For Cloud (Alveo U200/U250 Cards) - 1.4 English

1. Clone the Vitis AI repository.

   $git clone --recurse-submodules https://github.com/Xilinx/Vitis-AI
   $cd Vitis-AI

2. Run Docker container according to the instructions in the docker installation guide.

   $./docker_run.sh -X xilinx/vitis-ai-cpu:<x.y.z>

   Note: A workspace folder is created by the docker runtime system, and is mounted in /workspace of the docker runtime system.
3. Activate the conda environment.

   $conda activate vitis-ai-caffe

4. To modify the library source code, view and modify them under /workspace/Vitis-AI-Library. Before compiling the AI libraries, confirm the compiled output path. The default output path is $HOME/build. If you want to change the default output path, modify the `build_dir_default` in cmake.sh.

   build_dir_default=$HOME/build/build.${target_info}/${project_name}
   to build_dir_default=/workspace/build/build.${target_info}/$
   {project_name}

   Note: If you want to modify the build_dir_default, it is suggested to modify $HOME.
5. Execute the following command to build all DPUCADX8G supported examples in the AI Library.

   $cd /workspace/Vitis-AI-Library
   $./cmake.sh --clean --type=release --cmake-options=-DCMAKE_PREFIX_PATH=$CONDA_PREFIX --cmake-options=-DENABLE_DPUCADX8G_RUNNER=ON

After successful building, you can find the generated AI libraries and executables under build_dir_default.