diff --git a/scripts/install/purge-cuda.sh b/scripts/install/purge-cuda.sh
index a62b46a5625..caaabed5c37 100644
--- a/scripts/install/purge-cuda.sh
+++ b/scripts/install/purge-cuda.sh
@@ -1,5 +1,4 @@
 #!/bin/bash
-
 sudo apt-get --purge remove nvidia-*
 sudo apt-get --purge remove cuda-*
 sudo apt-get --purge remove cudnn-*
diff --git a/scripts/install/ubuntu-conda.sh b/scripts/install/ubuntu-conda.sh
index a7895312af7..10744381ac5 100644
--- a/scripts/install/ubuntu-conda.sh
+++ b/scripts/install/ubuntu-conda.sh
@@ -2,6 +2,7 @@
 set -ex
 
 MINDSPORE_VERSION=${MINDSPORE_VERSION:-1.5.0}
+PYTHON_VERSION=${PYTHON_VERSION:-3.7.5}
 
 #use huaweicloud mirror in China
 sudo sed -i "s@http://.*archive.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
@@ -14,14 +15,14 @@ sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 100
 
 cd /tmp
 curl -O https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-py37_4.10.3-Linux-x86_64.sh
-bash Miniconda3-py37_4.10.3-Linux-x86_64.sh
+bash Miniconda3-py37_4.10.3-Linux-x86_64.sh -b 
 
 # add conda to PATH
  echo -e 'export PATH=~/miniconda3/bin/:$PATH' >> ~/.bash_profile
  echo -e '. ~/miniconda3/etc/profile.d/conda.sh' >> ~/.bash_profile
  source ~/.bash_profile
 conda init bash
-# setting up conda mirror
+# setting up conda mirror with qinghua source
 cat >~/.condarc  <<END
 channels:
   - defaults
@@ -42,6 +43,25 @@ END
 
 #initialize conda env and install mindspore-cpu
 
-conda create -n py37  python=3.7.5 -y
-conda activate py37
-conda install mindspore-cpu=${MINDSPORE_VERSION} -c mindspore -c conda-forge -y
\ No newline at end of file
+conda create -n ms_${PYTHON_VERSION} python=${PYTHON_VERSION} -y
+conda activate ms_${PYTHON_VERSION}
+conda install mindspore-cpu=${MINDSPORE_VERSION} -c mindspore -c conda-forge -y
+
+# check if it is the right mindspore version
+python -c "import mindspore;mindspore.run_check()"
+
+# check if it can be run with GPU
+
+cat > example.py <<END
+import numpy as np
+from mindspore import Tensor
+import mindspore.ops as ops
+import mindspore.context as context
+
+context.set_context(device_target="GPU")
+x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+print(ops.add(x, y))
+END
+
+python example.py
\ No newline at end of file
diff --git a/scripts/install/ubuntu-gpu-conda.sh b/scripts/install/ubuntu-gpu-conda.sh
index d226a733bdd..45462570c9a 100644
--- a/scripts/install/ubuntu-gpu-conda.sh
+++ b/scripts/install/ubuntu-gpu-conda.sh
@@ -4,29 +4,20 @@ set -ex
 MINDSPORE_VERSION=${MINDSPORE_VERSION:-1.5.0}
 PYTHON_VERSION=${PYTHON_VERSION:-3.7.5}
 MINDSPORE_VERSION=${MINDSPORE_VERSION:-1.5.0}
-CUDA_VERSION=${CUDA_VERSION:-8.0.5.39-1+cuda11.1}
+CUDA_VERSION=${CUDA_VERSION:-11.1.1-1}
+LIB_CUDA_VERSION=${LIB_CUDA_VERSION:-8.0.5.39-1+cuda11.1}
 DISTRIBUTED=${DISTRIBUTED:-false}
-CUDA_INSTALL_PATH=${CUDA_INSTALL_PATH:-cuda-11}
 CUDATOOLKIT_VERSION=${CUDATOOLKIT_VERSION:-11.1}
 CUDNN_VERSION=${CUDNN_VERSION:-8.0.5}
 
