Create build-xformers.sh
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#!/bin/bash
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# ONLY USE ON A PAPERSPACE NOTEBOOK
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if [[ -z $1 ]]
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then
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echo -e "You need to set your cuda arch. Go to https://developer.nvidia.com/cuda-gpus and find your GPU.\nThen run this again like this:\n./build-xformers.sh [your cuda arch here]"
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exit
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fi
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# Completly remove cuda from your system
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# The container comes with cuda 11.2 installed which pytorch is incompatable with
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# We MUST install cuda 11.3
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apt update
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apt purge -y cuda*
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apt autoremove --purge -y
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wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004-keyring.gpg -O /usr/share/keyrings/cuda-archive-keyring.gpg
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echo "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg] https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /" | sudo tee /etc/apt/sources.list.d/cuda-ubuntu2004-x86_64.list
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apt update
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apt install -y cuda-command-line-tools-11-3 cuda-compat-11-3 cuda-minimal-build-11-3 cuda-compiler-11-3 cuda-libraries-dev-11-3 cuda-cupti-dev-11-3 cuda-cupti-11-3 cuda-nvcc-11-3 cuda-cudart-dev-11-3 cuda-libraries-11-3 cuda-cudart-11-3 cuda-gdb-11-3 cuda-cuobjdump-11-3 cuda-cuxxfilt-11-3 cuda-driver-dev-11-3 cuda-memcheck-11-3 cuda-nvdisasm-11-3 cuda-nvml-dev-11-3 cuda-nvprof-11-3 cuda-nvprune-11-3 cuda-nvrtc-dev-11-3 cuda-nvrtc-11-3 cuda-nvtx-11-3 cuda-sanitizer-11-3
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# Download xformers source
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cd /notebooks/
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git config --system core.longpaths true
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git clone https://github.com/facebookresearch/xformers.git
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cd /notebooks/xformers
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git submodule update --init --recursive
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# Build xformers
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apt install -y python3.9-venv
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python3 -m venv venv_xformers
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source ./venv_xformers/bin/activate
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pip uninstall -y torch torchvision torchaudio # Remove existing pytorch install.
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pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113 # Install pytorch for cuda 11.3
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pip install setuptools==49.6.0 # This was suggested by anon
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# nvidia-smi -L | perl -lane 'while (/^GPU\s[0-9]+:\s(.*?)\s\(UUID:.*?\)$/g) {printf "%s\n", $1}' # Get your GPU version and set the right cuda arch
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# https://developer.nvidia.com/cuda-gpus
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export TORCH_CUDA_ARCH_LIST=$1
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pip install -r requirements.txt
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pip install -e .
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