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Merge pull request #465 from instadeepai/develop
Feature / Release 0.1.2
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| --- | ||
| name: Investigation | ||
| about: Outline the structure for an investigation. This would commonly be used to measure the impact of various design/implementation choices. | ||
| title: '[INVESTIGATION]' | ||
| labels: investigation | ||
| assignees: '' | ||
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| --- | ||
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| ### What do you want to investigate? | ||
| A brief description of what you would like to investigate. Do you have a hypothesis? | ||
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| ### Definition of done | ||
| A precise outline for the investigation to be considered complete. | ||
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| ### [***Optional***] Results | ||
| <!-- This is added after the investigation is complete. --> | ||
| Results from experiments/derivations. This could be linked to a benchmarking issue. | ||
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| ### What was the conclusion of your investigation? | ||
| <!-- This is added after the investigation is complete. --> | ||
| - What are the findings from the investigation? | ||
| - Was your hypothesis correct? | ||
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| ### [***Optional***] Discussion/Future Investigations | ||
| <!-- This is added after the investigation is complete. --> | ||
| This could be a link to a Github [discussions page](https://github.com/instadeepai/Mava/discussions). | ||
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| <!-- Base checklist. Don’t hesitate to adapt it to your use-case. --> |
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examples/tf/petting_zoo/butterfly/cooperative_pong/feedforward/decentralised/run_mappo.py
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| # python3 | ||
| # Copyright 2021 InstaDeep Ltd. All rights reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| """Example running MAPPO on Cooperative Atari Pong.""" | ||
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| import functools | ||
| from datetime import datetime | ||
| from typing import Any | ||
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| import launchpad as lp | ||
| import numpy as np | ||
| from absl import app, flags | ||
| from acme.tf.networks import AtariTorso | ||
| from supersuit import dtype_v0 | ||
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| from mava.systems.tf import mappo | ||
| from mava.utils import lp_utils | ||
| from mava.utils.environments import pettingzoo_utils | ||
| from mava.utils.loggers import logger_utils | ||
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| FLAGS = flags.FLAGS | ||
| flags.DEFINE_string( | ||
| "env_class", | ||
| "butterfly", | ||
| "Pettingzoo environment class, e.g. atari (str).", | ||
| ) | ||
| flags.DEFINE_string( | ||
| "env_name", | ||
| "cooperative_pong_v3", | ||
| "Pettingzoo environment name, e.g. pong (str).", | ||
| ) | ||
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| flags.DEFINE_string( | ||
| "mava_id", | ||
| str(datetime.now()), | ||
| "Experiment identifier that can be used to continue experiments.", | ||
| ) | ||
| flags.DEFINE_string("base_dir", "~/mava", "Base dir to store experiments.") | ||
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| def main(_: Any) -> None: | ||
| """Run example.""" | ||
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| # Environment | ||
| environment_factory = functools.partial( | ||
| pettingzoo_utils.make_environment, | ||
| env_class=FLAGS.env_class, | ||
| env_name=FLAGS.env_name, | ||
| env_preprocess_wrappers=[(dtype_v0, {"dtype": np.float32})], | ||
| ) | ||
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| # Networks. | ||
| network_factory = lp_utils.partial_kwargs( | ||
| mappo.make_default_networks, observation_network=AtariTorso() | ||
| ) | ||
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| # Checkpointer appends "Checkpoints" to checkpoint_dir | ||
| checkpoint_dir = f"{FLAGS.base_dir}/{FLAGS.mava_id}" | ||
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| # Log every [log_every] seconds. | ||
| log_every = 10 | ||
| logger_factory = functools.partial( | ||
| logger_utils.make_logger, | ||
| directory=FLAGS.base_dir, | ||
| to_terminal=True, | ||
| to_tensorboard=True, | ||
| time_stamp=FLAGS.mava_id, | ||
| time_delta=log_every, | ||
| ) | ||
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| # Distributed program | ||
| program = mappo.MAPPO( | ||
| environment_factory=environment_factory, | ||
| network_factory=network_factory, | ||
| logger_factory=logger_factory, | ||
| num_executors=1, | ||
| checkpoint_subpath=checkpoint_dir, | ||
| num_epochs=5, | ||
| batch_size=32, | ||
| ).build() | ||
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| # Ensure only trainer runs on gpu, while other processes run on cpu. | ||
| local_resources = lp_utils.to_device( | ||
| program_nodes=program.groups.keys(), nodes_on_gpu=["trainer"] | ||
| ) | ||
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| # Launch. | ||
| lp.launch( | ||
| program, | ||
| lp.LaunchType.LOCAL_MULTI_PROCESSING, | ||
| terminal="current_terminal", | ||
| local_resources=local_resources, | ||
| ) | ||
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| if __name__ == "__main__": | ||
| app.run(main) |
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