import os import sys import unittest from pathlib import Path sys.path.append(str(Path(__file__).resolve().parent.parent)) import shutil from rdagent.utils.env import LocalConf, LocalEnv, QlibDockerConf, QTDockerEnv DIRNAME = Path(__file__).absolute().resolve().parent class EnvUtils(unittest.TestCase): def setUp(self): pass def tearDown(self): # NOTE: For a docker file, the output are generated with root permission. # mlrun_p = DIRNAME / "env_tpl" / "mlruns" # if mlrun_p.exists(): # shutil.rmtree(mlrun_p) ... # NOTE: Since I don't know the exact environment in which it will be used, here's just an example. # NOTE: Because you need to download the data during the prepare process. So you need to have pyqlib in your environment. def test_local(self): local_conf = LocalConf( py_bin="/home/v-linlanglv/miniconda3/envs/RD-Agent-310/bin", default_entry="qrun conf.yaml", ) qle = LocalEnv(conf=local_conf) qle.prepare() conf_path = str(DIRNAME / "env_tpl" / "conf.yaml") qle.run(entry="qrun " + conf_path) mlrun_p = DIRNAME / "env_tpl" / "mlruns" self.assertTrue(mlrun_p.exists(), f"Expected output file {mlrun_p} not found") def test_docker(self): """We will mount `env_tpl` into the docker image. And run the docker image with `qrun conf.yaml` """ qtde = QTDockerEnv() qtde.prepare() # you can prepare for multiple times. It is expected to handle it correctly # qtde.run("nvidia-smi") # NOTE: you can check your GPU with this command # the stdout are returned as result result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry="qrun conf.yaml") mlrun_p = DIRNAME / "env_tpl" / "mlruns" self.assertTrue(mlrun_p.exists(), f"Expected output file {mlrun_p} not found") # read experiment result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry="python read_exp_res.py") print(result) def test_docker_mem(self): cmd = 'python -c \'print("start"); import numpy as np; size_mb = 500; size = size_mb * 1024 * 1024 // 8; array = np.random.randn(size).astype(np.float64); print("success")\'' qtde = QTDockerEnv(QlibDockerConf(mem_limit="10m")) qtde.prepare() result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry=cmd) self.assertTrue(not result.strip().endswith("success")) qtde = QTDockerEnv(QlibDockerConf(mem_limit="1g")) qtde.prepare() result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry=cmd) self.assertTrue(result.strip().endswith("success")) # The above command equals to the follow commands with dockr cli.sh # docker run --memory=10m -it --rm local_qlib:latest python -c 'import numpy as np; print(123); size_mb = 1; size = size_mb * 1024 * 1024 // 8; array = np.random.randn(size).astype(np.float64); array[0], array[-1] = 1.0, 1.0; print(321)' # docker run --memory=10g -it --rm local_qlib:latest python -c 'import numpy as np; print(123); size_mb = 1; size = size_mb * 1024 * 1024 // 8; array = np.random.randn(size).astype(np.float64); array[0], array[-1] = 1.0, 1.0; print(321)' if __name__ == "__main__": unittest.main()