install_azure.sh

# Install.md

### Debug stub library error:


```bash
ldd -r /home/ubuntu/miniconda3/envs/pllava/lib/*/*/*/*.so | grep -a2 -b2 stub
```

## 1. Install gcc-13 for PyTorch AVX512 optimizations

```bash
sudo mv /etc/apt/sources.list.d/nvidia-docker.list /etc/apt
sudo apt update
sudo apt full-upgrade

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt update
sudo apt install gcc-13 g++-13
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-13 200
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-13 200
sudo update-alternatives --display gcc
sudo update-alternatives --display g++
```

## 2.1 Install nvidia-driver-550

```bash
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.1-1_all.deb # 20.04
sudo apt install ./cuda-keyring_1.1-1_all.deb
sudo apt update
sudo apt install nvidia-driver-550
sudo reboot
rm cuda-keyring_1.1-1_all.deb
```

## 2.2 Install CUDA 12.4

```bash
sudo apt install cuda-toolkit-12-4
sudo bash -c "echo '/usr/local/cuda/lib64' >> /etc/ld.so.conf"
sudo ldconfig
sudo vim /etc/environment # on a new line, type LD_LIBRARY_PATH="/usr/local/lib:/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}"
sudo reboot
```

## 2.3 Install cuDNN 9

```bash
sudo apt install cudnn9-cuda-12 libcudnn9-samples
```

## 2.4 Install miscellaneous NVIDIA libraries

```bash
sudo apt install libcusparse-12-4 libcusparse-dev-12-4 libcusparselt0 libcusparselt-dev # CUSparse and CUSparse-LT
sudo apt install nvidia-fabricmanager-550 nvidia-fabricmanager-dev-550 cuda-drivers-fabricmanager-550 # NVIDIA Fabric Manager for NVLink/NVSwitch
sudo apt install libnccl2 libnccl-dev # NCCL
sudo apt install libxnvctrl0=550.* nvidia-settings=550.* # Miscellaneous NVIDIA management tools
sudo apt install nvidia-container-toolkit # 2.5 (Optional) NVIDIA Docker
```

### 2.5 Start NVIDIA Fabric Manager service
```bash
sudo systemctl enable nvidia-fabricmanager.service
sudo systemctl start nvidia-fabricmanager.service
```

## 2.5 apt clean up

```bash
sudo apt autoremove
sudo apt clean
sudo apt autoclean
```

## 3.1. Install NVIDIA Video Codec SDK headers

```bash
cd
git clone --single-branch --branch n12.0.16.1 https://git.videolan.org/git/ffmpeg/nv-codec-headers.git # NOTE: n11.1.5.3 works. n12.0.16.0 works. n12.0.16.1 works. n12.1.14.0 and above do not work.
cd nv-codec-headers
sudo make install
cd
rm -rf nv-codec-headers
```

## 3.2. Install ffmpeg5 with NVIDIA Video Codec SDK support

```bash
cd
git clone --single-branch --branch n5.1.4 https://git.ffmpeg.org/ffmpeg.git # NOTE: 6.0 and above will break decord.
cd ffmpeg
sudo apt install yasm libgnutls28-dev libx264-dev
# NOTE: --enable-nvdec could fail for gpus without nvdec support, such as A100. Works for V100. See https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new
export MY_SM=70 # NOTE: For V100, it's 70. See https://developer.nvidia.com/cuda-gpus
./configure \
  --extra-cflags='-I/usr/local/cuda/include -I/usr/local/include' \
  --extra-ldflags='-L/usr/local/cuda/lib64' \
  --nvccflags="-gencode arch=compute_${MY_SM},code=sm_${MY_SM} -O2" \
  --disable-doc \
  --enable-decoder=aac \
  --enable-decoder=h264 \
  --enable-decoder=h264_cuvid \
  --enable-decoder=rawvideo \
  --enable-indev=lavfi \
  --enable-encoder=libx264 \
  --enable-encoder=h264_nvenc \
  --enable-demuxer=mov \
  --enable-muxer=mp4 \
  --enable-filter=scale \
  --enable-filter=testsrc2 \
  --enable-protocol=file \
  --enable-protocol=https \
  --enable-gnutls \
  --enable-gpl \
  --enable-nonfree \
  --enable-cuda \
  --enable-cuda-nvcc \
  --enable-libx264 \
  --enable-nvenc \
  --enable-nvdec \
  --enable-libnpp \
  --enable-cuvid \
  --disable-postproc \
  --enable-shared \
  --disable-static
make clean
make -j
sudo make install
sudo sh -c "echo '/usr/local/lib' >> /etc/ld.so.conf"
sudo ldconfig
cd && rm -rf ffmpeg
```

