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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82 行
2.5 KiB

import os
import subprocess
import yaml
def get_unity_executable_path():
UNITY_VERSION = os.environ["UNITY_VERSION"]
BOKKEN_UNITY = f"/Users/bokken/{UNITY_VERSION}/Unity.app/Contents/MacOS/Unity"
HUB_UNITY = (
f"/Applications/Unity/Hub/Editor/{UNITY_VERSION}/Unity.app/Contents/MacOS/Unity"
)
if os.path.exists(BOKKEN_UNITY):
return BOKKEN_UNITY
if os.path.exists(HUB_UNITY):
return HUB_UNITY
raise FileNotFoundError("Can't find bokken or hub executables")
def get_base_path():
# We might need to do some more work here if the working directory ever changes
# E.g. take the full path and back out the main module main.
# But for now, this should work
return os.getcwd()
def run_standalone_build(base_path: str, verbose: bool = False) -> int:
"""
Run BuildStandalonePlayerOSX test to produce a player at Project/testPlayer
:param base_path:
:return:
"""
unity_exe = get_unity_executable_path()
print(f"Running BuildStandalonePlayerOSX via {unity_exe}")
test_args = [
unity_exe,
"-projectPath",
f"{base_path}/Project",
"-batchmode",
"-executeMethod",
"MLAgents.StandaloneBuildTest.BuildStandalonePlayerOSX",
]
if verbose:
test_args += ["-logfile", "-"]
print(f"{' '.join(test_args)} ...")
timeout = 30 * 60 # 30 minutes, just in case
res: subprocess.CompletedProcess = subprocess.run(test_args, timeout=timeout)
return res.returncode
def init_venv():
# Set up the venv and install mlagents
subprocess.check_call("python -m venv venv", shell=True)
pip_commands = [
"--upgrade pip",
"--upgrade setuptools",
# TODO build these and publish to internal pypi
"~/tensorflow_pkg/tensorflow-2.0.0-cp37-cp37m-macosx_10_14_x86_64.whl",
"-e ./ml-agents-envs",
"-e ./ml-agents",
]
for cmd in pip_commands:
subprocess.check_call(
f"source venv/bin/activate; python -m pip install -q {cmd}", shell=True
)
def override_config_file(src_path, dest_path, **kwargs):
"""
Override settings in a trainer config file. For example,
override_config_file(src_path, dest_path, max_steps=42)
will copy the config file at src_path to dest_path, but override the max_steps field to 42 for all brains.
"""
with open(src_path) as f:
configs = yaml.safe_load(f)
for config in configs.values():
config.update(**kwargs)
with open(dest_path, "w") as f:
yaml.dump(configs, f)