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[Version] 1.2.0 (#80)
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benchmarl/__init__.py

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#
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__version__ = "1.1.1"
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__version__ = "1.2.0"
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import importlib
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docs/source/conf.py

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"python": ("https://docs.python.org/3/", None),
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"sphinx": ("https://www.sphinx-doc.org/en/master/", None),
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"torch": ("https://pytorch.org/docs/master", None),
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"torchrl": ("https://pytorch.org/rl", None),
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"tensordict": ("https://pytorch.org/tensordict", None),
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"torchrl": ("https://pytorch.org/rl/stable/", None),
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"tensordict": ("https://pytorch.org/tensordict/stable", None),
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}
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intersphinx_disabled_domains = ["std"]
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docs/source/usage/installation.rst

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Install BenchMARL
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-----------------
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You can just install it from github
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You can just install it from PyPi
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.. code-block:: console
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Install environments
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--------------------
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All enviornment dependencies are optional in BenchMARL and can be installed separately.
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All environment dependencies are optional in BenchMARL and can be installed separately.
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VMAS
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^^^^

setup.py

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url="https://github.com/facebookresearch/BenchMARL",
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author="Matteo Bettini",
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author_email="[email protected]",
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install_requires=["torchrl>=0.3.1", "tqdm", "hydra-core"],
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install_requires=["torchrl==0.4.0", "tqdm", "hydra-core"],
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extras_require={
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"vmas": ["vmas>=1.3.4"],
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"pettingzoo": ["pettingzoo[all]>=1.24.3"],

test/test_meltingpot.py

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#
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import packaging
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import pytest
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import torchrl
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from benchmarl.algorithms import (
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algorithm_config_registry,
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@pytest.mark.skipif(not _has_meltingpot, reason="Meltingpot not found")
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@pytest.mark.skipif(
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packaging.version.parse(torchrl.__version__).base_version <= "0.3.1",
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reason="TorchRL <= 0.3.1 does nto support meltingpot",
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)
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class TestMeltingPot:
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@pytest.mark.parametrize("algo_config", algorithm_config_registry.values())
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@pytest.mark.parametrize("task", [MeltingPotTask.COMMONS_HARVEST__OPEN])

test/test_models.py

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from typing import List
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import packaging
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import pytest
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import torch
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import torchrl
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from benchmarl.hydra_config import load_model_config_from_hydra
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from benchmarl.models import model_config_registry
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pytest.skip() # this combination should never happen
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if ("gnn" in model_name) and centralised:
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pytest.skip("gnn model is always decentralized")
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if (
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packaging.version.parse(torchrl.__version__).base_version <= "0.3.1"
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and "cnn" in model_name
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):
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pytest.skip("TorchRL <= 0.3.1 does not support MultiAgentCNN")
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torch.manual_seed(0)
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