udpate

finetune/Dockerfile

@@ -1,3 +1,9 @@
+# syntax=docker/dockerfile:1
+
+# NOTE: Building this image require's docker version >= 23.0.
+#
+# For reference:
+# - https://docs.docker.com/build/dockerfile/frontend/#stable-channel
 ARG CUDA_VERSION=12.1.0
 FROM nvidia/cuda:${CUDA_VERSION}-cudnn8-devel-ubuntu20.04
 ARG DEBIAN_FRONTEND="noninteractive"
@@ -105,7 +111,7 @@ ENV _GLIBCXX_USE_CXX11_ABI=${_GLIBCXX_USE_CXX11_ABI}
 RUN <<EOT
 #!/bin/bash
 source /opt/conda/etc/profile.d/conda.sh
-conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} pyyaml ipython -c conda-forge -y
+conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} -c conda-forge -y
 echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc
 conda activate ${CONDA_ENV_NAME}
 # 克隆 ninja 源码并编译
@@ -121,7 +127,7 @@ conda run -n ${CONDA_ENV_NAME} bash -c "CXXFLAGS='-pthread' LDFLAGS='-pthread' p
 # 运行 Ninja 单元测试
 ./ninja_test
 python3 -m pip install --no-cache-dir --upgrade pip
-python -m pip install open_clip_torch nvidia-ml-py3 opencv-contrib-python 
+python3 -m pip install open_clip_torch nvidia-ml-py3 opencv-contrib-python 
 conda clean -afy 
 git clone https://github.com/huggingface/transformers && cd transformers && git checkout $REF && cd ..
 python -m pip install setuptools==${SETUPTOOLS_VERSION}

finetune/Dockerfile.conda

@@ -1,3 +1,9 @@
+# syntax=docker/dockerfile:1
+
+# NOTE: Building this image require's docker version >= 23.0.
+#
+# For reference:
+# - https://docs.docker.com/build/dockerfile/frontend/#stable-channel
 ARG CUDA_VERSION=12.1.0
 FROM nvidia/cuda:${CUDA_VERSION}-cudnn8-devel-ubuntu20.04
 ARG DEBIAN_FRONTEND="noninteractive"
@@ -81,6 +87,8 @@ ENV NV_PEER_MEM_VERSION=1.2
 ENV NV_PEER_MEM_TAG=${NV_PEER_MEM_VERSION}-0
 ENV OPENMPI_BASEVERSION=4.1
 ENV OPENMPI_VERSION=${OPENMPI_BASEVERSION}.6
+ARG CUDA_NUM='121'
+ENV CUDA_NUM=${CUDA_NUM}
 ARG CUDA='cu121'
 ENV CUDA=${CUDA}
 ARG PYTORCH_VERSION=2.3.0
@@ -91,6 +99,9 @@ ARG TORCHAUDIO_VERSION=2.3.0
 ENV TORCHAUDIO_VERSION=${TORCHAUDIO_VERSION}
 ARG PYTORCH_CUDA_VERSION=12.1
 ENV PYTORCH_CUDA_VERSION=${PYTORCH_CUDA_VERSION}
+ENV TORCH_CUDA_ARCH_LIST="7.0 7.2 7.5 8.0 8.6 8.7 8.9 9.0 9.0a"
+ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
+ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
 ENV MLNX_OFED_VERSION=4.9-7.1.0.0
 ARG SETUPTOOLS_VERSION=69.5.1
 ENV SETUPTOOLS_VERSION=${SETUPTOOLS_VERSION}
@@ -105,7 +116,7 @@ ENV _GLIBCXX_USE_CXX11_ABI=${_GLIBCXX_USE_CXX11_ABI}
 RUN <<EOT
 #!/bin/bash
 source /opt/conda/etc/profile.d/conda.sh
-conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} pyyaml ipython cmake ninja -c conda-forge -y
+conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} cmake ninja -c conda-forge -y
 echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc
 conda activate ${CONDA_ENV_NAME}
 python3 -m pip install --no-cache-dir --upgrade pip
@@ -120,11 +131,14 @@ python3 -m pip uninstall -y torch torchvision torchaudio
 # # install pytorch create conda env aleay exists
 git clone --recursive https://github.com/pytorch/pytorch ${STAGE_DIR}/pytorch
 cd ${STAGE_DIR}/pytorch
+git checkout v${PYTORCH_VERSION}
 git submodule sync
 git submodule update --init --recursive
 pip install -r requirements.txt
+conda install -y intel::mkl-static intel::mkl-include
+conda install -y -c pytorch magma-cuda${CUDA_NUM}
 export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
-python setup.py develop
+python setup.py install
 # python3 -m pip install torch==${PYTORCH_VERSION}+${CUDA} torchvision==${TORCHVISION_VERSION}+${CUDA} torchaudio==${TORCHAUDIO_VERSION} --extra-index-url https://download.pytorch.org/whl/${CUDA}
 python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
 python3 -m pip uninstall -y transformer-engine

