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import atexit
import logging
from pathlib import Path
import socket
from subprocess import Popen
import time
from typing import Optional, Union, List, overload, Any
import json_tricks
import colorama
import psutil
import nni.runtime.log
from .config import ExperimentConfig, AlgorithmConfig
from .data import TrialJob, TrialMetricData, TrialResult
from . import launcher
from . import management
from . import rest
from ..tools.nnictl.command_utils import kill_command
_logger = logging.getLogger('nni.experiment')
class Experiment:
"""
Create and stop an NNI experiment.
Attributes
----------
config
Experiment configuration.
port
Web UI port of the experiment, or `None` if it is not running.
"""
@overload
def __init__(self, config: ExperimentConfig) -> None:
"""
Prepare an experiment.
Use `Experiment.run()` to launch it.
Parameters
----------
config
Experiment configuration.
"""
...
@overload
def __init__(self, training_service: Union[str, List[str]]) -> None:
"""
Prepare an experiment, leaving configuration fields to be set later.
Example usage::
experiment = Experiment('remote')
experiment.config.trial_command = 'python3 trial.py'
experiment.config.machines.append(RemoteMachineConfig(ip=..., user_name=...))
...
experiment.run(8080)
Parameters
----------
training_service
Name of training service.
Supported value: "local", "remote", "openpai", "aml", "kubeflow", "frameworkcontroller", "adl" and hybrid training service.
"""
...
def __init__(self, config=None, training_service=None):
nni.runtime.log.init_logger_experiment()
self.config: Optional[ExperimentConfig] = None
self.id: Optional[str] = None
self.port: Optional[int] = None
self._proc: Optional[Popen] = None
self.mode = 'new'
args = [config, training_service] # deal with overloading
if isinstance(args[0], (str, list)):
self.config = ExperimentConfig(args[0])
self.config.tuner = AlgorithmConfig(name='_none_', class_args={})
self.config.assessor = AlgorithmConfig(name='_none_', class_args={})
self.config.advisor = AlgorithmConfig(name='_none_', class_args={})
else:
self.config = args[0]
def start(self, port: int = 8080, debug: bool = False) -> None:
"""
Start the experiment in background.
This method will raise exception on failure.
If it returns, the experiment should have been successfully started.
Parameters
----------
port
The port of web UI.
debug
Whether to start in debug mode.
"""
atexit.register(self.stop)
if self.mode == 'new':
self.id = management.generate_experiment_id()
else:
self.config = launcher.get_stopped_experiment_config(self.id, self.mode)
if self.config.experiment_working_directory is not None:
log_dir = Path(self.config.experiment_working_directory, self.id, 'log')
else:
log_dir = Path.home() / f'nni-experiments/{self.id}/log'
nni.runtime.log.start_experiment_log(self.id, log_dir, debug)
self._proc = launcher.start_experiment(self.id, self.config, port, debug, mode=self.mode)
assert self._proc is not None
self.port = port # port will be None if start up failed
ips = [self.config.nni_manager_ip]
for interfaces in psutil.net_if_addrs().values():
for interface in interfaces:
if interface.family == socket.AF_INET:
ips.append(interface.address)
ips = [f'http://{ip}:{port}' for ip in ips if ip]
msg = 'Web UI URLs: ' + colorama.Fore.CYAN + ' '.join(ips) + colorama.Style.RESET_ALL
_logger.info(msg)
def stop(self) -> None:
"""
Stop background experiment.
"""
_logger.info('Stopping experiment, please wait...')
atexit.unregister(self.stop)
if self.id is not None:
nni.runtime.log.stop_experiment_log(self.id)
if self._proc is not None:
try:
rest.delete(self.port, '/experiment')
except Exception as e:
_logger.exception(e)
_logger.warning('Cannot gracefully stop experiment, killing NNI process...')
kill_command(self._proc.pid)
self.id = None
self.port = None
self._proc = None
_logger.info('Experiment stopped')
def run(self, port: int = 8080, wait_completion: bool = True, debug: bool = False) -> bool:
"""
Run the experiment.
If wait_completion is True, this function will block until experiment finish or error.
Return `True` when experiment done; or return `False` when experiment failed.
Else if wait_completion is False, this function will non-block and return None immediately.
"""
self.start(port, debug)
if wait_completion:
try:
while True:
time.sleep(10)
status = self.get_status()
if status == 'DONE' or status == 'STOPPED':
return True
if status == 'ERROR':
return False
except KeyboardInterrupt:
_logger.warning('KeyboardInterrupt detected')
finally:
self.stop()
@classmethod
def connect(cls, port: int):
"""
Connect to an existing experiment.
Parameters
----------
port
The port of web UI.
"""
experiment = Experiment()
experiment.port = port
experiment.id = experiment.get_experiment_profile().get('id')
status = experiment.get_status()
pid = experiment.get_experiment_metadata(experiment.id).get('pid')
if pid is None:
_logger.warning('Get experiment pid failed, can not stop experiment by stop().')
else:
experiment._proc = psutil.Process(pid)
_logger.info('Connect to port %d success, experiment id is %s, status is %s.', port, experiment.id, status)
return experiment
@classmethod
def resume(cls, experiment_id: str, port: int = 8080, wait_completion: bool = True, debug: bool = False):
"""
Resume a stopped experiment.
Parameters
----------
experiment_id
The stopped experiment id.
port
The port of web UI.
wait_completion
If true, run in the foreground. If false, run in the background.
debug
Whether to start in debug mode.
