BabyAI experiments, license, coc, contributing

BabyAI experiments

COC, Contributing and License

Add link to license in README

CODE_OF_CONDUCT.md

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+# Code of Conduct
+
+Facebook has adopted a Code of Conduct that we expect project participants to adhere to.
+Please read the [full text](https://code.fb.com/codeofconduct/)
+so that you can understand what actions will and will not be tolerated

CONTRIBUTING.md

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+# Contributing to modeling_long_term_future
+We want to make contributing to this project as easy and transparent as
+possible.
+
+## Our Development Process
+... (in particular how this is synced with internal changes to the project)
+
+## Pull Requests
+We actively welcome your pull requests.
+
+1. Fork the repo and create your branch from `master`.
+2. If you've added code that should be tested, add tests.
+3. If you've changed APIs, update the documentation.
+4. Ensure the test suite passes.
+5. Make sure your code lints.
+6. If you haven't already, complete the Contributor License Agreement ("CLA").
+
+## Contributor License Agreement ("CLA")
+In order to accept your pull request, we need you to submit a CLA. You only need
+to do this once to work on any of Facebook's open source projects.
+
+Complete your CLA here: <https://code.facebook.com/cla>
+
+## Issues
+We use GitHub issues to track public bugs. Please ensure your description is
+clear and has sufficient instructions to be able to reproduce the issue.
+
+Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe
+disclosure of security bugs. In those cases, please go through the process
+outlined on that page and do not file a public issue.
+
+
+## License
+By contributing to modeling_long_term_future, you agree that your contributions will be licensed
+under the LICENSE file in the root directory of this source tree.

LICENSE

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README.md

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+This repo contains code for our paper [Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future](https://arxiv.org/abs/1903.01599)
+
+The code base contains multiple branches.
+
+- The main branch contains experiments for the BabyAI tasks.
+- The mujoco branch contains experiments for the Mujoco tasks.
+
+Based on code base for the BabyAI project at Mila. https://github.com/mila-iqia/babyai
+
+Follow similar installations as in https://github.com/mila-iqia/babyai.
+
+
+Requirements:
+## Installation
+
+Requirements:
+- Python 3.5+
+- OpenAI Gym
+- NumPy
+- PyQT5
+- PyTorch 0.4.1+
+
+Start by manually installing PyTorch. See the [PyTorch website](http://pytorch.org/)
+for installation instructions specific to your platform.
+
+Then, clone this repository and install the other dependencies with `pip3`:
+
+    git clone https://github.com/nke001/iclr_babyai
+    cd babyai
+    pip3 install --editable .
+
+Create a new conda env using env.yml in the repo
+
+## Training teacher
+
+We use the BabyAI Pickup-Unlock game.
+
+First train the teacher (for imitation learning) using PPO with curriculum learning. Start with a room size of 6 and then work our way up to room size of 15.
+
+
+    python3 -m scripts.train_curclm. --env BabyAI-UnlockPickup-v0  --algo ppo   --arch cnn1 --tb --seed 1 --save-interval 10 --room-size 6
+    python3 -m scripts.train_curclm. --env BabyAI-UnlockPickup-v0  --algo ppo   --arch cnn1 --tb --seed 1 --save-interval 10 --room-size 8 --model MODEL_ROOM6_PRETRAINED
+    python3 -m scripts.train_curclm. --env BabyAI-UnlockPickup-v0  --algo ppo   --arch cnn1 --tb --seed 1 --save-interval 10 --room-size 10 --model MODEL_ROOM8_PRETRAINED
+    python3 -m scripts.train_curclm. --env BabyAI-UnlockPickup-v0  --algo ppo   --arch cnn1 --tb --seed 1 --save-interval 10 --room-size 12 --model MODEL_ROOM10_PRETRAINED
+    python3 -m scripts.train_curclm. --env BabyAI-UnlockPickup-v0  --algo ppo   --arch cnn1 --tb --seed 1 --save-interval 10 --room-size 15 --model MODEL_ROOM12_PRETRAINED
+
+
+## Generate expert trajectories
+
+Generate expert trajectories from the experts trained using curriculum learning
+
+    mnkdir data
+    python3 -m scripts.gen_samples --episodes 10000 --env BabyAI-UnlockPickup-v0 --model pretrained_model_room_10 --room 10
+
+
+## Training the student to imitate the expert
+
+To run our model
+
+    python3 -m scripts.zforcing_main_state_dec --env BabyAI-UnlockPickup-v0 --datafile EXPERT_DATA_TO_LOAD --model MODEL_NAME --eval-episodes 100 --eval-interval 200  --bwd-weight 0.0 --lr 1e-4 --aux-weight-start 0.0001 --bwd-l2-weight 1. --kld-weight-start 0.2  --aux-weight-end 0.0001  --room 10
+
+
+To run the baseline
+
+    python3 -m scripts.zforcing_main_state_dec --datafile EXPERT_DATA_TO_LOAD --env BabyAI-UnlockPickup-v0 --model MODEL_NAME --eval-episodes 100 --eval-interval 200  --bwd-weight 0.0 --lr 1e-4 --aux-weight-start 0.000 --aux-weight-end 0.0 --room 10
+
+
+## License
+
+Find license in [LICENSE](LICENSE) file.

babyai/__init__.py

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+# Import levels so that the OpenAI Gym environments get registered
+# when the babyai package is imported
+from . import levels
+from . import utils

babyai/levels/__init__.py

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+from .levels import level_dict