finetune/Dockerfile.conda1

@@ -0,0 +1,372 @@
+# syntax=docker/dockerfile:1
+
+# NOTE: Building this image requires Docker version >= 23.0.
+#
+# For reference:
+# - https://docs.docker.com/build/dockerfile/frontend/#stable-channel
+
+ARG CUDA_VERSION=12.1.0
+FROM nvidia/cuda:${CUDA_VERSION}-cudnn8-devel-ubuntu20.04
+ARG DEBIAN_FRONTEND="noninteractive"
+ENV DEBIAN_FRONTEND=${DEBIAN_FRONTEND}
+ENV MAMBA_ROOT_PREFIX=~/micromamba
+ARG ROOT_PASSWD="root"
+ENV ROOT_PASSWD=${ROOT_PASSWD}
+WORKDIR /root
+SHELL ["/bin/bash", "-c"]
+
+# Base tools
+RUN <<EOT
+apt-get update
+apt-get install -y wget curl htop jq vim bash libaio-dev build-essential openssh-server python3 python3-pip
+apt-get install -y --no-install-recommends software-properties-common build-essential autotools-dev nfs-common pdsh cmake g++ gcc curl wget vim tmux emacs less unzip htop iftop iotop ca-certificates openssh-client openssh-server rsync iputils-ping net-tools sudo llvm-dev re2c
+add-apt-repository ppa:git-core/ppa -y
+apt-get install -y git libnuma-dev wget
+sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
+sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config
+sed -i 's/PubkeyAuthentication no/PubkeyAuthentication yes/' /etc/ssh/sshd_config
+sed -i 's/^#Port 22/Port 22/' /etc/ssh/sshd_config
+sed -i 's/^Port [0-9]*/Port 22/' /etc/ssh/sshd_config
+mkdir /var/run/sshd
+echo 'root:${ROOT_PASSWD}' | chpasswd
+mkdir -p ~/.pip
+wget -qO- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh
+bash /tmp/miniconda.sh -b -p /opt/conda 
+rm /tmp/miniconda.sh 
+conda init bash 
+ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh
+echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc 
+cat <<EOF > ~/.condarc
+channels:
+  - conda-forge
+  - bioconda
+  - pytorch
+  - pytorch-nightly
+  - nvidia
+  - defaults
+show_channel_urls: true
+EOF
+echo 1 | bash <(curl -s https://cdn.jsdelivr.net/gh/hotwa/MicroMamba_Installer@main/install.sh)
+micromamba shell init -s bash -p ~/micromamba
+cat <<'EOF' >> ~/.bashrc
+source ~/micromamba/etc/profile.d/micromamba.sh
+alias mamba=micromamba
+alias mba=mamba
+EOF
+cat <<EOF > ~/.mambarc
+channels:
+  - conda-forge
+  - bioconda
+  - pytorch
+  - pytorch-nightly
+  - nvidia
+  - defaults
+show_channel_urls: true
+EOF
+EOT
+
+# PyTorch
+ARG CONDA_ENV_NAME="deepspeed"
+ENV CONDA_ENV_NAME=${CONDA_ENV_NAME}
+ARG PYTHON_VERSION=3.10
+ENV PYTHON_VERSION=${PYTHON_VERSION}
+ENV PATH /opt/conda/bin:/opt/conda/envs/${CONDA_ENV_NAME}/bin:$PATH
+ARG PYTORCH_VERSION=2.3.0
+ENV PYTORCH_VERSION=${PYTORCH_VERSION}
+ENV TORCH_CUDA_ARCH_LIST="7.0 7.2 7.5 8.0 8.6 8.7 8.9 9.0 9.0a"
+ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
+ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
+ARG CUDA_NUM='121'
+ENV CUDA_NUM=${CUDA_NUM}
+
+RUN <<EOT
+source /opt/conda/etc/profile.d/conda.sh
+conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} cmake ninja -c conda-forge -y
+echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc
+conda activate ${CONDA_ENV_NAME}
+python3 -m pip install --no-cache-dir --upgrade pip
+conda clean -afy 
+
+# 获取指定版本的 PyTorch 源代码
+git clone --recursive https://github.com/pytorch/pytorch ${STAGE_DIR}/pytorch
+cd ${STAGE_DIR}/pytorch
+git checkout v${PYTORCH_VERSION}
+git submodule sync
+git submodule update --init --recursive
+
+# 安装依赖项
+conda install -y intel::mkl-static intel::mkl-include
+conda install -y -c pytorch magma-cuda${CUDA_NUM}
+
+# 构建和安装 PyTorch