-#use huaweicloud mirror in China
-sudo sed -i "s@http://.*archive.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
-sudo sed -i "s@http://.*security.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
-sudo apt-get update
-
-# install python 3.7 and make it default
-sudo apt-get install gcc-7 libgmp-dev curl python3.7  -y
-sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 100
-
 cd /tmp
 curl -O https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-py37_4.10.3-Linux-x86_64.sh
 bash Miniconda3-py37_4.10.3-Linux-x86_64.sh
 
 # add conda to PATH
- echo -e 'export PATH=~/miniconda3/bin/:$PATH' >> ~/.bash_profile
- echo -e '. ~/miniconda3/etc/profile.d/conda.sh' >> ~/.bash_profile
- source ~/.bash_profile
+echo -e 'export PATH=~/miniconda3/bin/:$PATH' >> ~/.bash_profile
+echo -e '. ~/miniconda3/etc/profile.d/conda.sh' >> ~/.bash_profile
+source ~/.bash_profile
 conda init bash
 # setting up conda mirror
 cat >~/.condarc  <<END
@@ -49,68 +40,39 @@ END
 
 #initialize conda env and install mindspore-cpu
 
-conda create -n py37  python=3.7.5 -y
-conda activate py37
+conda create -n ms_${PYTHON_VERSION} python=${PYTHON_VERSION} -y
+conda activate ms_${PYTHON_VERSION}
 
 # install gmp 6.1.2, downloading gmp is slow
-echo "install gmp start"
-
-sudo apt-get install m4 -y 
-cd /tmp
-curl -O https://gmplib.org/download/gmp/gmp-6.1.2.tar.xz
-xz -d gmp-6.1.2.tar.xz
-tar xvzf gmp-6.1.2.tar && cd gmp-6.1.2
-./configure --prefix=/usr/local/gmp-6.1.2
-make
-sudo make install
-echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/gmp-6.1.2/lib' >> ~/.bash_profile
-
-echo "install gmp success"
-# install cuda with apt-get
-echo "install cuda start"
-
-wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
-sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
-wget -c https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
-sudo dpkg -i cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
-sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
-sudo apt-get update
-sudo apt-get -y install cuda
-
-# add cuda to path 
-cat >> ~/.bash_profile <<END
-export PATH=/usr/local/cuda/bin:\$PATH
-export LD_LIBRARY_PATH=\$LD_LIBRARY_PATH:/usr/local/cuda/lib64
-END
-source ~/.bash_profile
-
-echo "cuda install success."
-
-# install cudnn
-cd /tmp
-wget https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64/libcudnn8_${CUDA_VERSION}_amd64.deb
-wget https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64/libcudnn8-dev_${CUDA_VERSION}_amd64.deb
-sudo dpkg -i libcudnn8_${CUDA_VERSION}_amd64.deb libcudnn8-dev_${CUDA_VERSION}_amd64.deb
-
-# Install CuDNN 8 and NCCL 2
-wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
-sudo dpkg -i nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
-sudo apt update
-sudo apt install -y libcudnn8=${CUDA_VERSION} libcudnn8-dev=${CUDA_VERSION} libnccl2=2.7.8-1+cuda11.1 libnccl2-dev=2.7.8-1+cuda11.1 
-
-# optional (tensort for serving, openmpi for distributed training)
-if [[ "$DISTRIBUTED" == "false" ]]; then
-    cd /tmp
-    curl -O https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.3.tar.gz
-    tar xvzf openmpi-4.0.3.tar.gz
-    cd openmpi-4.0.3
-    ./configure --prefix=/usr/local/openmpi
-    make 
-    sudo make install 
-    echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/openmpi/lib' >> ~/.bash_profile
-    echo 'export PATH=$PATH:/usr/local/openmpi/bin' >> ~/.bash_profile
-    source ~/.bash_profile
-fi
+# echo "install gmp start"
+# sudo apt-get install m4 -y 
+# cd /tmp
+# curl -O https://gmplib.org/download/gmp/gmp-6.1.2.tar.xz
+# xz -d gmp-6.1.2.tar.xz
+# tar xvzf gmp-6.1.2.tar && cd gmp-6.1.2
+# ./configure --prefix=/usr/local/gmp-6.1.2
+# make
+# sudo make install
+# echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/gmp-6.1.2/lib' >> ~/.bash_profile
 
