HumanCompatibleAI / evaluating-rewards

Library to compare and evaluate reward functions
https://arxiv.org/abs/2006.13900
Apache License 2.0
61 stars 7 forks source link

Clean up runners #47

Closed AdamGleave closed 4 years ago

AdamGleave commented 4 years ago

Delete runners/comparison/hardcoded_npec.sh and runners/comparison/learnt.sh which are now redundant with the new scripts.distances.npec.

Delete runners/comparison/hardcoded_epic_sweep.sh and runners/comparison/hardcoded_figs.sh that are non-functional after refactoring the plot_{epic,npec,erc}_heatmap code. These may still be useful as a starting point for similar experiments in the future.

Delete runners/eval/greedy_pm_irl.sh and runners/eval/learnt.sh that are also non-functional but may be useful as a starting point in the future.

Fix runners/eval/greedy_pm_hardcoded.sh and it's Monte Carlo dependents. This is now tested working.

Note irl/train_irl.sh and transfer_point_maze.sh are unlikely to work verbatim, but I intend to address those in separate PRs.

codecov[bot] commented 4 years ago

Codecov Report

Merging #47 into master will increase coverage by 0.04%. The diff coverage is 100.00%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master      #47      +/-   ##
==========================================
+ Coverage   85.10%   85.14%   +0.04%     
==========================================
  Files          65       65              
  Lines        4263     4262       -1     
==========================================
+ Hits         3628     3629       +1     
+ Misses        635      633       -2     
Impacted Files Coverage Δ
src/evaluating_rewards/envs/point_mass.py 83.33% <ø> (ø)
src/evaluating_rewards/policies/monte_carlo.py 0.00% <ø> (ø)
src/evaluating_rewards/__init__.py 100.00% <100.00%> (ø)

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