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jysgro/rfdiffusion

By jysgro

•Updated over 2 years ago

v1.1.0 RFdiffusion from https://github.com/RosettaCommons/RFdiffusion **with** models included

Image
Data science
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jysgro/rfdiffusion repository overview

⁠v1.1.0 RFdiffusion

from https://github.com/RosettaCommons/RFdiffusion⁠

Notes: Docker file included on the repository had to be modified for the following reasons:

  1. Built on an M1 Silicon Mac, hence need to specify ubuntu platform in FROM --platform=linux/amd64
  2. Requirement torch==1.12.1+cu116 could not be honored (reported as "does not exists") and replaced with torch>=1.12.1+cu116 (hence it is unclear which exact version was installed.) For this reason the longer RUN command was split in two sections.
  3. Due to the torch version above, a new requirement appeared to need to install package nvtx.
  4. All other rfdiffusion container found on this site have an ENTRYPOINT which makes it more difficult to use on a Linux cluster using HTCondor. Hence this was removed to provide more flexibility.
  5. The models listed in the github repository README file obtained by command with wget http://files.ipd.uw.edu/pub/RFdiffusion/ ETC. are missing in all other containers listed on this site. As such there is a complaint when trying to run them: FileNotFoundError: [Errno 2] No such file or directory: '/usr/local/lib/python3.9/dist-packages/rfdiffusion/inference/../../models/Base_ckpt.pt' To remedy this problem the models were made available at this location by symlink (See Dockerfile below.)

⁠Docker file for TAG py39_cu116_pt11x

Here is the Docker file used to create this Docker images:

# Usage: 
# git clone https://github.com/RosettaCommons/RFdiffusion.git
# cd RFdiffusion
# docker build -f docker/Dockerfile -t rfdiffusion .
# mkdir $HOME/inputs $HOME/outputs $HOME/models
# bash scripts/download_models.sh $HOME/models
# wget -P $HOME/inputs https://files.rcsb.org/view/5TPN.pdb

# docker run -it --rm --gpus all \
#   -v $HOME/models:$HOME/models \
#   -v $HOME/inputs:$HOME/inputs \
#   -v $HOME/outputs:$HOME/outputs \
#   rfdiffusion \
#   inference.output_prefix=$HOME/outputs/motifscaffolding \
#   inference.model_directory_path=$HOME/models \
#   inference.input_pdb=$HOME/inputs/5TPN.pdb \
#   inference.num_designs=3 \
#   'contigmap.contigs=[10-40/A163-181/10-40]'

FROM --platform=linux/amd64 nvcr.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04

COPY . /app/RFdiffusion/

RUN apt-get -q update \ 
  && DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y \
  git \
  python3.9 \
  python3-pip \
  && python3.9 -m pip install -q -U --no-cache-dir pip \
  && rm -rf /var/lib/apt/lists/* \
  && apt-get autoremove -y \
  && apt-get clean 

 RUN  pip install -q --no-cache-dir \
  dgl==1.0.2+cu116 -f https://data.dgl.ai/wheels/cu116/repo.html \
  torch>=1.12.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116 \
  e3nn==0.3.3 \
  wandb==0.12.0 \
  pynvml==11.0.0 \
  git+https://github.com/NVIDIA/dllogger#egg=dllogger \
  decorator==5.1.0 \
  hydra-core==1.3.2 \
  pyrsistent==0.19.3 \
  /app/RFdiffusion/env/SE3Transformer \
  && pip install --no-cache-dir /app/RFdiffusion --no-deps
  
 RUN pip install -q --no-cache-dir nvtx

# RUN mv /app/RFdiffusion/models /usr/local/lib/python3.9/dist-packages/rfdiffusion/inference/../../
RUN ln -s /app/RFdiffusion/models /usr/local/lib/python3.9/dist-packages/rfdiffusion/inference/../../models

WORKDIR /app/RFdiffusion

ENV DGLBACKEND="pytorch"

#ENTRYPOINT ["python3.9", "scripts/run_inference.py"]

Tag summary

Content type

Image

Digest

sha256:8ef27ff91…

Size

4.2 GB

Last updated

over 2 years ago

docker pull jysgro/rfdiffusion:1.12.1_cu116_nvtx