+export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
+python setup.py install
+
+# 安装其他必要的依赖项
+python -m pip install open_clip_torch nvidia-ml-py3 opencv-contrib-python 
+python -m pip install setuptools==69.5.1
+python3 -m pip install --no-cache-dir ./transformers[deepspeed-testing]
+python3 -m pip uninstall -y torch torchvision torchaudio 
+python3 -m pip install torch==${PYTORCH_VERSION}+${CUDA} torchvision==0.18.0+${CUDA} torchaudio==2.3.0 --extra-index-url https://download.pytorch.org/whl/${CUDA}
+python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
+python3 -m pip uninstall -y transformer-engine
+python3 -m pip uninstall -y torch-tensorrt
+python3 -m pip uninstall -y apex
+EOT
+
+# install apex
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+git clone https://github.com/NVIDIA/apex ${STAGE_DIR}/apex
+cd apex
+# if pip >= 23.1 (ref: https://pip.pypa.io/en/stable/news/#v23-1) which supports multiple `--config-settings` with the same key... 
+MAX_JOBS=1 python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./
+python -c "import apex.amp; print('Apex is installed and the amp module is available.')"
+cd ..
+rm -rf ${STAGE_DIR}/apex
+EOT
+
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+# Pre-build **latest** DeepSpeed, so it would be ready for testing (otherwise, the 1st deepspeed test will timeout)
+python3 -m pip uninstall -y deepspeed
+# This has to be run (again) inside the GPU VMs running the tests.
+# The installation works here, but some tests fail, if we do not pre-build deepspeed again in the VMs running the tests.
+# TODO: Find out why test fail. install deepspeed
+# DS_BUILD_CPU_ADAM=${DS_BUILD_CPU_ADAM} DS_BUILD_FUSED_ADAM={DS_BUILD_FUSED_ADAM} python3 -m pip install "deepspeed<=0.14.0" --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
+# from https://github.com/huggingface/transformers/blob/main/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile install deepspeed fail 
+# reference deepspeed install from https://github.com/microsoft/DeepSpeed/blob/master/docker/Dockerfile
+# install deepspeed prepare
+# install Mellanox OFED
+mkdir -p ${STAGE_DIR}
+wget -q -O - http://www.mellanox.com/downloads/ofed/MLNX_OFED-${MLNX_OFED_VERSION}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu20.04-x86_64.tgz | tar xzf -
+cd MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu20.04-x86_64 
+./mlnxofedinstall --user-space-only --without-fw-update --all -q 
+cd ${STAGE_DIR} 
+rm -rf ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu20.04-x86_64*
+cd ..
+# install nv_peer_mem
+rm -rf ${STAGE_DIR}
+mkdir -p ${STAGE_DIR}
+git clone https://github.com/Mellanox/nv_peer_memory.git --branch ${NV_PEER_MEM_TAG} ${STAGE_DIR}/nv_peer_memory
+cd ${STAGE_DIR}/nv_peer_memory
+./build_module.sh
+cd ${STAGE_DIR}
+tar xzf ${STAGE_DIR}/nvidia-peer-memory_${NV_PEER_MEM_VERSION}.orig.tar.gz
+cd ${STAGE_DIR}/nvidia-peer-memory-${NV_PEER_MEM_VERSION}
+apt-get update
+apt-get install -y dkms
+dpkg-buildpackage -us -uc
+dpkg -i ${STAGE_DIR}/nvidia-peer-memory_${NV_PEER_MEM_TAG}_all.deb
+EOT
+
+# install mpi
+ENV PATH=/usr/local/mpi/bin:${PATH} 
+ENV LD_LIBRARY_PATH=/usr/local/lib:/usr/local/mpi/lib:/usr/local/mpi/lib64:${LD_LIBRARY_PATH}
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+# OPENMPI
+rm -rf ${STAGE_DIR}
+mkdir -p ${STAGE_DIR}
+cd ${STAGE_DIR}
+wget -q -O - https://download.open-mpi.org/release/open-mpi/v${OPENMPI_BASEVERSION}/openmpi-${OPENMPI_VERSION}.tar.gz | tar xzf - 