"""
experiment = Experiment()
experiment.id = experiment_id
experiment.mode = 'resume'
experiment.run(port=port, wait_completion=wait_completion, debug=debug)
if not wait_completion:
return experiment
@classmethod
def view(cls, experiment_id: str, port: int = 8080, non_blocking: bool = False):
"""
View a stopped experiment.
Parameters
----------
experiment_id
The stopped experiment id.
port
The port of web UI.
non_blocking
If false, run in the foreground. If true, run in the background.
"""
debug = False
experiment = Experiment()
experiment.id = experiment_id
experiment.mode = 'view'
experiment.start(port=port, debug=debug)
if non_blocking:
return experiment
else:
try:
while True:
time.sleep(10)
except KeyboardInterrupt:
_logger.warning('KeyboardInterrupt detected')
finally:
experiment.stop()
def get_status(self) -> str:
"""
Return experiment status as a str.
Returns
-------
str
Experiment status.
"""
resp = rest.get(self.port, '/check-status')
return resp['status']
def get_trial_job(self, trial_job_id: str):
"""
Return a trial job.
Parameters
----------
trial_job_id: str
Trial job id.
Returns
-------
TrialJob
A `TrialJob` instance corresponding to `trial_job_id`.
"""
resp = rest.get(self.port, '/trial-jobs/{}'.format(trial_job_id))
return TrialJob(**resp)
def list_trial_jobs(self):
"""
Return information for all trial jobs as a list.
Returns
-------
list
List of `TrialJob`.
"""
resp = rest.get(self.port, '/trial-jobs')
return [TrialJob(**trial_job) for trial_job in resp]
def get_job_statistics(self):
"""
Return trial job statistics information as a dict.
Returns
-------
dict
Job statistics information.
"""
resp = rest.get(self.port, '/job-statistics')
return resp
def get_job_metrics(self, trial_job_id=None):
"""
Return trial job metrics.
Parameters
----------
trial_job_id: str
trial job id. if this parameter is None, all trail jobs' metrics will be returned.
Returns
-------
dict
Each key is a trialJobId, the corresponding value is a list of `TrialMetricData`.
"""
api = '/metric-data/{}'.format(trial_job_id) if trial_job_id else '/metric-data'
resp = rest.get(self.port, api)
metric_dict = {}
for metric in resp:
trial_id = metric["trialJobId"]
if trial_id not in metric_dict:
metric_dict[trial_id] = [TrialMetricData(**metric)]
else:
metric_dict[trial_id].append(TrialMetricData(**metric))
return metric_dict
def get_experiment_profile(self):
"""
Return experiment profile as a dict.
Returns
-------
dict
The profile of the experiment.
"""
resp = rest.get(self.port, '/experiment')
return resp
def get_experiment_metadata(self, exp_id: str):
"""
Return experiment metadata with specified exp_id as a dict.
Returns
-------
dict
The specified experiment metadata.
"""
experiments_metadata = self.get_all_experiments_metadata()
for metadata in experiments_metadata:
if metadata['id'] == exp_id:
return metadata
return {}
def get_all_experiments_metadata(self):
"""
Return all experiments metadata as a list.
Returns
-------
list
The experiments metadata.
"""
resp = rest.get(self.port, '/experiments-info')
return resp
def export_data(self):
"""
Return exported information for all trial jobs.
Returns
-------
list
List of `TrialResult`.
"""
resp = rest.get(self.port, '/export-data')
return [TrialResult(**trial_result) for trial_result in resp]
def _get_query_type(self, key: str):
if key == 'trialConcurrency':
return '?update_type=TRIAL_CONCURRENCY'
if key == 'maxExecDuration':
return '?update_type=MAX_EXEC_DURATION'
if key == 'searchSpace':
return '?update_type=SEARCH_SPACE'
if key == 'maxTrialNum':
return '?update_type=MAX_TRIAL_NUM'
def _update_experiment_profile(self, key: str, value: Any):
"""
Update an experiment's profile
Parameters
----------
key: str
One of `['trial_concurrency', 'max_experiment_duration', 'search_space', 'max_trial_number']`.
value: Any
New value of the key.
"""
api = '/experiment{}'.format(self._get_query_type(key))
experiment_profile = self.get_experiment_profile()
experiment_profile['params'][key] = value
rest.put(self.port, api, experiment_profile)
logging.info('Successfully update %s.', key)
def update_trial_concurrency(self, value: int):
"""
Update an experiment's trial_concurrency
Parameters
----------
value: int
New trial_concurrency value.
"""
self._update_experiment_profile('trialConcurrency', value)
def update_max_experiment_duration(self, value: str):
"""
Update an experiment's max_experiment_duration
Parameters
----------
value: str
Strings like '1m' for one minute or '2h' for two hours.
SUFFIX may be 's' for seconds, 'm' for minutes, 'h' for hours or 'd' for days.
"""
self._update_experiment_profile('maxExecDuration', value)
def update_search_space(self, value: dict):
"""
Update the experiment's search_space.
TODO: support searchspace file.
Parameters
----------
value: dict
New search_space.
"""
value = json_tricks.dumps(value)
self._update_experiment_profile('searchSpace', value)
def update_max_trial_number(self, value: int):
"""
Update an experiment's max_trial_number
Parameters
----------
value: int
New max_trial_number value.
"""
self._update_experiment_profile('maxTrialNum', value)
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