Remove bnb multi-source dockerfile

docker/README.md

@@ -6,6 +6,3 @@ Here we store all PEFT Docker images used in our testing infrastructure. We use
 - `peft-gpu`: PEFT complied for NVIDIA GPUs with all other HF libraries installed on main branch
 - `peft-gpu-bnb-source`: PEFT complied for NVIDIA GPUs with `bitsandbytes` and all other HF libraries installed from main branch
 - `peft-gpu-bnb-latest`: PEFT complied for NVIDIA GPUs with `bitsandbytes` complied from main and all other HF libraries installed from latest PyPi
-- `peft-gpu-bnb-multi-source`: PEFT complied for NVIDIA GPUs with `bitsandbytes` complied from `multi-backend` branch and all other HF libraries installed from main branch
-
-`peft-gpu-bnb-source` and `peft-gpu-bnb-multi-source` are essentially the same, with the only difference being `bitsandbytes` compiled on another branch. Make sure to propagate the changes you applied on one file to the other!

docker/peft-gpu-bnb-multi-source/Dockerfile

@@ -1,68 +0,0 @@
-# Builds GPU docker image of PyTorch
-# Uses multi-staged approach to reduce size
-# Stage 1
-# Use base conda image to reduce time
-FROM continuumio/miniconda3:latest AS compile-image
-# Specify py version
-ENV PYTHON_VERSION=3.11
-# Install apt libs - copied from https://github.com/huggingface/accelerate/blob/main/docker/accelerate-gpu/Dockerfile
-RUN apt-get update && \
-    apt-get install -y curl git wget software-properties-common git-lfs && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists*
-
-# Install audio-related libraries 
-RUN apt-get update && \
-    apt install -y ffmpeg
-
-RUN apt install -y libsndfile1-dev
-RUN git lfs install
-
-# Create our conda env - copied from https://github.com/huggingface/accelerate/blob/main/docker/accelerate-gpu/Dockerfile
-RUN conda create --name peft python=${PYTHON_VERSION} ipython jupyter pip
-RUN python3 -m pip install --no-cache-dir --upgrade pip
-
-# Below is copied from https://github.com/huggingface/accelerate/blob/main/docker/accelerate-gpu/Dockerfile
-# We don't install pytorch here yet since CUDA isn't available
-# instead we use the direct torch wheel
-ENV PATH /opt/conda/envs/peft/bin:$PATH
-# Activate our bash shell
-RUN chsh -s /bin/bash
-SHELL ["/bin/bash", "-c"]
-
-# Stage 2
-FROM nvidia/cuda:12.4.1-devel-ubuntu22.04 AS build-image
-COPY --from=compile-image /opt/conda /opt/conda
-ENV PATH /opt/conda/bin:$PATH
-
-RUN chsh -s /bin/bash
-SHELL ["/bin/bash", "-c"]
-
-# Install apt libs
-RUN apt-get update && \
-    apt-get install -y curl git wget cmake && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists*
-
-# Activate the conda env and install transformers + accelerate from source
-# Also clone BNB and build it from source.
-RUN source activate peft && \
-    python3 -m pip install -U --no-cache-dir \
-    librosa \
-    "soundfile>=0.12.1" \
-    scipy \
-    git+https://github.com/huggingface/transformers \
-    git+https://github.com/huggingface/accelerate \
-    peft[test]@git+https://github.com/huggingface/peft \
-    optimum \
-    auto-gptq && \
-    git clone https://github.com/TimDettmers/bitsandbytes && cd bitsandbytes && git checkout multi-backend-refactor && \
-    cmake -B . -DCOMPUTE_BACKEND=cuda -S . && \
-    cmake --build . && \
-    pip install -e . && \ 
-    pip freeze | grep bitsandbytes
-
-RUN echo "source activate peft" >> ~/.profile
-
-# Activate the virtualenv
-CMD ["/bin/bash"]