+cd openmpi-${OPENMPI_VERSION} 
+./configure --prefix=/usr/local/openmpi-${OPENMPI_VERSION} 
+make -j"$(nproc)" install 
+ln -s /usr/local/openmpi-${OPENMPI_VERSION} /usr/local/mpi 
+# Sanity check:
+test -f /usr/local/mpi/bin/mpic++ 
+cd ${STAGE_DIR} 
+rm -r ${STAGE_DIR}/openmpi-${OPENMPI_VERSION}
+# Create a wrapper for OpenMPI to allow running as root by default
+mv /usr/local/mpi/bin/mpirun /usr/local/mpi/bin/mpirun.real
+echo '#!/bin/bash' > /usr/local/mpi/bin/mpirun
+echo 'mpirun.real --allow-run-as-root --prefix /usr/local/mpi "$@"' >> /usr/local/mpi/bin/mpirun
+chmod a+x /usr/local/mpi/bin/mpirun
+EOT
+
+# Some Packages
+RUN <<EOT
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+apt-get update 
+apt-get install -y --no-install-recommends libsndfile-dev libcupti-dev libjpeg-dev libpng-dev screen libaio-dev
+python -m pip install https://github.com/mpi4py/mpi4py/tarball/master
+python -m pip install psutil \
+yappi \
+cffi \
+ipdb \
+pandas \
+matplotlib \
+py3nvml \
+pyarrow \
+graphviz \
+astor \
+boto3 \
+tqdm \
+sentencepiece \
+msgpack \
+requests \
+pandas \
+sphinx \
+sphinx_rtd_theme \
+scipy \
+numpy \
+scikit-learn \
+nvidia-ml-py3
+EOT
+
+# SSH daemon port inside container cannot conflict with host OS port
+ENV SSH_PORT=2222
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+cat /etc/ssh/sshd_config > ${STAGE_DIR}/sshd_config && \
+sed "0,/^Port 22/s//Port ${SSH_PORT}/" ${STAGE_DIR}/sshd_config > /etc/ssh/sshd_config
+EOT
+
+# 29.78 Usage: install.sh [options...]
+# 29.78 
+# 29.78 By default will install deepspeed and all third party dependencies across all machines listed in
+# 29.78 hostfile (hostfile: /job/hostfile). If no hostfile exists, will only install locally
+# 29.78 
+# 29.78 [optional]
+# 29.78     -l, --local_only        Install only on local machine
+# 29.78     -s, --pip_sudo          Run pip install with sudo (default: no sudo)
+# 29.78     -r, --allow_sudo        Allow script to be run by root (probably don't want this, instead use --pip_sudo)
+# 29.78     -n, --no_clean          Do not clean prior build state, by default prior build files are removed before building wheels
+# 29.78     -m, --pip_mirror        Use the specified pip mirror (default: the default pip mirror)
+# 29.78     -H, --hostfile          Path to MPI-style hostfile (default: /job/hostfile)
+# 29.78     -e, --examples          Checkout deepspeed example submodule (no install)
+# 29.78     -v, --verbose           Verbose logging
+# 29.78     -h, --help              This help text
+
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+useradd --create-home --uid 1000 --shell /bin/bash deepspeed
+usermod -aG sudo deepspeed
+echo "deepspeed ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers
+EOT
+
+# install cutlass https://github.com/NVIDIA/cutlass
+# H100: architecture is Hopper (cutlass need add : cmake .. -DCUTLASS_NVCC_ARCHS="90a" )
+# A100: architecture is Ampere 
+# V100: architecture is Volta 
+# T4: architecture is Turing 
+# ENV CUDACXX=${CUDA_INSTALL_PATH}/bin/nvcc
+# 70：适用于 NVIDIA Volta 架构（如 Tesla V100）。
+# 75：适用于 NVIDIA Turing 架构（如 Tesla T4）。
+# 80：适用于 NVIDIA Ampere 架构（如 A100）。
+# 90a：适用于 NVIDIA Hopper 架构（如 H100）。
+# 89:GeForce RTX 4090 
+ARG DCUTLASS_NVCC_ARCHS="89"
+ENV DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS}
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+git clone https://github.com/NVIDIA/cutlass /opt/cutlass
