Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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99 行
3.2 KiB

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