 # install mindspore-gpu with conda
-conda install mindspore-gpu=${MINDSPORE_VERSION} cudatoolkit=${CUDATOOLKIT_VERSION} cudnn=${CUDNN_VERSION} -c mindspore -c conda-forge
+conda install mindspore-gpu=${MINDSPORE_VERSION} cudatoolkit=${CUDATOOLKIT_VERSION} -c mindspore -c conda-forge -y
+
+# check if it is the right mindspore version
+python -c "import mindspore;mindspore.run_check()"
+
+# check if it can be run with GPU
+
+cat > example.py <<END
+import numpy as np
+from mindspore import Tensor
+import mindspore.ops as ops
+import mindspore.context as context
+
+context.set_context(device_target="GPU")
+x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+print(ops.add(x, y))
+END
+
+python example.py
\ No newline at end of file
diff --git a/scripts/install/ubuntu-gpu-pip.sh b/scripts/install/ubuntu-gpu-pip.sh
index d33de3ae3bb..c7bce98d36f 100644
--- a/scripts/install/ubuntu-gpu-pip.sh
+++ b/scripts/install/ubuntu-gpu-pip.sh
@@ -5,14 +5,14 @@ PYTHON_VERSION=${PYTHON_VERSION:-3.7.5}
 MINDSPORE_VERSION=${MINDSPORE_VERSION:-1.5.0}
 CUDA_VERSION=${CUDA_VERSION:-8.0.5.39-1+cuda11.1}
 DISTRIBUTED=${DISTRIBUTED:-false}
-CUDA_INSTALL_PATH=${CUDA_INSTALL_PATH:-cuda-11}
+CUDA_VERSION=${CUDA_VERSION:-11.1.1-1}
+CUDA_INSTALL_PATH=${CUDA_INSTALL_PATH:-cuda-11.1}
+LIBNCCL2_VERSION=${LIBNCCL2_VERSION:-2.7.8-1+cuda11.1}
 ARCH=$(uname -m)
 
-if [[ "${PYTHON_VERSION}" == "3.7.5" ]]; then
-VERSION="${MINDSPORE_VERSION}-cp37-cp37m"
-else
-VERSION="${MINDSPORE_VERSION}-cp39-cp39m"
-fi
+declare -A version_map=()
+version_map["3.7.5"]="${MINDSPORE_VERSION}-cp37-cp37m"
+version_map["3.9.0"]="${MINDSPORE_VERSION}-cp39-cp39m"
 
 #use huaweicloud mirror in China
 sudo sed -i "s@http://.*archive.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
@@ -20,7 +20,7 @@ sudo sed -i "s@http://.*security.ubuntu.com@http://repo.huaweicloud.com@g" /etc/
 sudo apt-get update
 
 # install python 3.7 and make it default
-sudo apt-get install gcc-7 libgmp-dev curl python3.7  openssl ubuntu-drivers-common openssl -y
+sudo apt-get install gcc-7 libgmp-dev curl python3.7  openssl ubuntu-drivers-common openssl software-properties-common -y
 sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 100
 
 cd /tmp
@@ -28,9 +28,7 @@ curl -O https://bootstrap.pypa.io/get-pip.py
 sudo python get-pip.py
 
 # add pip mirror
-
-mkdir ~/.pip
-
+mkdir -p ~/.pip
 cat > ~/.pip/pip.conf <<END
 [global]
 index-url = https://repo.huaweicloud.com/repository/pypi/simple
@@ -38,28 +36,55 @@ trusted-host = repo.huaweicloud.com
 timeout = 120
 END
 
