use cuda 11

images/scipy-ml-notebook/Dockerfile

@@ -9,7 +9,7 @@ USER root
 
 # coerce rebuild in only this nteb
 
-ARG LIBNVINFER=7.2.2 LIBNVINFER_MAJOR_VERSION=7 CUDA_VERSION=12.2
+ARG LIBNVINFER=7.2.2 LIBNVINFER_MAJOR_VERSION=7 CUDA_VERSION=11.8
 
 RUN apt-get update && \
   apt-get install -y \
@@ -31,20 +31,20 @@ ADD manual_tests /opt/manual_tests
 RUN chmod 777 /etc/datahub-profile.d/*.sh /tmp/activate.sh
 
 RUN apt update && apt install -y wget && \
-    wget https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/libcudnn8_8.9.6.50-1+cuda12.2_amd64.deb && \
-    dpkg -i libcudnn8_8.9.6.50-1+cuda12.2_amd64.deb && \
-    rm libcudnn8_8.9.6.50-1+cuda12.2_amd64.deb && \
+    wget https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/libcudnn8_8.9.6.50-1+cuda11.8_amd64.deb && \
+    dpkg -i libcudnn8_8.9.6.50-1+cuda11.8_amd64.deb && \
+    rm libcudnn8_8.9.6.50-1+cuda11.8_amd64.deb && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
 USER jovyan
 
-# CUDA 12
+# CUDA 11.8
 # tf requirements: https://www.tensorflow.org/install/pip#linux
-RUN mamba install -c "nvidia/label/cuda-12.2" cuda-nvcc -y && \
+RUN mamba install -c "nvidia/label/cuda-11.8" cuda-nvcc -y && \
   fix-permissions $CONDA_DIR && \
   fix-permissions /home/$NB_USER && \
- mamba clean -a -y
+  mamba clean -a -y
 
 #RUN mamba list | egrep '(cuda-version|nvidia/label/cuda)' | awk '{ print $1"=="$2;}' > public/envs/test3/conda-meta/pinned
 
@@ -67,7 +67,7 @@ RUN pip install --no-cache-dir protobuf==3.20.3
 RUN pip install opencv-contrib-python-headless \
     opencv-python \
     datascience \
-    nvidia-cudnn-cu12==8.9.6.50 \
+    nvidia-cudnn-cu11==8.9.6.50 \
     tensorflow==2.14.0 \ 
     tensorflow-datasets \
     tensorrt==8.6.1 && \