ci

.github/unittest/install_magent2.sh

@@ -0,0 +1,6 @@
+
+pip install "pettingzoo[all]==1.24.3"
+pip install git+https://github.com/Farama-Foundation/MAgent2
+
+sudo apt-get update
+sudo apt-get install python3-opengl xvfb

.github/workflows/magent_tests.yml

@@ -0,0 +1,43 @@
+# This workflow will install Python dependencies, run tests and lint with a single version of Python
+# For more information see:
+# https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+
+name: magent_tests
+
+on:
+  push:
+    branches: [ $default-branch , "main" ]
+  pull_request:
+    branches: [ $default-branch , "main" ]
+
+permissions:
+  contents: read
+
+jobs:
+  tests:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11"]
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+       bash .github/unittest/install_dependencies_nightly.sh
+    - name: Install pettingzoo
+      run: |
+       bash .github/unittest/install_magent2.sh
+    - name: Test with pytest
+      run: |
+        xvfb-run -s "-screen 0 1024x768x24" pytest test/test_magent.py --doctest-modules --junitxml=junit/test-results.xml --cov=. --cov-report=xml --cov-report=html
+    - name: Upload coverage to Codecov
+      uses: codecov/codecov-action@v3
+      with:
+        fail_ci_if_error: false

test/conftest.py

@@ -90,6 +90,31 @@ def mlp_gnn_sequence_config() -> ModelConfig:
     )
 
 
+@pytest.fixture
+def cnn_gnn_sequence_config() -> ModelConfig:
+    return SequenceModelConfig(
+        model_configs=[
+            CnnConfig(
+                cnn_num_cells=[4, 3],
+                cnn_kernel_sizes=[3, 2],
+                cnn_strides=1,
+                cnn_paddings=0,
+                cnn_activation_class=nn.Tanh,
+                mlp_num_cells=[4],
+                mlp_activation_class=nn.Tanh,
+                mlp_layer_class=nn.Linear,
+            ),
+            GnnConfig(
+                topology="full",
+                self_loops=False,
+                gnn_class=torch_geometric.nn.conv.GATv2Conv,
+            ),
+            MlpConfig(num_cells=[4], activation_class=nn.Tanh, layer_class=nn.Linear),
+        ],
+        intermediate_sizes=[5, 3],
+    )
+
+
 @pytest.fixture
 def gru_mlp_sequence_config() -> ModelConfig:
     return SequenceModelConfig(
@@ -128,3 +153,32 @@ def lstm_mlp_sequence_config() -> ModelConfig:
         ],
         intermediate_sizes=[5],
     )
+
+
+@pytest.fixture
+def cnn_lstm_sequence_config() -> ModelConfig:
+    return SequenceModelConfig(
+        model_configs=[
+            CnnConfig(
+                cnn_num_cells=[4, 3],
+                cnn_kernel_sizes=[3, 2],
+                cnn_strides=1,
+                cnn_paddings=0,
+                cnn_activation_class=nn.Tanh,
+                mlp_num_cells=[4],
+                mlp_activation_class=nn.Tanh,
+                mlp_layer_class=nn.Linear,
+            ),
+            LstmConfig(
+                hidden_size=13,
+                mlp_num_cells=[],
+                mlp_activation_class=nn.Tanh,
+                mlp_layer_class=nn.Linear,
+                n_layers=1,
+                bias=True,
+                dropout=0,
+                compile=False,
+            ),
+        ],
+        intermediate_sizes=[5],
+    )

