Docker 빌드 시 자주 쓸만한거 FlowSE용

FROM nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1
ENV PIP_NO_CACHE_DIR=1

RUN apt-get update && apt-get install -y \
    python3 python3-pip python3-dev \
    git wget curl vim tmux \
    build-essential cmake ninja-build \
    libsndfile1 libsndfile1-dev ffmpeg \
    && rm -rf /var/lib/apt/lists/*

RUN python3 -m pip install --upgrade pip setuptools wheel

RUN pip3 install \
    torch==2.1.2 \
    torchvision==0.16.2 \
    torchaudio==2.1.2 \
    --index-url https://download.pytorch.org/whl/cu121

RUN pip3 install \
    pytorch-lightning==1.6.5.post0 \
    soundfile==0.13.1 \
    torch-ema==0.3 \
    torch-pesq==0.1.2 \
    torchelastic==0.2.2 \
    torchmetrics==0.9.3 \
    torchtyping==0.1.5 \
    wandb==0.13.10

WORKDIR /workspace

CMD ["/bin/bash"]

FlowSE 를 위한 도커파일임

S. Lee, S. Cheong, S. Han, and J. W. Shin,
“FlowSE: Flow Matching-based Speech Enhancement,”
in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
Hyderabad, India, 2025, pp. 1-5,
doi: 10.1109/ICASSP49660.2025.10888274.

@INPROCEEDINGS{10888274,
author={Lee, Seonggyu and Cheong, Sein and Han, Sangwook and Shin, Jong Won},
booktitle={ICASSP 2025 – 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={FlowSE: Flow Matching-based Speech Enhancement},
year={2025},
doi={10.1109/ICASSP49660.2025.10888274}
}

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