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111 行
3.7 KiB
111 行
3.7 KiB
import argparse
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import os
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import sys
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import subprocess
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import time
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from .yamato_utils import (
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get_base_path,
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get_base_output_path,
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run_standalone_build,
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init_venv,
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override_config_file,
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override_legacy_config_file,
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checkout_csharp_version,
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undo_git_checkout,
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)
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def run_training(python_version, csharp_version):
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latest = "latest"
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run_id = int(time.time() * 1000.0)
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print(
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f"Running training with python={python_version or latest} and c#={csharp_version or latest}"
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)
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output_dir = "models" if python_version else "results"
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nn_file_expected = f"./{output_dir}/{run_id}/3DBall.nn"
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if os.path.exists(nn_file_expected):
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# Should never happen - make sure nothing leftover from an old test.
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print("Artifacts from previous build found!")
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sys.exit(1)
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base_path = get_base_path()
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print(f"Running in base path {base_path}")
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# Only build the standalone player if we're overriding the C# version
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# Otherwise we'll use the one built earlier in the pipeline.
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if csharp_version is not None:
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# We can't rely on the old C# code recognizing the commandline argument to set the output
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# So rename testPlayer (containing the most recent build) to something else temporarily
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artifact_path = get_base_output_path()
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full_player_path = os.path.join(artifact_path, "testPlayer.app")
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temp_player_path = os.path.join(artifact_path, "temp_testPlayer.app")
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final_player_path = os.path.join(
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artifact_path, f"testPlayer_{csharp_version}.app"
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)
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os.rename(full_player_path, temp_player_path)
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checkout_csharp_version(csharp_version)
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build_returncode = run_standalone_build(base_path)
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if build_returncode != 0:
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print("Standalone build FAILED!")
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sys.exit(build_returncode)
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# Now rename the newly-built executable, and restore the old one
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os.rename(full_player_path, final_player_path)
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os.rename(temp_player_path, full_player_path)
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standalone_player_path = f"testPlayer_{csharp_version}"
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else:
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standalone_player_path = "testPlayer"
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venv_path = init_venv(python_version)
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# Copy the default training config but override the max_steps parameter,
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# and reduce the batch_size and buffer_size enough to ensure an update step happens.
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yaml_out = "override.yaml"
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if python_version:
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overrides = {"max_steps": 100, "batch_size": 10, "buffer_size": 10}
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override_legacy_config_file(
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python_version, "config/trainer_config.yaml", yaml_out, **overrides
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)
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else:
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overrides = {
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"hyperparameters": {"batch_size": 10, "buffer_size": 10},
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"max_steps": 100,
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}
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override_config_file("config/ppo/3DBall.yaml", yaml_out, overrides)
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mla_learn_cmd = (
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f"mlagents-learn {yaml_out} --force --env="
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f"{os.path.join(get_base_output_path(), standalone_player_path)} "
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f"--run-id={run_id} --no-graphics --env-args -logFile -"
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) # noqa
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res = subprocess.run(
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f"source {venv_path}/bin/activate; {mla_learn_cmd}", shell=True
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)
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if res.returncode != 0 or not os.path.exists(nn_file_expected):
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print("mlagents-learn run FAILED!")
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sys.exit(1)
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print("mlagents-learn run SUCCEEDED!")
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sys.exit(0)
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--python", default=None)
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parser.add_argument("--csharp", default=None)
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args = parser.parse_args()
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try:
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run_training(args.python, args.csharp)
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finally:
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# Cleanup - this gets executed even if we hit sys.exit()
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undo_git_checkout()
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if __name__ == "__main__":
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main()
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