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# Prepping your environment # | |
# 1. Set up WSL with ffmpeg: https://streaminglearningcenter.com/encoding/running-ffmpeg-on-windows-subsystem-for-linux.html | |
# 2. Install Miniconda in your WSL environment: https://dev.to/sfpear/miniconda-in-wsl-3642 | |
# 3. Install Python packages: | |
# pip uninstall ffmpeg | |
# pip uninstall ffmpeg-python | |
# pip install ffmpeg-python git+https://github.com/SYSTRAN/faster-whisper | |
# 4. [IF YOU HAVE A COMPATIBLE NVIDIA GPU] Install all CUDA stuff, which can be painful | |
# The instructions in this section should work clean: https://github.com/SYSTRAN/faster-whisper?tab=readme-ov-file#install-with-pip-linux-only | |
# But it might be easiest to use the Docker image. |
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call plug#begin() | |
Plug 'brooth/far.vim' | |
Plug 'SirVer/ultisnips' | |
Plug 'honza/vim-snippets' | |
Plug 'scrooloose/nerdtree' " file list | |
Plug 'majutsushi/tagbar' " show tags in a bar (functions etc) for easy browsing | |
Plug 'vim-airline/vim-airline' " make statusline awesome |
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echo "deb https://apt.repos.intel.com/mkl all main" > /etc/apt/sources.list.d/intel-mkl.list && \ | |
echo "deb https://apt.repos.intel.com/tbb all main" > /etc/apt/sources.list.d/intel-tbb.list && \ | |
echo "deb https://apt.repos.intel.com/daal all main" > /etc/apt/sources.list.d/intel-daal.list && \ | |
echo "deb https://apt.repos.intel.com/mpi all main" > /etc/apt/sources.list.d/intel-mpi.list && \ | |
apt-get update | |
## Set a bunch of envvars (perhaps throw these in your bashrc) | |
MKL_LIB_PATH="/opt/intel/compilers_and_libraries/linux/mkl/lib/intel64_lin" \ | |
MKL="-L/opt/intel/compilers_and_libraries/linux/mkl/lib/intel64_lin -Wl,--no-as-needed -lmkl_gf_lp64 -Wl,--start-group -lmkl_gnu_thread -lmkl_cdft_core -lmkl_core -Wl,--end-group -fopenmp -ldl -lpthread -lm" \ |
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