Repository: pytorch
Issue: pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel docker container contains cudnn 8.2, not 7.x as the name implies
Labels: triaged,module: docker

### 🐛 Describe the bug

The name of the [pytorch/pytorch:1.9.0-cuda10.2-cudnn7-devel docker container](https://hub.docker.com/layers/pytorch/pytorch/1.9.0-cuda10.2-cudnn7-devel/images/sha256-a027b6b72224e501371edb441877ac0a0771c01c1feff273d219c0fb43407ccd?context=explore) implies that it has cudnn 7.x installed in it. It does not. It contains cudnn 8.2.

To reproduce this:

`docker pull pytorch/pytorch:1.9.0-cuda10.2-cudnn7-devel`
`docker run -it pytorch/pytorch:1.9.0-cuda10.2-cudnn7-devel cat /usr/include/cudnn_version.h | grep CUDNN_MAJOR -A 2`

The output indicates that cudnn 8.2 is installed:
```
#define CUDNN_MAJOR 8
#define CUDNN_MINOR 2
#define CUDNN_PATCHLEVEL 0
--
  #define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)

#endif /* CUDNN_VERSION_H */
```

When I run `collect_env.py` in that same container I also see that it agrees cudnn 8.2 is installed:

`docker run -it pytorch/pytorch:1.9.0-cuda10.2-cudnn7-devel /bin/bash -c "apt-get update && apt-get install -y wget && wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py && python collect_env.py"`

That output is included below in the `Versions` section

### Versions

Collecting environment information...
PyTorch version: 1.9.0
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.5 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-2.10

Python version: 3.7.10 (default, Feb 26 2021, 18:47:35)  [GCC 7.3.0] (64-bit runtime)
Python platform: Linux-5.10.25-linuxkit-x86_64-with-debian-buster-sid
Is CUDA available: False
CUDA runtime version: 10.2.89
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.2.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.20.2
[pip3] torch==1.9.0
[pip3] torchelastic==0.2.0
[pip3] torchtext==0.10.0
[pip3] torchvision==0.10.0
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               10.2.89              h6bb024c_0    nvidia
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.2.0           h06a4308_296  
[conda] mkl-service               2.3.0            py37h27cfd23_1  
[conda] mkl_fft                   1.3.0            py37h42c9631_2  
[conda] mkl_random                1.2.1            py37ha9443f7_2  
[conda] numpy                     1.20.2           py37h2d18471_0  
[conda] numpy-base                1.20.2           py37hfae3a4d_0  
[conda] pytorch                   1.9.0           py3.7_cuda10.2_cudnn7.6.5_0    pytorch
[conda] torchelastic              0.2.0                    pypi_0    pypi
[conda] torchtext                 0.10.0                     py37    pytorch
[conda] torchvision               0.10.0               py37_cu102    pytorch


cc @malfet @seemethere @csarofeen @ptrblck @xwang233