mirror of
https://github.com/google-deepmind/alphafold3.git
synced 2025-10-20 13:23:47 +08:00
72 lines
3.7 KiB
Docker
72 lines
3.7 KiB
Docker
# Copyright 2024 DeepMind Technologies Limited
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#
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# AlphaFold 3 source code is licensed under CC BY-NC-SA 4.0. To view a copy of
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# this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/
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#
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# To request access to the AlphaFold 3 model parameters, follow the process set
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# out at https://github.com/google-deepmind/alphafold3. You may only use these
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# if received directly from Google. Use is subject to terms of use available at
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# https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md
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FROM nvidia/cuda:12.6.3-base-ubuntu24.04
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# Some RUN statements are combined together to make Docker build run faster.
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# Get latest package listing, install python, git, wget, compilers and libs.
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# * git is required for pyproject.toml toolchain's use of CMakeLists.txt.
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# * gcc, g++, make are required for compiling HMMER and AlphaFold 3 libaries.
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# * zlib is a required dependency of AlphaFold 3.
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RUN DEBIAN_FRONTEND=noninteractive \
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apt-get update --quiet \
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&& apt-get install --yes --quiet python3.12 python3-pip python3.12-venv python3.12-dev \
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&& apt-get install --yes --quiet git wget gcc g++ make zlib1g-dev zstd
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# The base image uses Python 3.12. For local installation use 3.11 or greater.
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RUN python3 -m venv /alphafold3_venv
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ENV PATH="/hmmer/bin:/alphafold3_venv/bin:$PATH"
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# Update pip to the latest version. Not necessary in Docker, but good to do when
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# this is used as a recipe for local installation since we rely on new pip
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# features for secure installs.
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RUN pip3 install --no-cache-dir --upgrade pip
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# Install HMMER. Do so before copying the source code, so that docker can cache
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# the image layer containing HMMER. Alternatively, you could also install it
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# using `apt-get install hmmer` instead of bulding it from source, but we want
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# to have control over the exact version of HMMER. Also note that eddylab.org
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# unfortunately doesn't support HTTPS and the tar file published on GitHub is
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# explicitly not recommended to be used for building from source.
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RUN mkdir /hmmer_build /hmmer ; \
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wget http://eddylab.org/software/hmmer/hmmer-3.4.tar.gz --directory-prefix /hmmer_build ; \
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(cd /hmmer_build && echo "ca70d94fd0cf271bd7063423aabb116d42de533117343a9b27a65c17ff06fbf3 hmmer-3.4.tar.gz" | sha256sum --check) && \
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(cd /hmmer_build && tar zxf hmmer-3.4.tar.gz && rm hmmer-3.4.tar.gz) ; \
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(cd /hmmer_build/hmmer-3.4 && ./configure --prefix /hmmer) ; \
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(cd /hmmer_build/hmmer-3.4 && make -j) ; \
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(cd /hmmer_build/hmmer-3.4 && make install) ; \
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(cd /hmmer_build/hmmer-3.4/easel && make install) ; \
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rm -R /hmmer_build
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# Copy the AlphaFold 3 source code from the local machine to the container and
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# set the working directory to there.
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COPY . /app/alphafold
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WORKDIR /app/alphafold
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# Install setuptools (removed in Python 3.12) which some libraries still need.
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# Then install the Python dependencies of AlphaFold 3.
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RUN pip3 install --no-cache-dir setuptools \
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&& pip3 install --no-cache-dir -r dev-requirements.txt \
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&& pip3 install --no-cache-dir --no-deps .
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# Build chemical components database (this binary was installed by pip).
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RUN build_data
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# To work around a known XLA issue causing the compilation time to greatly
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# increase, the following environment variable setting XLA flags must be enabled
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# when running AlphaFold 3. Note that if using CUDA capability 7 GPUs, it is
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# necessary to set the following XLA_FLAGS value instead:
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# ENV XLA_FLAGS="--xla_disable_hlo_passes=custom-kernel-fusion-rewriter"
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# (no need to disable gemm in that case as it is not supported for such GPU).
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ENV XLA_FLAGS="--xla_gpu_enable_triton_gemm=false"
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# Memory settings used for folding up to 5,120 tokens on A100 80 GB.
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ENV XLA_PYTHON_CLIENT_PREALLOCATE=true
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ENV XLA_CLIENT_MEM_FRACTION=0.95
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CMD ["python3", "run_alphafold.py"]
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