Default Tensorflow binary does not work; outdated/incompatible cuDNN version

The `azureml_py38_PT_TF` conda environment is broken and doesn't work as the current (as of 17/05/2023) as the default cuDNN binary is version `6.1`, which is not compatible with any version of tensorflow.

Current work around is to manually update the cuDNN binaries as below, using the link [from Nvidia](https://developer.nvidia.com/rdp/cudnn-archive)

```sh
export URL="CUDNN-8.6.0-LINK-FROM-NVIDIA-WEBSITE"
# ==== DOWNLOAD CUDDN ====
curl $URL -o ./cudnn-linux-x86_64-8.6.0.163_cuda11-archive.tar.xz
sudo tar -xvf ./cudnn-linux-x86_64-8.6.0.163_cuda11-archive.tar.xz
# ==== INSTALL CUDDN ====
sudo cp ./cudnn-*-archive/include/cudnn*.h /usr/local/cuda/include
sudo cp -P ./cudnn-*-archive/lib/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
# ==== LINK UPDATED BINARIES ====
sudo ldconfig
# ==== INSTALL CONDA ENV ====
conda create -n "tfgpu" python=3.10 -y
conda activate tfgpu
conda install -c conda-forge cudatoolkit=11.8.0 ipykernel -y
python3 -m pip install nvidia-cudnn-cu11==8.6.0.163 tensorflow==2.12.*
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
echo 'CUDNN_PATH=$(dirname $(python -c "import nvidia.cudnn;print(nvidia.cudnn.__file__)"))' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/:$CUDNN_PATH/lib' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
source $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
python3 -m ipykernel install --user --name tfgpu --display-name "Python (tf-cudnn8.6)"
# ==== VERIFY ====
python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
```

Is it possible to bump the included cuDNN version to get around this problem?

([Associated SO post](https://stackoverflow.com/a/76274154/8162159))