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