Adding Docker Container

Dockerfile

@@ -0,0 +1,15 @@
+ARG base_img_with_tag=pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel
+FROM ${base_img_with_tag} as base
+RUN rm /etc/apt/sources.list.d/cuda.list
+RUN rm /etc/apt/sources.list.d/nvidia-ml.list
+RUN apt-get -y update && apt-get -y install \
+    libxrender1 \
+    libsm6 \
+    libxext6 \
+    libxrender-dev && \
+    apt-get -y clean
+
+RUN conda create -n my-rdkit-env python=3.7
+RUN conda init
+RUN mkdir -p /usr/src/app/rl_graph_generation
+WORKDIR /usr/src/app/rl_graph_generation

Makefile

@@ -0,0 +1,37 @@
+.PHONY: build run_dev_gpu run_dev_no_gpu
+
+base_img_with_tag := pytorch/pytorch:1.11.0-cuda11.3-cudnn8-devel 
+built_img := gcpn
+built_tag := dev
+local_dir := $(shell pwd)
+
+gpu_args := -e USER_ID=$(shell id -u) \
+	-e USER_GP=$(shell id -g) \
+	-e USERNAME=$(shell id -un) \
+	--env NVIDIA_VISIBLE_DEVICES=all \
+	--env NVIDIA_VISIBLE_CAPABILITIES=all \
+	--env="QT_X11_NO_MITSHM=1" \
+	--env="XAUTHORITY=$(XAUTH)" \
+	--volume $(XAUTH):$(XAUTH) \
+	--volume /tmp/.X11-unix:/tmp/.X11-unix \
+
+no_gpu_args := -e USER_ID=$(shell id -u) \
+	-e USER_GP=$(shell id -g) \
+	-e USERNAME=$(shell id -un) \
+	--env="QT_X11_NO_MITSHM=1" \
+	--env="XAUTHORITY=$(XAUTH)" \
+	--volume $(XAUTH):$(XAUTH) \
+	--volume /tmp/.X11-unix:/tmp/.X11-unix \
+
+gpu_container := --gpus all -it --init $(gpu_args)
+no_gpu_container := -it --init $(no_gpu_args)
+
+build:
+	@docker build --build-arg base_img_with_tag=$(base_img_with_tag) . -f Dockerfile --network=host --tag ${built_img}:${built_tag}
+
+
+run_dev_gpu:
+	@docker run -d --net=host $(gpu_container) -v $(local_dir):/usr/src/app/rl_graph_generation $(built_img):$(built_tag)
+
+run_dev_no:
+	@docker run -d --net=host $(no_gpu_container) -v $(local_dir):/usr/src/app/rl_graph_generation ${built_img}:${built_tag}

README.md

@@ -10,20 +10,38 @@ conda create -c rdkit -n my-rdkit-env rdkit
 ```
 - Install mpi4py, networkx:
 ```bash
-conda install mpi4py
-pip install networkx=1.11
+conda install -y mpi4py
+pip install networkx==1.11
+pip install matplotlib==3.5.3
 ```
 - Install OpenAI baseline dependencies:
 ```bash
-cd rl-baselines
-pip install -e .
+pip install -e rl-baselines
 ```
 - Install customized molecule gym environment:
 ```bash
-cd gym-molecule
-pip install -e.
+pip install -e gym-molecule
 ```
 
+## Alternative Install instructions
+For greater reproducibility a `Dockerfile` is provided that can be used to build an environment in which this code simply runs. To use this container environment download and install [Docker](https://www.docker.com/). To more easily reproduce the build and run steps install [Make](https://www.gnu.org/software/make/) and run the recipes provided in the [Makefile](Makefile).
+- To build the Docker container:
+```bash
+make build
+```
+- To run this Docker container with/out a gpu while mounting the project into the running container:
+```bash
+make run_dev_{gpu}
+```
+- Enter the running container:
+```bash
+docker exec -it <container id> bash
+```
+- Activate conda environment and install project dependencies:
+```bash
+conda activate my-rdkit-env
+bash install.sh
+```
 
 ## Code description
 There are 4 important files:

gym-molecule/setup.py

@@ -2,5 +2,5 @@
 
 setup(name='gym-molecule',
       version='0.0.1',
-      install_requires=['gym>=0.2.3', 'pandas']
-      )
+      install_requires=['gym==0.12.0', 'pandas']
+      )

install.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+conda install -y mpi4py
+conda install -y -c rdkit rdkit
+pip install networkx==1.11
+pip install matplotlib==3.5.3
+pip install -e rl-baselines
+pip install -e gym-molecule

rl-baselines/setup.py

@@ -19,7 +19,8 @@
           'progressbar2',
           'mpi4py',
           'cloudpickle',
-          'tensorflow>=1.4.0',
+          'tensorflow==1.13.1',
+          'tensorboardX==2.5.1',
           'click',
       ],
       description='OpenAI baselines: high quality implementations of reinforcement learning algorithms',