Repository: pytorch
Issue: Conv1d: NNPACK SpatialConvolution_updateOutput failed when batchsize or padding is too large
Labels: module: nn,module: convolution,triaged,module: nnpack

### 🐛 Describe the bug

When using conv1d in torch=1.10.2 and python=3.8.13
I found that if both the input batchsize and padding parameter are given a large value ( or maybe the production of them), I will get a "NNPACK SpatialConvolution_updateOutput failed" error. 
I wonder if it is a bug or some inner remand for the op?

Here is a short example
'''
import torch 
op = nn.Conv1d(3, 3, 2, 1, 1, 1, 1)
input = torch.randn((1000, 3, 10))
op(input)
'''

Here is the error info
'''
Traceback (most recent call last):
  File "test.py", line 184, in <module>
    op(input)
  File "/home/hek/anaconda3/envs/dnngen/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/hek/anaconda3/envs/dnngen/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 301, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "/home/hek/anaconda3/envs/dnngen/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 297, in _conv_forward
    return F.conv1d(input, weight, bias, self.stride,
RuntimeError: NNPACK SpatialConvolution_updateOutput failed
'''

### Versions

Collecting environment information...
PyTorch version: 1.10.2
Is debug build: False
CUDA used to build PyTorch: 11.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.27

Python version: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:18)  [GCC 10.3.0] (64-bit runtime)
Python platform: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.10
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3070 Ti
Nvidia driver version: 516.40
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.1
[pip3] torch==1.10.2
[pip3] torchaudio==0.10.2
[pip3] torchvision==0.10.0a0
[conda] blas                      2.115                       mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] blas-devel                3.9.0            15_linux64_mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] cpuonly                   2.0                           0    pytorch
[conda] cudatoolkit               11.7.0              hd8887f6_10    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] libblas                   3.9.0            15_linux64_mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] libcblas                  3.9.0            15_linux64_mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] liblapack                 3.9.0            15_linux64_mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] liblapacke                3.9.0            15_linux64_mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] magma                     2.5.4                h6103c52_2    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] mkl                       2022.1.0           h84fe81f_915    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] mkl-devel                 2022.1.0           ha770c72_916    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] mkl-include               2022.1.0           h84fe81f_915    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] numpy                     1.23.1           py38h3a7f9d9_0    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] pytorch                   1.10.2          cuda112py38h6425f36_1    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] pytorch-gpu               1.10.2          cuda112py38h0bbbad9_1    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
[conda] pytorch-mutex             1.0                         cpu    pytorch
[conda] torchaudio                0.10.2                 py38_cpu  [cpuonly]  pytorch
[conda] torchvision               0.10.1          py38cuda112h04b465a_0_cuda    http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge

cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are