,oncall: pt2,module: inductor

### 🐛 Describe the bug

backend: inductor, any mode

reproducer:

```python
import torch
from torch.nn import Conv1d

net_d = Conv1d(in_channels=1, out_channels=16, kernel_size=15, stride=1, padding=7, device='cuda')
net_d = torch.compile(net_d)

wave = torch.randn((8, 1, 1024), device='cuda').as_strided(
    size=(8, 1, 1024), stride=(1024, 1, 1))

a = net_d(wave)
print("ok")
```

### Error logs

```
  File "/home/yorick/code/w/.venv/lib/python3.11/site-packages/torch/_inductor/utils.py", line 1977, in run
    return model(new_inputs)
           ^^^^^^^^^^^^^^^^^
  File "/tmp/torchinductor_yorick/3s/c3spesdi5qxuareundjfschy7f3ctwcp7uwflyqcfmv24amwvwxj.py", line 83, in call
    assert_size_stride(buf0, (8, 16, 1024), (16384, 1024, 1))
AssertionError: expected size 16==16, stride 1==1024 at dim=1; expected size 1024==1024, stride 16==1 at dim=2
```

### Versions

(it also happens on `2.6.0.dev20241210+cu126` nightly)

```
Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: NixOS 24.11 (Vicuna) (x86_64)
GCC version: (GCC) 13.3.0
Clang version: Could not collect
CMake version: version 3.30.5
Libc version: glibc-2.40

Python version: 3.11.10 (main, Sep  7 2024, 01:03:31) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.6.63-x86_64-with-glibc2.40
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA RTX A5000
Nvidia driver version: 565.77
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        43 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               32
On-line CPU(s) list:                  0-31
Vendor ID:                            AuthenticAMD
Model name:                           AMD Ryzen 9 3950X 16-Core Processor
CPU family:                           23
Model:                                113
Thread(s) per core:                   2
Core(s) per socket:                   16
Socket(s):                            1
Stepping:                             0
Frequency boost:                      enabled
CPU(s) scaling MHz:                   64%
CPU max MHz:                          3500.0000
CPU min MHz:                          2200.0000
BogoMIPS:                             6999.87
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sev sev_es
Virtualization:                       AMD-V
L1d cache:                            512 KiB (16 instances)
L1i cache:                            512 KiB (16 instances)
L2 cache:                             8 MiB (16 instances)
L3 cache:                             64 MiB (4 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-31
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 Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow:   Mitigation; Safe RET
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; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] clip-anytorch==2.6.0
[pip3] dctorch==0.1.2
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] onnx==1.17.0
[pip3] onnx2torch==1.5.15
[pip3] onnxruntime==1.20.1
[pip3] open_clip_torch==2.29.0
[pip3] rotary-embedding-torch==0.8.6
[pip3] torch==2.5.1
[pip3] torchaudio==2.5.1
[pip3] torchcrepe==0.0.23
[pip3] torchdiffeq==0.2.5
[pip3] torchsde==0.2.6
[pip3] torchvision==0.20.1
[pip3] triton==3.1.0
[conda] Could not collect
```

cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @aakhundov