## 3.3. Confirm your ffmpeg has nvcodec enabled

```bash
# Examples in https://pytorch.org/audio/stable/build.ffmpeg.html#checking-the-intallation
ffprobe -hide_banner -decoders | grep h264
ffmpeg -hide_banner -encoders | grep 264
src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/NASAs_Most_Scientifically_Complex_Space_Observatory_Requires_Precision-MP4_small.mp4"
ffmpeg -hide_banner -y -vsync 0 \
     -hwaccel cuvid \
     -hwaccel_output_format cuda \
     -c:v h264_cuvid \
     -resize 360x240 \
     -i "${src}" \
     -c:a copy \
     -c:v h264_nvenc \
     -b:v 5M test.mp4
rm test.mp4
```

## 4.1 Install Anaconda under ${HOME}. Will not work under a network disk

```bash
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh # Say yes to everything
source .bashrc
rm Miniconda3-latest-Linux-x86_64.sh
conda update --all
conda install libgcc-ng=13.1 libstdcxx-ng=13.1 libgcc-ng=13.1 libgomp=13.1 -c defaults -c conda-forge
```

## 4.2 Install/Update AWS EFA

```bash
curl -O https://efa-installer.amazonaws.com/aws-efa-installer-1.32.0.tar.gz
tar -xf aws-efa-installer-1.32.0.tar.gz && cd aws-efa-installer
sudo ./efa_installer.sh -y
sudo bash -c "echo 'openmpi5' >> /etc/modules"
echo 'module load openmpi5' >> ~/.bashrc
sudo reboot
```

## 4.3 Build PyTorch from source

```bash
mv .condarc .condarc-old
conda create -n clean_pytorch_ffmpeg_build cmake ninja intel::mkl-static intel::mkl-include astunparse "expecttest!=0.2.0" hypothesis numpy psutil pyyaml requests setuptools "typing-extensions>=4.8.0" sympy filelock networkx jinja2 fsspec
conda activate clean_pytorch_ffmpeg_build
conda install libgcc-ng=13.1 libstdcxx-ng=13.1 libgcc-ng=13.1 libgomp=13.1 -c defaults -c conda-forge
conda install -c pytorch magma-cuda124
pip install types-dataclasses "optree>=0.9.1" lark
```

```bash
cd && git clone --recursive --single-branch --branch v2.3.1 https://github.com/pytorch/pytorch.git && cd pytorch
git submodule sync
git submodule update --init --recursive
# TODO: Monkey-patch ${HOME}/pytorch/aten/src/ATen/core/boxing/impl/boxing.h according to <https://github.com/pytorch/pytorch/issues/122169#issuecomment-2146155541>
```

```bash
export TORCH_CUDA_ARCH_LIST="7.0" # NOTE: For V100, it's 7.0. See https://developer.nvidia.com/cuda-gpus
export USE_FFMPEG=1
export _GLIBCXX_USE_CXX11_ABI=1
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
export USE_SYSTEM_NCCL=1
export NCCL_ROOT=/usr
export NCCL_INCLUDE_DIR=/usr/include # Also need this for suppressing "COULD NOT FIND NCCL"
rm ${CONDA_PREFIX}/lib/libffi.7.so ${CONDA_PREFIX}/lib/libffi.so.7
ln -sf /usr/lib/x86_64-linux-gnu/libstdc++.so.6 ${CONDA_PREFIX}/lib/libstdc++.so.6 # Fixes ImportError: ${CONDA_PREFIX}/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by ${CONDA_PREFIX}/lib/python3.12/site-packages/torch/lib/libtorch_python.so)
```

```bash
python setup.py clean && echo "Done Cleaning"
python setup.py install | tee install_pytorch.log # Wait 10 mins for it to finish.
echo "DONE building pytorch" && cd # NOTE it's important to move out of the pytorch build directory to import torch.
ln -sf /usr/lib/x86_64-linux-gnu/libstdc++.so.6 ${CONDA_PREFIX}/lib/libstdc++.so.6 # Fixes ImportError: ${CONDA_PREFIX}/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by ${CONDA_PREFIX}/lib/python3.12/site-packages/torch/lib/libtorch_python.so)
```

```bash
python -c "import torch; print(torch.cuda.is_available()); exit()"
python
import torch
torch.rand(2, 3, device='cuda') @ torch.rand(3, 2, device='cuda') # Check CUDA is working
torch.svd(torch.rand(3,3, device='cuda')) # Check MAGMA-CUDA is working
exit() # Get out of the Python shell.
python -m torch.utils.collect_env
```

