def test_run_local_minimum_conf():
batches_data_dir = tempfile.mkdtemp(prefix="hyperctl-test-batches")
config_dict = {
"jobs": [{
"params": {
"learning_rate": 0.1
},
"execution": {
"command": "pwd"
}
}],
"daemon": {
'exit_on_finish': True,
'port': 8063
}
}
print("Config:")
print(config_dict)
daemon.run_batch(config_dict, batches_data_dir)
executor_manager = get_context().executor_manager
batch = get_context().batch
batch_name = batch.name
jobs_name = [j.name for j in batch.jobs]
assert isinstance(executor_manager, LocalExecutorManager)
assert_batch_finished(batch, batch_name, jobs_name,
ShellJob.STATUS_SUCCEED)
assert_local_job_succeed(batch.jobs)
def test_run_local():
batches_data_dir = tempfile.mkdtemp(prefix="hyperctl-test-batches")
job_name0 = "eVqNV5Uo0"
job_name1 = "eVqNV5Uo1"
batch_name = "eVqNV5Ut"
local_example_script = Path(
"hypernets/tests/hyperctl/local-example-script.py").absolute()
print(local_example_script)
config_dict = {
"jobs": [{
"name": job_name0,
"params": {
"learning_rate": 0.1
},
"resource": {
"cpu": 2
},
"execution": {
"command": f"{sys.executable} {local_example_script}",
"working_dir": "/tmp"
}
}, {
"name": job_name1,
"params": {
"learning_rate": 0.1
},
"resource": {
"cpu": 2
},
"execution": {
"command": f"{sys.executable} {local_example_script}",
"working_dir": "/tmp",
}
}],
"backend": {
"type": "local",
"conf": {}
},
"name":
batch_name,
"daemon": {
"port": 8061,
"exit_on_finish": True
},
"version":
2.5
}
print("Config:")
print(config_dict)
daemon.run_batch(config_dict, batches_data_dir)
executor_manager = get_context().executor_manager
assert isinstance(executor_manager, LocalExecutorManager)
assert_batch_finished(get_context().batch, batch_name,
[job_name0, job_name1], ShellJob.STATUS_SUCCEED)
def test_run_remote():
job1_name = "eVqNV5Uo1"
job2_name = "eVqNV5Uo2"
batch_name = "eVqNV5Ut"
jobs_data_dir = tempfile.mkdtemp(prefix="hyperctl-test-jobs")
config_dict = {
"jobs": [{
"name": job1_name,
"params": {
"learning_rate": 0.1
},
"resource": {},
"execution": {
"command": "sleep 3",
"working_dir": "/tmp",
"data_dir": jobs_data_dir
}
}, {
"name": job2_name,
"params": {
"learning_rate": 0.1
},
"resource": {},
"execution": {
"command": "sleep 3",
"working_dir": "/tmp",
"data_dir": jobs_data_dir
}
}],
"backend": {
"type": "remote",
"conf": {
"machines":
ssh_utils_test.get_ssh_test_config(use_password=True,
use_rsa_file=False)
}
},
"name":
batch_name,
"daemon": {
"port": 8060,
"exit_on_finish": True
},
"version":
2.5
}
batches_data_dir = tempfile.mkdtemp(prefix="hyperctl-test-batches")
daemon.run_batch(config_dict, batches_data_dir)
executor_manager = get_context().executor_manager
batch = get_context().batch
assert isinstance(executor_manager, RemoteSSHExecutorManager)
assert len(executor_manager.machines) == 2
assert_batch_finished(batch, batch_name, [job1_name, job2_name],
ShellJob.STATUS_SUCCEED)
def post(self, job_name, operation, **kwargs):
# job_name
# request_body = self.get_request_as_dict()
if operation not in [self.OPT_KILL]:
raise ValueError(f"unknown operation {operation} ")
# checkout job
job: ShellJob = dao.get_job_by_name(job_name)
if job is None:
raise ValueError(f'job {job_name} does not exists ')
if operation == self.OPT_KILL: # do kill
logger.debug(
f"trying kill job {job_name}, it's status is {job.status} ")
# check job status
if job.status != job.STATUS_RUNNING:
raise RuntimeError(
f"job {job_name} in not in {job.STATUS_RUNNING} status but is {job.status} "
)
# find executor and close
em: RemoteSSHExecutorManager = get_context().executor_manager
executor = em.get_executor(job)
logger.debug(f"find executor {executor} of job {job_name}")
if executor is not None:
