load_model.py

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"""
example of how to load a model and keep training for timesteps_total steps
"""

from marllib import marl

# prepare the environment
env = marl.make_env(environment_name="mpe", map_name="simple_spread", force_coop=True)

# initialize algorithm and load hyperparameters
mappo = marl.algos.mappo(hyperparam_source="mpe")

# build agent model based on env + algorithms + user preference if checked available
model = marl.build_model(env, mappo, {"core_arch": "mlp", "encode_layer": "128-256"})

# rendering
mappo.render(env, model,
             stop={'timesteps_total': 40000000},
             restore_path={'params_path': "checkpoint/params.json",  # experiment configuration
                           'model_path': "checkpoint/checkpoint-6250"},  # checkpoint path
             num_workers=10,
             local_mode=False,
             share_policy="all",
             checkpoint_end=True)