Setting up an ML envronment can be a tricky thing. Here’s what worked for me on how to set up the environment and keep track of experiments.

Project Setup

Directory Structure

Cookiecuttet

Computational Environment

  1. Pycharm
  2. virtualenv
  3. pip install the packages:

  • [1] Unzip the downloaded mjpro150 into ~/.mujoco/mjpro150, and place the mjkey.txt file at ~/.mujoco/mjkey.txt.

  • [2] Run pip3 install -U 'mujoco-py<1.50.2,>=1.50.1'

  • [3] Remove ~/.mujoco/mjpro150/bin/libglfw.3.dylib

  • [4] Run brew install llvm boost hdf5 glfw

  • [5] Add

export PATH="/usr/local/opt/llvm/bin:$PATH"
export CC="/usr/local/opt/llvm/bin/clang"
export CXX="/usr/local/opt/llvm/bin/clang++"
export CXX11="/usr/local/opt/llvm/bin/clang++"
export CXX14="/usr/local/opt/llvm/bin/clang++"
export CXX17="/usr/local/opt/llvm/bin/clang++"
export CXX1X="/usr/local/opt/llvm/bin/clang++"
export LDFLAGS="-L/usr/local/opt/llvm/lib"
export CPPFLAGS="-I/usr/local/opt/llvm/include"

to .zshrc and source ~/.zshrc

  • [6] Run pip install -U 'mujoco-py<1.50.2,>=1.50.1'

  • [7] Run python3 -c 'import mujoco_py'

  • [8] Run pip install 'gym[all]'

Experiments

  1. Hyperparameters
  2. Description
  3. Performance on benchmarking tasks

Preparing for publishing

  1. README
  2. Add packages to requirements.txt pip freeze > requirements.txt
  3. Source code
  4. Visualizations