ARG CUDA_VERSION="12.6.3"
ARG CUDNN_VERSION=""
ARG UBUNTU_VERSION="22.04"
ARG MAX_JOBS=4
ARG TARGETARCH

FROM nvidia/cuda:$CUDA_VERSION-cudnn$CUDNN_VERSION-devel-ubuntu$UBUNTU_VERSION AS base-builder

ARG TARGETARCH
ARG PYTHON_VERSION="3.11"
ARG PYTORCH_VERSION="2.6.0"
ARG CUDA="126"
ARG TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 9.0+PTX"

ENV PYTHON_VERSION=$PYTHON_VERSION
ENV TORCH_CUDA_ARCH_LIST=$TORCH_CUDA_ARCH_LIST
ENV UV_TORCH_BACKEND="cu${CUDA}"

RUN apt-get update \
    && apt-get install -y wget git build-essential ninja-build git-lfs libaio-dev pkg-config curl && rm -rf /var/lib/apt/lists/* \
    && git lfs install --skip-repo \
    && curl -LsSf https://astral.sh/uv/install.sh | sh

ENV PATH="/root/.local/bin:${PATH}"

RUN uv python install ${PYTHON_VERSION}

WORKDIR /workspace

RUN uv venv --no-project --relocatable axolotl-venv

ENV PATH="/workspace/axolotl-venv/bin:${PATH}"

RUN uv pip install packaging setuptools wheel psutil \
    && uv pip install torch==${PYTORCH_VERSION} torchvision \
    && uv pip install awscli pydantic

RUN if [ "$TARGETARCH" = "amd64" ]; then \
        MAMBA_SKIP_CUDA_BUILD=TRUE CAUSAL_CONV1D_SKIP_CUDA_BUILD=TRUE uv pip install --no-build-isolation mamba_ssm causal_conv1d; \
    fi