## 4.4 Install torchvision

```bash
cd && git clone --recursive --single-branch --branch v0.18.1 https://github.com/pytorch/vision.git && cd vision
sudo ln /usr/lib/x86_64-linux-gnu/libnvcuvid.so.1 /usr/lib/x86_64-linux-gnu/libnvcuvid.so
# TODO download the cuviddec.h and nvdec.h header files from the specific version (12.0.1) from https://developer.nvidia.com/video-codec-sdk-archive and move them to /usr/local/cuda/include
scp ${HOME}/Downloads/Video_Codec_SDK_12.0.16/Interface/{cuviddec.h,nvcuvid.h,nvEncodeAPI.h} my_server:~ # NOTE: on laptop
sudo mv cuviddec.h /usr/local/cuda/include
sudo mv nvcuvid.h /usr/local/cuda/include
conda activate clean_pytorch_ffmpeg_build
export TORCH_CUDA_ARCH_LIST="7.0" # NOTE: For V100, it's 7.0. See https://developer.nvidia.com/cuda-gpus
export TORCHVISION_INCLUDE=/usr/local/include:/usr/local/include/ffnvcodec:/usr/local/cuda/include # for cuviddec.h and nvcuvid.h
export TORCHVISION_LIBRARY=/usr/local/lib:/usr/lib/x86_64-linux-gnu:/usr/local/lib:/usr/local/cuda/lib64 # for libnvcuvid.so
export USE_FFMPEG=1
export _GLIBCXX_USE_CXX11_ABI=1
python setup.py install
cd && rm -rf vision
```

## 4.5 Install torchaudio

<!-- https://blog.csdn.net/ReadyShowShow/article/details/131572199 -->
```bash
cd && git clone --recursive --single-branch --branch v2.3.1 https://github.com/pytorch/audio.git && cd audio
git submodule sync
git submodule update --init --recursive
export USE_CUDA=1
export USE_FFMPEG=1
export USE_OPENMP=1
export FFMPEG_ROOT=/usr/local/
python setup.py install | tee install_torchaudio.log
cd && rm -rf audio
```


