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Restructure python folders, add basic gym environment and MAPPO (#70)
* Functioning single-agent SB3 PPO implementation. * Add env * Render update and working pygame example. * Restructure * Add basic pygame rgb_array example * Render bug fixes * Rendering progress * Add PPO support for multiple worlds * Cleanup * minor * WIP: benchmark ppo speed * minor * Cleanup * Reformatting and filter out expert obs using boolean mask. * Bug fix: Specify squeeze dim to avoid reducing to a one-dim tensor when using a single world. * Delete data_10 directory * Updated gym env. * Add support for multi-agent PPO * Minor env changes * remove AbsoluteSelfObsTensor and remove whitespaces. * rmv white spaces * rmv * Update render func
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/CMakeSettings.json
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/scripts/__pycache__
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/train_src/madrona_escape_room_learn/__pycache__
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/nocturne_data*
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/waymo_data*
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.vscode/launch.json
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.vscode/settings.json
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.vscode/tasks.json
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/cloudpickle
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/cloudpickle-3.0.0.dist-info
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/bin
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/zipp*
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.python-version
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# Data
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/formatted_json_v2_no_tl_train
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/data_10
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/data_100
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/data_1000
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# Logging
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/wandb
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events.out.tfevents.*
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### C++ ###
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# Prerequisites
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*.d
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# Compiled Object files
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*.slo
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*.lo
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*.o
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*.obj
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# Precompiled Headers
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*.gch
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*.pch
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# Compiled Dynamic libraries
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*.so
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*.dylib
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*.dll
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# Fortran module files
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*.mod
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*.smod
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# Compiled Static libraries
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*.lai
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*.la
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*.a
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*.lib
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# Executables
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*.exe
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*.out
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*.app
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### Python ###
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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### Python Patch ###
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# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
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poetry.toml
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# ruff
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.ruff_cache/
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# LSP config files
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pyrightconfig.json
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# End of https://www.toptal.com/developers/gitignore/api/python,c++

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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.0.1 # Use the latest version
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hooks:
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- id: trailing-whitespace
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- id: end-of-file-fixer
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- id: check-yaml
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- id: check-added-large-files
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- repo: https://github.com/pycqa/flake8
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rev: 3.9.2 # Use the latest version
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hooks:
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- id: flake8
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- repo: https://github.com/psf/black
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rev: 22.3.0 # Use the latest version
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hooks:
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- id: black
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args: [--line-length, "79"]

Diff for: ‎README.md

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If you use Madrona in a research project, please cite our SIGGRAPH paper.
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```
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@article{shacklett23madrona,
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title = {An Extensible, Data-Oriented Architecture for High-Performance, Many-World Simulation},
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author = {Brennan Shacklett and Luc Guy Rosenzweig and Zhiqiang Xie and Bidipta Sarkar and Andrew Szot and Erik Wijmans and Vladlen Koltun and Dhruv Batra and Kayvon Fatahalian},
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journal = {ACM Trans. Graph.},
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volume = {42},
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number = {4},
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year = {2023}
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@article{...,
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}
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```

Diff for: ‎algorithms/__init__.py

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Diff for: ‎algorithms/ppo/sb3/__init__.py

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Diff for: ‎algorithms/ppo/sb3/callbacks.py

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import logging
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import os
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import wandb
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import numpy as np
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import torch
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import torch.nn as nn
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from stable_baselines3.common.callbacks import BaseCallback
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from stable_baselines3.common.policies import ActorCriticPolicy
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class MultiAgentCallback(BaseCallback):
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"""SB3 callback for gpudrive."""
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def __init__(
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self,
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wandb_run=None,
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**kwargs,
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) -> None:
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super().__init__(**kwargs)
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self.wandb_run = wandb_run
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def _on_training_start(self) -> None:
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"""
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This method is called before the first rollout starts.
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"""
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pass
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def _on_rollout_start(self) -> None:
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"""
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A rollout is the collection of environment interaction
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using the current policy.
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This event is triggered before collecting new samples.
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"""
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pass
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def _on_step(self) -> bool:
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"""
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This method will be called by the model after each call to `env.step()`.
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"""
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pass
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def _on_rollout_end(self) -> None:
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"""
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This event is triggered before updating the policy.
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"""
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rewards = self.locals["rollout_buffer"].rewards.cpu().detach().numpy().flatten()
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self.logger.record("rollout/global_step", self.num_timesteps)
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self.logger.record("rollout/avg_reward", np.mean(rewards))
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self.logger.record("rollout/std_reward", np.std(rewards))
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