em.kill_executor(executor)
logger.debug(f"write failed status file for {job_name}")
dao.change_job_status(job, job.STATUS_FAILED)
self.response({"msg": f"{job.name} killed"})
else:
raise ValueError(f"no executor found for job {job.name}")
def test_kill_local_job():
batches_data_dir = tempfile.mkdtemp(prefix="hyperctl-test-batches")
job_name = "eVqNV5Uo0"
batch_name = "eVqNV5Ut"
daemon_port = 8062
config_dict = {
"jobs": [{
"name": job_name,
"params": {
"learning_rate": 0.1
},
"resource": {},
"execution": {
"command": "sleep 8",
"working_dir": "/tmp"
}
}],
"backend": {
"type": "local",
"conf": {}
},
"name":
batch_name,
"daemon": {
"port": daemon_port,
"exit_on_finish": True
},
"version":
2.5
}
def send_kill_request():
time.sleep(6)
runtime.kill_job(f'http://localhost:{daemon_port}', job_name)
_thread.start_new_thread(send_kill_request, ())
print("Config:")
print(config_dict)
daemon.run_batch(config_dict, batches_data_dir)
batch = get_context().batch
assert_batch_finished(get_context().batch, batch_name, [job_name],
ShellJob.STATUS_FAILED)
assert_local_job_finished(batch.jobs)
def _make_run_shell_content(self):
# default http://localhost:8060
vars = {
consts.KEY_ENV_JOB_DATA_DIR: self.job.job_data_dir,
consts.KEY_ENV_JOB_NAME: self.job.name,
consts.KEY_ENV_JOB_EXECUTION_WORKING_DIR:
self.job.execution.working_dir, # default value
consts.KEY_TEMPLATE_COMMAND: self.job.execution.command,
consts.KEY_ENV_DAEMON_PORTAL:
get_context().batch.daemon_conf.portal,
}
run_shell = str(consts.RUN_SH_TEMPLATE)
for k, v in vars.items():
run_shell = run_shell.replace(f"#{k}#", v)
return run_shell
def schedule(self):
c = get_context()
executor_manager = c.executor_manager
jobs = c.batch.jobs
# check all jobs finished
job_finished = c.batch.is_finished()
if job_finished:
batch_summary = json.dumps(c.batch.summary())
logger.info("all jobs finished, stop scheduler:\n" + batch_summary)
self._timer.stop() # stop the timer
if self.exit_on_finish:
logger.info("stop ioloop")
ioloop.IOLoop.instance().stop()
return
self._check_executors(executor_manager)
self._dispatch_jobs(executor_manager, jobs)
def run(self):
# check remote host setting
daemon_host = get_context().batch.daemon_conf.host
if consts.HOST_LOCALHOST == daemon_host:
logger.warning(
"recommended that set IP address that can be accessed in remote machines, "
"but now it's \"localhost\", and the task executed on the remote machines "
"may fail because it can't get information from the daemon server,"
" you can set it in `daemon.host` ")
# create remote data dir
execution_data_dir = Path(self.job.execution.data_dir).as_posix()
with ssh_utils.sftp_client(**self.connections) as sftp_client:
logger.debug(f"create remote job data dir {execution_data_dir} ")
ssh_utils.makedirs(sftp_client, execution_data_dir)
# create run shell file
fd_run_file, run_file = tempfile.mkstemp(
prefix=f'hyperctl_run_{self.job.name}_', suffix='.sh')
os.close(fd_run_file)
self._write_run_shell_script(run_file)
# copy file to remote
with ssh_utils.sftp_client(**self.connections) as sftp_client:
logger.debug(f'upload {run_file} to {self.job.run_file_path}')
sftp_client: SFTPClient = sftp_client
ssh_utils.copy_from_local_to_remote(sftp_client, run_file,
self.job.run_file_path)
# execute command in async
self._command_ssh_client = ssh_utils.create_ssh_client(
**self.connections)
command = f'sh {self.job.run_file_path}'
logger.debug(f'execute command {command}')
self._remote_process = self._command_ssh_client.exec_command(
command, get_pty=True)
def get_job_by_name(job_name):
for job in get_context().batch.jobs:
if job.name == job_name:
return job
return None
def get_jobs():
return get_context().batch.jobs