# install_env_pllava.md

## 1. Clone base env

```bash
conda create -n pllava --clone clean_pytorch_ffmpeg_build
conda activate pllava
rm ${CONDA_PREFIX}/lib/libffi.7.so ${CONDA_PREFIX}/lib/libffi.so.7 # Fixes ImportError: /lib/x86_64-linux-gnu/libp11-kit.so.0: undefined symbol: ffi_type_pointer, version LIBFFI_BASE_7.0
ln -sf /usr/lib/x86_64-linux-gnu/libstdc++.so.6 ${CONDA_PREFIX}/lib/libstdc++.so.6 # Fixes ImportError: ${CONDA_PREFIX}/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by ${CONDA_PREFIX}/lib/python3.12/site-packages/torch/lib/libtorch_python.so)
export IMAGEIO_FFMPEG_EXE=ffmpeg
# export IMAGEIO_FREEIMAGE_LIB=

# ImageIO without ffmpeg binary (use system ffmpeg)
pip install imageio imageio-ffmpeg --no-binary imageio-ffmpeg

# OpenCV with CUDA support and system ffmpeg
cd && git clone --recursive https://github.com/opencv/opencv-python.git && cd opencv-python
git submodule sync
git submodule update --init --recursive
sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-bad1.0-dev gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 gstreamer1.0-pulseaudio
    #   if(PYTHONLIBS_FOUND)
    #     # Copy outputs
    #     set(_libs_found ${PYTHONLIBS_FOUND})
    #     set(_libraries ${PYTHON_LIBRARIES})
    #     set(_include_path ${PYTHON_INCLUDE_PATH})
    #     set(_include_dirs ${PYTHON_INCLUDE_DIRS})
    #     set(_debug_libraries ${PYTHON_DEBUG_LIBRARIES})
    #     set(_libs_version_string ${PYTHONLIBS_VERSION_STRING})
    #     set(_debug_library ${PYTHON_DEBUG_LIBRARY})
    #     set(_library ${PYTHON_LIBRARY})
    #     set(_library_debug ${PYTHON_LIBRARY_DEBUG})
    #     set(_library_release ${PYTHON_LIBRARY_RELEASE})
    #     set(_include_dir ${PYTHON_INCLUDE_DIR})
    #     set(_include_dir2 ${PYTHON_INCLUDE_DIR2})

export CMAKE_ARGS="-DCMAKE_BUILD_TYPE=RELEASE
    -DWITH_CUBLAS=1
    -DWITH_CUDA=ON
    -DWITH_NVCUVID=ON
    -DWITH_CUDNN=ON
    -DOPENCV_DNN_CUDA=ON
    -DCMAKE_CUDA_ARCHITECTURES=70
    -DOPENCV_ENABLE_NONFREE=ON
    -DENABLE_FAST_MATH=1
    -DCUDA_FAST_MATH=1
    -DOPENCV_EXTRA_MODULES_PATH=${HOME}/opencv-python/opencv_contrib/modules
    -DCUDA_CUDA_LIBRARY=/lib/x86_64-linux-gnu/libcuda.so
    -DCUDA_nvidia-encode_LIBRARY=/usr/local/cuda-12.4/targets/x86_64-linux/lib/libnvidia-encode.so
    -DPYTHON3_LIBRARIES=${CONDA_PREFIX}/lib
    -DPYTHON3_LIBRARY=${CONDA_PREFIX}/lib
    -DPYTHON3_INCLUDE_DIR=${CONDA_PREFIX}/include/python3.12
    -DPYTHON3_INCLUDE_DIRS=${CONDA_PREFIX}/include/python3.12
    -DPYTHON_DEFAULT_EXECUTABLE=${CONDA_PREFIX}/bin/python
    -DPYTHON3_EXECUTABLE=${CONDA_PREFIX}/bin/python
    -DPYTHON3_PACKAGES_PATH=${CONDA_PREFIX}/lib/python3.12/site-packages
    -DPYTHON3_LIMITED_API=OFF
    -DPYTHON3_NUMPY_INCLUDE_DIRS=${CONDA_PREFIX}/lib/python3.12/site-packages/numpy/core/include/numpy
    -DBUILD_PYTHON_SUPPORT=ON \
    -DBUILD_NEW_PYTHON_SUPPORT=ON \
    -DOPENCV_PYTHON3_INSTALL_PATH=${CONDA_PREFIX}/lib/python3.12/site-packages \
    -DPython_NumPy_INCLUDE_DIRS=${CONDA_PREFIX}/lib/python3.12/site-packages/numpy/core/include/numpy
    -DWITH_GSTREAMER=ON"
export CMAKE_ARGS='-DCMAKE_VERBOSE_MAKEFILE=ON'
export VERBOSE=1
