[CI] upgrade CI pytorch version (#5047)

* upgrade CI pytorch version

* update

* revert tensorflow image

* old image (220816) backup

* Update Dockerfile.ci_gpu

Jenkinsfile

@@ -261,7 +261,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-cpu-node"
-                  image "dgllib/dgl-ci-cpu:v220816"
+                  image "dgllib/dgl-ci-cpu:v221216"
                   args "-u root"
                   alwaysPull true
                 }
@@ -279,7 +279,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-cpu-node"
-                  image "dgllib/dgl-ci-gpu:cu101_v220816"
+                  image "dgllib/dgl-ci-gpu:cu102_v221216"
                   args "-u root"
                   alwaysPull true
                 }
@@ -334,7 +334,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-cpu-node"
-                  image "dgllib/dgl-ci-cpu:v220816"
+                  image "dgllib/dgl-ci-cpu:v221216"
                   alwaysPull true
                 }
               }
@@ -351,7 +351,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-gpu-node"
-                  image "dgllib/dgl-ci-gpu:cu101_v220816"
+                  image "dgllib/dgl-ci-gpu:cu102_v221216"
                   args "--runtime nvidia"
                   alwaysPull true
                 }
@@ -423,7 +423,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-cpu-node"
-                  image "dgllib/dgl-ci-cpu:v220816"
+                  image "dgllib/dgl-ci-cpu:v221216"
                   args "--shm-size=4gb"
                   alwaysPull true
                 }
@@ -475,7 +475,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-gpu-node"
-                  image "dgllib/dgl-ci-gpu:cu101_v220816"
+                  image "dgllib/dgl-ci-gpu:cu102_v221216"
                   args "--runtime nvidia --shm-size=8gb"
                   alwaysPull true
                 }
@@ -503,7 +503,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-cpu-node"
-                  image "dgllib/dgl-ci-cpu:ssh_v220818"
+                  image "dgllib/dgl-ci-cpu:v221216"
                   args "--shm-size=4gb"
                   alwaysPull true
                 }
@@ -548,7 +548,7 @@ pipeline {
               agent {
                 docker {
                   label "linux-cpu-node"
-                  image "dgllib/dgl-ci-cpu:v220816"
+                  image "dgllib/dgl-ci-cpu:v221216"
                   alwaysPull true
                 }
               }

docker/Dockerfile.ci_gpu

 # CI docker GPU env
-FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
+FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
 
 ENV TZ=US
 RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
 
+# Update outdated public key from NVIDIA
+RUN apt-key del 3bf863cc
+RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
 RUN apt-get update --fix-missing
 
 COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh

docker/Dockerfile.ci_gpu_220816

+# CI docker GPU env
+FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
+
+ENV TZ=US
+RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
+
+RUN apt-get update --fix-missing
+
+COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh
+RUN bash /install/ubuntu_install_core.sh
+
+COPY install/ubuntu_install_build.sh /install/ubuntu_install_build.sh
+RUN bash /install/ubuntu_install_build.sh
+
+# python
+COPY install/ubuntu_install_conda.sh /install/ubuntu_install_conda.sh
+RUN bash /install/ubuntu_install_conda.sh
+
+ENV CONDA_ALWAYS_YES="true"
+
+COPY install/conda_env/torch_gpu.yml /install/conda_env/torch_gpu.yml
+COPY install/conda_env/torch_gpu_pip.txt /install/conda_env/torch_gpu_pip.txt
+RUN ["/bin/bash", "-i", "-c", "conda env create -f /install/conda_env/torch_gpu.yml"]
+
+COPY install/conda_env/tensorflow_gpu.yml /install/conda_env/tensorflow_gpu.yml
+RUN ["/bin/bash", "-i", "-c", "conda env create -f /install/conda_env/tensorflow_gpu.yml"]
+
+COPY install/conda_env/mxnet_gpu.yml /install/conda_env/mxnet_gpu.yml
+RUN ["/bin/bash", "-i", "-c", "conda env create -f /install/conda_env/mxnet_gpu.yml"]
+
+ENV CONDA_ALWAYS_YES=
+
+# Environment variables
+ENV PATH=/usr/local/nvidia/bin:${PATH}
+ENV PATH=/usr/local/cuda/bin:${PATH}
+ENV CPLUS_INCLUDE_PATH=/usr/local/cuda/include:${CPLUS_INCLUDE_PATH}
+ENV C_INCLUDE_PATH=/usr/local/cuda/include:${C_INCLUDE_PATH}
+ENV LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64:${LIBRARY_PATH}
+ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64:${LD_LIBRARY_PATH}
+ENV CUDA_VISIBLE_DEVICES=0
+ENV TF_FORCE_GPU_ALLOW_GROWTH=true
\ No newline at end of file

docker/install/conda_env/torch_cpu_pip.txt

 --find-links https://download.pytorch.org/whl/torch_stable.html
-torch==1.9.0+cpu
+torch==1.12.0+cpu
 pytest
 nose
 numpy

docker/install/conda_env/torch_gpu_pip.txt

 --find-links https://download.pytorch.org/whl/torch_stable.html
-torch==1.9.0+cu102
+torch==1.12.0+cu102
 pytest
 nose
 numpy