+cd /opt/cutlass
+git checkout . 
+git checkout master
+mkdir build
+cd build
+cmake .. -DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS} -DCUTLASS_ENABLE_TESTS=OFF -DCUTLASS_UNITY_BUILD_ENABLED=ON            # compiles for NVIDIA Hopper GPU architecture, like H100
+make -j"$(nproc)" install
+cd ..
+# make test_unit -j"$(nproc)"
+# make test_unit_gemm_warp -j"$(nproc)"
+EOT
+
+# CUDA_ARCH_LIST="80;86;89;90"
+ARG DEEPSPEED_INSTALL_FLAGS="--allow_sudo --pip_sudo --no_clean"
+ENV DEEPSPEED_INSTALL_FLAGS=${DEEPSPEED_INSTALL_FLAGS}
+ARG CUDA_ARCH_LIST="80;86;89;90"
+ENV CUDA_ARCH_LIST=${CUDA_ARCH_LIST}
+ARG DS_BUILD_SPARSE_ATTN=0
+ENV DS_BUILD_SPARSE_ATTN=${DS_BUILD_SPARSE_ATTN}
+ARG DS_BUILD_FUSED_ADAM=1
+ENV DS_BUILD_FUSED_ADAM=${DS_BUILD_FUSED_ADAM}
+ARG DS_BUILD_CPU_ADAM=0
+ENV DS_BUILD_CPU_ADAM=${DS_BUILD_CPU_ADAM}
+ARG DS_BUILD_OPS=1
+ENV DS_BUILD_OPS=${DS_BUILD_OPS}
+ENV CUTLASS_PATH=/opt/cutlass
+# install deepspeed
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+python -m pip install setuptools==${SETUPTOOLS_VERSION}
+# install oneapi for deepspeed
+git clone https://github.com/oneapi-src/oneCCL.git ${STAGE_DIR}/oneCCL
+cd ${STAGE_DIR}/oneCCL
+git checkout . 
+git checkout master
+mkdir build
+cd build 
+cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local
+make -j install
+git clone https://github.com/microsoft/DeepSpeed-Kernels.git ${STAGE_DIR}/DeepSpeed-Kernels
+cd ${STAGE_DIR}/DeepSpeed-Kernels
+CUDA_ARCH_LIST=${CUDA_ARCH_LIST} python setup.py bdist_wheel
+# pip install dist/deepspeed_kernels-*.whl
+CUDA_ARCH_LIST=${CUDA_ARCH_LIST} pip install -v .
+git clone https://github.com/microsoft/DeepSpeed.git ${STAGE_DIR}/DeepSpeed
+cd ${STAGE_DIR}/DeepSpeed 
+git checkout . 
+git checkout master 
+python setup.py bdist_wheel
+DS_BUILD_OPS=${DS_BUILD_OPS} pip install dist/deepspeed*.whl --force-reinstall
+# DS_BUILD_OPS=${DS_BUILD_OPS} pip install -r requirements/requirements.txt
+# DS_BUILD_OPS=0 DS_BUILD_SPARSE_ATTN=0 DS_BUILD_CPU_ADAM=0 DS_BUILD_FUSED_ADAM=1 pip install -U --no-cache-dir .
+# ./install.sh ${DEEPSPEED_INSTALL_FLAGS} --hostfile /job/hostfile # ./install.sh --allow_sudo --pip_sudo --no_clean --hostfile /path/to/your/hostfile
+cd ..
+# rm -rf ${STAGE_DIR}/DeepSpeed
+EOT
+
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+# install transformers
+git clone https://github.com/huggingface/transformers ${STAGE_DIR}/transformers
+cd ${STAGE_DIR}/transformers
+python3 ./setup.py develop
+python3 -m pip install -U --no-cache-dir "pydantic<2"
+# install flash-attn
+# pip install packaging -i https://pypi.org/simple/ --trusted-host pypi.org
+pip install flash-attn --no-build-isolation -i https://pypi.org/simple/ --trusted-host pypi.org
+EOT
+
+RUN <<EOT
+#!/bin/bash
+source /opt/conda/etc/profile.d/conda.sh
+conda activate ${CONDA_ENV_NAME}
+pip install optimum
+pip install peft tiktoken \
+    tqdm matplotlib seaborn numpy pandas scikit-learn diffusers \
+    huggingface_hub spacy blobfile pycocotools \
+    xformers open_clip_torch \
+    zstandard -i https://pypi.org/simple/ --trusted-host pypi.org
+EOT
+
+# add vscode server
+# RUN <<EOT
+# #!/bin/bash
+# wget -qO- https://update.code.visualstudio.com/commit:${commit_id}/server-linux-x64/stable
+# code-server --install-extension ms-python.vscode-pylance
+# EOT
+
+# 启动 ssh 服务
+# CMD ["/bin/bash", "-c", "service ssh start; tail -f /dev/null"]
+CMD ["/usr/sbin/sshd", "-D"]