test/test_magent.py

@@ -0,0 +1,135 @@
+#  Copyright (c) Meta Platforms, Inc. and affiliates.
+#
+#  This source code is licensed under the license found in the
+#  LICENSE file in the root directory of this source tree.
+#
+
+
+import pytest
+from benchmarl.algorithms import (
+    algorithm_config_registry,
+    IppoConfig,
+    IsacConfig,
+    MasacConfig,
+    QmixConfig,
+)
+from benchmarl.algorithms.common import AlgorithmConfig
+from benchmarl.environments import MAgentTask, Task
+from benchmarl.experiment import Experiment
+
+from utils import _has_magent2
+from utils_experiment import ExperimentUtils
+
+
+@pytest.mark.skipif(not _has_magent2, reason="magent2 not found")
+class TestMagent:
+    @pytest.mark.parametrize("algo_config", algorithm_config_registry.values())
+    @pytest.mark.parametrize("task", [MAgentTask.ADVERSARIAL_PURSUIT])
+    def test_all_algos(
+        self,
+        algo_config: AlgorithmConfig,
+        task: Task,
+        experiment_config,
+        cnn_sequence_config,
+    ):
+
+        # To not run unsupported algo-task pairs
+        if not algo_config.supports_discrete_actions():
+            pytest.skip()
+
+        task = task.get_from_yaml()
+        experiment = Experiment(
+            algorithm_config=algo_config.get_from_yaml(),
+            model_config=cnn_sequence_config,
+            seed=0,
+            config=experiment_config,
+            task=task,
+        )
+        experiment.run()
+
+    @pytest.mark.parametrize("algo_config", [IppoConfig, QmixConfig, IsacConfig])
+    @pytest.mark.parametrize("task", [MAgentTask.ADVERSARIAL_PURSUIT])
+    def test_gnn(
+        self,
+        algo_config: AlgorithmConfig,
+        task: Task,
+        experiment_config,
+        cnn_gnn_sequence_config,
+    ):
+        task = task.get_from_yaml()
+        experiment = Experiment(
+            algorithm_config=algo_config.get_from_yaml(),
+            model_config=cnn_gnn_sequence_config,
+            critic_model_config=cnn_gnn_sequence_config,
+            seed=0,
+            config=experiment_config,
+            task=task,
+        )
+        experiment.run()
+
+    @pytest.mark.parametrize("algo_config", [IppoConfig, QmixConfig, MasacConfig])
+    @pytest.mark.parametrize("task", [MAgentTask.ADVERSARIAL_PURSUIT])
+    def test_lstm(
+        self,
+        algo_config: AlgorithmConfig,
+        task: Task,
+        experiment_config,
+        cnn_lstm_sequence_config,
+    ):
+        algo_config = algo_config.get_from_yaml()
+        if algo_config.has_critic():
+            algo_config.share_param_critic = False
+        experiment_config.share_policy_params = False
+        task = task.get_from_yaml()
+        experiment = Experiment(
+            algorithm_config=algo_config,
+            model_config=cnn_lstm_sequence_config,
+            critic_model_config=cnn_lstm_sequence_config,
+            seed=0,
+            config=experiment_config,
+            task=task,
+        )
+        experiment.run()
+
+    @pytest.mark.parametrize("algo_config", algorithm_config_registry.values())
+    @pytest.mark.parametrize("task", [MAgentTask.ADVERSARIAL_PURSUIT])
+    def test_reloading_trainer(
+        self,
+        algo_config: AlgorithmConfig,
+        task: Task,
+        experiment_config,
+        cnn_sequence_config,
+    ):
+        # To not run unsupported algo-task pairs
+        if not algo_config.supports_discrete_actions():
+            pytest.skip()
+        algo_config = algo_config.get_from_yaml()
+
+        ExperimentUtils.check_experiment_loading(
+            algo_config=algo_config,
+            model_config=cnn_sequence_config,
+            experiment_config=experiment_config,
+            task=task.get_from_yaml(),
+        )
+
+    @pytest.mark.parametrize("algo_config", [QmixConfig, IppoConfig, MasacConfig])
+    @pytest.mark.parametrize("task", [MAgentTask.ADVERSARIAL_PURSUIT])
+    @pytest.mark.parametrize("share_params", [True, False])
+    def test_share_policy_params(
+        self,
+        algo_config: AlgorithmConfig,
+        task: Task,
+        share_params,
+        experiment_config,
+        cnn_sequence_config,
+    ):
+        experiment_config.share_policy_params = share_params
+        task = task.get_from_yaml()
+        experiment = Experiment(
+            algorithm_config=algo_config.get_from_yaml(),
+            model_config=cnn_sequence_config,
+            seed=0,
+            config=experiment_config,
+            task=task,
+        )
+        experiment.run()

test/utils.py

@@ -10,3 +10,4 @@
 _has_smacv2 = importlib.util.find_spec("smacv2") is not None
 _has_pettingzoo = importlib.util.find_spec("pettingzoo") is not None
 _has_meltingpot = importlib.util.find_spec("meltingpot") is not None
+_has_magent2 = importlib.util.find_spec("magent2") is not None