-# install gmp 6.1.2, downloading gmp is slow
+# install nvidia driver if not presented
+# root@ecs-gpu-testing:~# ubuntu-drivers devices
+# == /sys/devices/pci0000:20/0000:20:00.0/0000:21:01.0 ==
+# modalias : pci:v000010DEd00001EB8sv000010DEsd000012A2bc03sc02i00
+# vendor   : NVIDIA Corporation
+# driver   : nvidia-driver-418 - third-party non-free
+# driver   : nvidia-driver-450 - third-party non-free
+# driver   : nvidia-driver-460 - third-party non-free
+# driver   : nvidia-driver-450-server - distro non-free
+# driver   : nvidia-driver-460-server - distro non-free
+# driver   : nvidia-driver-440 - third-party non-free
+# driver   : nvidia-driver-418-server - distro non-free
+# driver   : nvidia-driver-465 - third-party non-free
+# driver   : nvidia-driver-470 - third-party non-free recommended #pick the latest one
+# driver   : nvidia-driver-410 - third-party non-free
+# driver   : nvidia-driver-470-server - distro non-free
+# driver   : nvidia-driver-455 - third-party non-free
+# driver   : xserver-xorg-video-nouveau - distro free builtin
+# sudo apt-get install nvidia-driver-470 -y
+# nvidia-smi # run this to check the driver is working
+#root@ecs-testing:~# nvidia-smi
+#Thu Dec 30 21:06:13 2021
+#+-----------------------------------------------------------------------------+
+#| NVIDIA-SMI 460.73.01    Driver Version: 460.73.01    CUDA Version: 11.2     |
+#|-------------------------------+----------------------+----------------------+
+#| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
+#| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
+#|                               |                      |               MIG M. |
+#|===============================+======================+======================|
+#|   0  Tesla T4            Off  | 00000000:21:01.0 Off |                    0 |
+#| N/A   61C    P0    29W /  70W |      0MiB / 15109MiB |      0%      Default |
+#|                               |                      |                  N/A |
+#+-------------------------------+----------------------+----------------------+
+#
+#+-----------------------------------------------------------------------------+
+#| Processes:                                                                  |
+#|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
+#|        ID   ID                                                   Usage      |
+#|=============================================================================|
+#|  No running processes found                                                 |
+#+-----------------------------------------------------------------------------+
 
-sudo apt-get install m4 -y 
-cd /tmp
-curl -O https://gmplib.org/download/gmp/gmp-6.1.2.tar.xz
-xz -d gmp-6.1.2.tar.xz
-tar xvzf gmp-6.1.2.tar && cd gmp-6.1.2
-./configure --prefix=/usr/local/gmp-6.1.2
-make
-sudo make install
-echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/gmp-6.1.2/lib' >> ~/.bash_profile
-
-# install cuda with linux.run
-# another option is to use https://developer.download.nvidia.com/compute/cuda/11.1.0/local_installers/cuda_11.1.0_455.23.05_linux.run
-
-wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
-sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
-wget -c https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
-sudo dpkg -i cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
-sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
+# install cuda/cudnn/nccl2 with apt-get
+# another option is to use linux.run https://developer.download.nvidia.com/compute/cuda/11.1.0/local_installers/cuda_11.1.0_455.23.05_linux.run
+sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
+sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
+sudo add-apt-repository "deb https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1804/x86_64/ /"
 sudo apt-get update
-sudo apt-get -y install cuda
+sudo apt-get -y install cuda=${CUDA_VERSION}
 
 # add cuda to path 
 cat >> ~/.bash_profile <<END
@@ -67,35 +92,43 @@ export PATH=/usr/local/cuda/bin:\$PATH
 export LD_LIBRARY_PATH=\$LD_LIBRARY_PATH:/usr/local/cuda/lib64
 END
 source ~/.bash_profile
-
 echo "cuda install success."
 
-# install cudnn
-cd /tmp
-wget https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64/libcudnn8_${CUDA_VERSION}_amd64.deb
-wget https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu1804/x86_64/libcudnn8-dev_${CUDA_VERSION}_amd64.deb
-sudo dpkg -i libcudnn8_${CUDA_VERSION}_amd64.deb libcudnn8-dev_${CUDA_VERSION}_amd64.deb
-
-# Install CuDNN 8 and NCCL 2
-wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
-sudo dpkg -i nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
-sudo apt update
-sudo apt install -y libcudnn8=${CUDA_VERSION} libcudnn8-dev=${CUDA_VERSION} libnccl2=2.7.8-1+cuda11.1 libnccl2-dev=2.7.8-1+cuda11.1 
+sudo apt-get install -y libcudnn8=${CUDA_VERSION} libcudnn8-dev=${CUDA_VERSION} libnccl2=${LIBNCCL2_VERSION} libnccl-dev=${LIBNCCL2_VERSION}
 