finetune/docker-compose_pytorch1.13.yml

@@ -12,7 +12,7 @@ services:
         TORCHVISION_VERSION: 0.14.1
         TORCHAUDIO_VERSION: 0.13.1
         DS_BUILD_OPS: 1
-        DS_BUILD_SPARSE_ATTN: 0
+        DS_BUILD_SPARSE_ATTN: 1
         DS_BUILD_FUSED_ADAM: 1
         DS_BUILD_CPU_ADAM: 1
         USE_CUDA: 1

finetune/docker-compose_pytorch1.13_conda.yml

@@ -4,7 +4,7 @@ services:
   ubuntu-finetune:
     build: 
       context: .
-      dockerfile: Dockerfile.conda
+      dockerfile: Dockerfile.conda1
       args: # PyTorch版本、Python版本与pytorch_lightning版本的对应关系表 https://blog.csdn.net/qq_41813454/article/details/137421822
         PYTHON_VERSION: 3.9 # sparse attion 最新支持到3.9
         CUDA_VERSION: 11.7.1 # pytorch 1.13.1 对应cuda 11.7.1
@@ -18,6 +18,7 @@ services:
         USE_CUDA: 1
         USE_ROCM: 0
         USE_XPU: 0
+        CUDA_NUM: 117
         CUDA: cu117
         CUDA_ARCH_LIST: "80;86;89;90" # for RTX 4090, all : "80;86;89;90"
         SETUPTOOLS_VERSION: "69.5.1"

finetune/docker-compose_pytorch2.3_conda.yml

@@ -21,7 +21,7 @@ services:
       args: # PyTorch版本、Python版本与pytorch_lightning版本的对应关系表 https://blog.csdn.net/qq_41813454/article/details/137421822
         PYTHON_VERSION: 3.9
         CUDA_VERSION: 12.1.0
-        PYTORCH_VERSION: 2.3.0
+        PYTORCH_VERSION: 2.3.1
         TORCHVISION_VERSION: 0.18.0
         TORCHAUDIO_VERSION: 2.3.0
         DS_BUILD_OPS: 1