# ENABLE_LIBJPEG_TURBO_SIMD
# MKL_WITH_OPENMP
export ENABLE_HEADLESS=1
export ENABLE_CONTRIB=1
sudo ln -s ${CONDA_PREFIX}/lib/python3.12/site-packages/numpy/core/include/numpy /usr/include/numpy
scp ${HOME}/Downloads/Video_Codec_SDK_12.0.16/{Interface/nvEncodeAPI.h,Lib/linux/stubs/x86_64/libnvcuvid.so,Lib/linux/stubs/x86_64/libnvidia-encode.so} c1:~ # NOTE: on laptop
sudo mv ~/nvEncodeAPI.h /usr/local/cuda/include
sudo mv ~/{libnvcuvid.so,libnvidia-encode.so} /usr/local/cuda/lib64
# TODO: remove the version number for setuptools in pyproject.toml
pip wheel . --verbose |& tee install_opencv.log
pip install opencv_contrib_python_headless-*.whl
ldd -r ${CONDA_PREFIX}/lib/python3.12/site-packages/cv2/cv2.abi3.so # Check to see symbols are defined
# pip uninstall opencv_contrib_python_headless

# PyAV without FFMPEG binary (use system ffmpeg)
pip install av --no-binary av

pip install transformers accelerate safetensors peft huggingface_hub
# is imageio already installed?
pip install einops gradio moviepy # For eval
pip install wandb termcolor # Training
pip install -U anthropic[bedrock]

# Install decord

cd && git clone --recursive https://github.com/zhanwenchen/decord && cd decord
git submodule sync
git submodule update --init --recursive
mkdir build && cd build

# Specifying these paths helps avoid stubs
cmake .. \
    -DUSE_CUDA=ON \
    -DCMAKE_CUDA_ARCHITECTURES=70 \
    -DCMAKE_BUILD_TYPE=Release \
    -DCUDA_CUDA_LIBRARY=/lib/x86_64-linux-gnu/libcuda.so \
    -DCUDA_CUDART_LIBRARY=/usr/local/cuda/targets/x86_64-linux/lib/libcudart.so \
    -DCUDA_NVRTC_LIBRARY=/usr/local/cuda/targets/x86_64-linux/lib/libnvrtc.so \
    -DCUDA_CUDNN_LIBRARY=/lib/x86_64-linux-gnu/libcudnn.so \
    -DCUDA_CUBLAS_LIBRARY=/usr/local/cuda/targets/x86_64-linux/lib/libcublas.so \
    -DCUDA_NVIDIA_ML_LIBRARY=/lib/x86_64-linux-gnu/libnvidia-ml.so \
    -DCUDA_NVCUVID_LIBRARY=/lib/x86_64-linux-gnu/libnvcuvid.so

make -j

cd ../python
pip install .


## flash-attn

cd && git clone --single-branch --branch v2.5.9.post1 https://github.com/Dao-AILab/flash-attention.git && cd flash-attention
python setup.py install # Cannot use pip install . on this repo. Also need to specify

```

## Download models

```bash
python python_scripts/hf.py

# curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
# sudo apt install git-lfs
# git lfs install
# git clone https://huggingface.co/ermu2001/pllava-7b # No need - can def
```


## Download data

```bash
# VideoChat
mkdir -p DATAS/TRAIN_TEST

wget https://pjlab-gvm-data.oss-cn-shanghai.aliyuncs.com/videochat2/data/videochat2_conversation_videos.zip
tar -xvf videochat2_conversation_videos.zip

# Video-ChatGPT instruction (removed)
gdown https://drive.google.com/file/d/1Wb0vYuavCoBYos6LXjY5CKfQjU6UqlIi/view?usp=drive_link --fuzzy


```

## Run Demo

```bash
bash scripts/demo.sh
```

## Run Eval

```bash
bash scripts/eval.sh
```

## Run Training

```bash
bash scripts/train_pllava_7b.sh | tee train_pllava_7b.log
```



# reinstall efa

```bash
sudo apt remove ibacm ibverbs-providers ibverbs-utils infiniband-diags libibmad-dev libibmad5 libibumad-dev libibumad3 libibverbs1 rdma-core
```