Repository: pytorch
Issue: Unable to find an engine to execute when using pip to install but not with conda
Labels: module: binaries,module: cudnn,module: convolution,triaged

When I tried to run resnet34 model test with the nightly version that is installed with pip in cuda 11.6 with A100 gpu. 

~~UPDATE: As mentioned in Notes below, it seems that the problem caused by `torchtriton` package. I can resolve the problem by manually install `torchtriton` via conda: `conda install torchtriton -c pytorch-nightly`~~

## Here is the command to reproduce the error:
```
pip3 install --pre torch torchvision --extra-index-url https://download.pytorch.org/whl/nightly/cu116
pip install pytest
git clone git@github.com:pytorch/vision.git
cd vision/test
pytest test_models.py -k test_classification_model -k resnet34
```

## And I got the following error:
```
Traceback (most recent call last):
  File "/fsx/users/yosuamichael/repos/temp/vision/test/test_models.py", line 688, in test_classification_model
    out = model(x)
  File "/fsx/users/yosuamichael/conda/envs/tv_test/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1488, in _call_impl
    return forward_call(*args, **kwargs)
  File "/fsx/users/yosuamichael/conda/envs/tv_test/lib/python3.8/site-packages/torchvision/models/resnet.py", line 285, in forward
    return self._forward_impl(x)
  File "/fsx/users/yosuamichael/conda/envs/tv_test/lib/python3.8/site-packages/torchvision/models/resnet.py", line 268, in _forward_impl
    x = self.conv1(x)
  File "/fsx/users/yosuamichael/conda/envs/tv_test/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1488, in _call_impl
    return forward_call(*args, **kwargs)
  File "/fsx/users/yosuamichael/conda/envs/tv_test/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 463, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "/fsx/users/yosuamichael/conda/envs/tv_test/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 459, in _conv_forward
    return F.conv2d(input, weight, bias, self.stride,
RuntimeError: GET was unable to find an engine to execute this computation
```

Which quite an unexpected error. When I tried to install using conda, i.e. change the installation line to: 
```
conda install pytorch torchvision pytorch-cuda=11.6 -c pytorch-nightly -c nvidia
```
then it actually works as expected, I get assertion error (which is expected) like: 
```
Mismatched elements: 10 / 50 (20.0%)
Greatest absolute difference: 0.01226806640625 at index (0, 39) (up to 0.001 allowed)
Greatest relative difference: 0.003982544439953874 at index (0, 49) (up to 0.001 allowed)
```

Hence, I think there is something wrong with the pip installation.

## Environment
Here is the result of `collect_env.py` when I use pip installation:
```
Collecting environment information...
PyTorch version: 2.0.0.dev20230124+cu116
Is debug build: False
CUDA used to build PyTorch: 11.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~18.04) 9.4.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.25.0
Libc version: glibc-2.27

Python version: 3.8.16 (default, Jan 17 2023, 23:13:24)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.4.0-1069-aws-x86_64-with-glibc2.17 
Is CUDA available: True
CUDA runtime version: 11.6.112
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-40GB  
Nvidia driver version: 510.47.03
cuDNN version: Probably one of the following:
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.5
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.24.1
[pip3] pytorch-triton==2.0.0+0d7e753227
[pip3] torch==2.0.0.dev20230124+cu116
[pip3] torchvision==0.15.0.dev20230124+cu116
[conda] numpy                     1.24.1                   pypi_0    pypi
[conda] pytorch-triton            2.0.0+0d7e753227          pypi_0    pypi
[conda] torch                     2.0.0.dev20230124+cu116          pypi_0    pypi
[conda] torchvision               0.15.0.dev20230124+cu116          pypi_0    pypi
```

And here is the result of collect_env.py when I install using conda:
```
Collecting environment information...
PyTorch version: 2.0.0.dev20230124
Is debug build: False
CUDA used to build PyTorch: 11.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~18.04) 9.4.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.25.0
Libc version: glibc-2.27

Python version: 3.8.16 (default, Jan 17 2023, 23:13:24)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.4.0-1069-aws-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.6.112
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-40GB
Nvidia driver version: 510.47.03
cuDNN version: Probably one of the following:
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.5
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] pytorch-triton==2.0.0+0d7e753227
[pip3] torch==2.0.0.dev20230124+cu116
[pip3] torchvision==0.15.0.dev20230124
[conda] blas                      1.0                         mkl  
[conda] mkl                       2021.4.0           h06a4308_640  
[conda] mkl-service               2.4.0            py38h7f8727e_0  
[conda] mkl_fft                   1.3.1            py38hd3c417c_0  
[conda] mkl_random                1.2.2            py38h51133e4_0  
[conda] numpy                     1.23.5           py38h14f4228_0  
[conda] numpy-base                1.23.5           py38h31eccc5_0  
[conda] pytorch                   2.0.0.dev20230124 py3.8_cuda11.6_cudnn8.3.2_0    pytorch-nightly
[conda] pytorch-cuda              11.6                 h867d48c_2    pytorch-nightly
[conda] pytorch-mutex             1.0                        cuda    pytorch-nightly
[conda] pytorch-triton            2.0.0+0d7e753227          pypi_0    pypi
[conda] torch                     2.0.0.dev20230124+cu116          pypi_0    pypi
[conda] torchtriton               2.0.0+0d7e753227            py38    pytorch-nightly
[conda] torchvision               0.15.0.dev20230124      py38_cu116    pytorch-nightly
```
## Notes

- I have also tried to install from `.whl` files archived in s3, and I found that the problem starts to occur since the nightly version `2022-12-15`. The version `2022-12-14` dont get the error `RuntimeError: GET was unable to find an engine to execute this computation`.
- After further investigation, seems like the problem is on the pytorch core package since I got the same exact behaviour when we install torchvision via source, will move the issue to pytorch/pytorch for this.
~~- The error is resolved when I manually install `torchtriton` using conda. So the following command will work as expected:~~ --> This only seems to fix because it actually replace the pytorch core 

cc @ezyang @seemethere @malfet @csarofeen @ptrblck @xwang233