 # optional (tensort for serving, openmpi for distributed training)
-if [[ "$DISTRIBUTED" == "false" ]]; then
-    cd /tmp
-    curl -O https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.3.tar.gz
-    tar xvzf openmpi-4.0.3.tar.gz
-    cd openmpi-4.0.3
-    ./configure --prefix=/usr/local/openmpi
-    make 
-    sudo make install 
-    echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/openmpi/lib' >> ~/.bash_profile
-    echo 'export PATH=$PATH:/usr/local/openmpi/bin' >> ~/.bash_profile
-    source ~/.bash_profile
-fi
+# uncomment this to compile openmpi
+#   cd /tmp
+#   curl -O https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.3.tar.gz
+#   tar xvzf openmpi-4.0.3.tar.gz
+#   cd openmpi-4.0.3
+#   ./configure --prefix=/usr/local/openmpi
+#   make 
+#   sudo make install 
+#   echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/openmpi/lib' >> ~/.bash_profile
+#   echo 'export PATH=$PATH:/usr/local/openmpi/bin' >> ~/.bash_profile
+#   source ~/.bash_profile
+#  reference this to install tensorrt https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html#downloading
 
-# install mindspore gpu
+echo "install mindspore gpu ${MINDSPORE_VERSION}"
+pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/${MINDSPORE_VERSION}/MindSpore/gpu/${ARCH}/${CUDA_INSTALL_PATH}/mindspore_gpu-${version_map["$PYTHON_VERSION"]}-linux_${ARCH}.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
 
-pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/${MINDSPORE_VERSION}/MindSpore/gpu/${CUDA_INSTALL_PATH}/mindspore-${VERSION}-linux_${ARCH}.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
\ No newline at end of file
+
+# check if it is the right mindspore version
+python -c "import mindspore;mindspore.run_check()"
+
+# check if it can be run with GPU
+
+cat > example.py <<END
+import numpy as np
+from mindspore import Tensor
+import mindspore.ops as ops
+import mindspore.context as context
+
+context.set_context(device_target="GPU")
+x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+print(ops.add(x, y))
+END
+
+python example.py
\ No newline at end of file
diff --git a/scripts/install/ubuntu-pip.sh b/scripts/install/ubuntu-pip.sh
index f68938e2540..0349e0b857f 100644
--- a/scripts/install/ubuntu-pip.sh
+++ b/scripts/install/ubuntu-pip.sh
@@ -6,12 +6,8 @@ PYTHON_VERSION=${PYTHON_VERSION:-3.7.5}
 MINDSPORE_VERSION=${MINDSPORE_VERSION:-1.5.0}
 ARCH=`uname -m`
 
-if [[ "${PYTHON_VERSION}" == "3.7.5" ]]; then
-VERSION="${MINDSPORE_VERSION}-cp37-cp37m"
-else
-VERSION="${MINDSPORE_VERSION}-cp39-cp39"
-fi
-
+declare -A version_map=()
+version_map["3.7.5"]="${MINDSPORE_VERSION}-cp37-cp37m"
 
 #use huaweicloud mirror in China
 sudo sed -i "s@http://.*archive.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
@@ -26,4 +22,23 @@ cd /tmp
 curl -O https://bootstrap.pypa.io/get-pip.py
 sudo python get-pip.py
 
-pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/${MINDSPORE_VERSION}/MindSpore/cpu/${ARCH}/mindspore-${VERSION}-linux_${ARCH}.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
\ No newline at end of file
+pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/${MINDSPORE_VERSION}/MindSpore/cpu/${ARCH}/mindspore-${version_map["$PYTHON_VERSION"]}-linux_${ARCH}.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+# check if it is the right mindspore version
+python -c "import mindspore;mindspore.run_check()"
+
+# check if it can be run with GPU
+
+cat > example.py <<END
+import numpy as np
+from mindspore import Tensor
+import mindspore.ops as ops
+import mindspore.context as context
+
+context.set_context(device_target="GPU")
+x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
+print(ops.add(x, y))
+END
+
+python example.py
\ No newline at end of file