def create_experiment(
self,
config: Union[str, pathlib.Path, Dict],
model_dir: str,
) -> experiment.ExperimentReference:
check.is_instance(config, (str, pathlib.Path, dict),
"config parameter must be dictionary or path")
if isinstance(config, str):
with open(config) as f:
experiment_config = yaml.safe_load(f)
elif isinstance(config, pathlib.Path):
with config.open() as f:
experiment_config = yaml.safe_load(f)
elif isinstance(config, Dict):
experiment_config = config
model_context = _path_to_files(pathlib.Path(model_dir))
experiment_request = V1CreateExperimentRequest(
model_definition=model_context,
config=yaml.safe_dump(experiment_config),
)
experiment_response = self._internal.determined_create_experiment(
experiment_request)
return experiment.ExperimentReference(
experiment_response.experiment.id,
self._session._master,
self._experiments,
)
def get_experiment(self, experiment_id: int) -> experiment.ExperimentReference:
"""
Get the :class:`~determined.experimental.ExperimentReference` representing the
experiment with the provided experiment ID.
"""
return experiment.ExperimentReference(
experiment_id,
self._session,
)
def create_experiment(
self,
config: Union[str, pathlib.Path, Dict],
model_dir: Union[str, pathlib.Path],
) -> experiment.ExperimentReference:
"""
Create an experiment with config parameters and model directory. The function
returns :class:`~determined.experimental.ExperimentReference` of the experiment.
Arguments:
config(string, pathlib.Path, dictionary): experiment config filename (.yaml)
or a dict.
model_dir(string): directory containing model definition.
"""
check.is_instance(
config, (str, pathlib.Path, dict), "config parameter must be dictionary or path"
)
if isinstance(config, str):
with open(config) as f:
experiment_config = util.safe_load_yaml_with_exceptions(f)
elif isinstance(config, pathlib.Path):
with config.open() as f:
experiment_config = util.safe_load_yaml_with_exceptions(f)
elif isinstance(config, Dict):
experiment_config = config
if isinstance(model_dir, str):
model_dir = pathlib.Path(model_dir)
model_context, _ = context.read_context(model_dir)
resp = self._session.post(
"/api/v1/experiments",
body={
"config": yaml.safe_dump(experiment_config),
"model_definition": model_context,
},
)
exp_id = _CreateExperimentResponse(resp.json()).id
exp = experiment.ExperimentReference(exp_id, self._session)
exp.activate()
return exp
def create_experiment(
self,
config: Union[str, pathlib.Path, Dict],
model_dir: str,
) -> experiment.ExperimentReference:
"""
Create an experiment with config parameters and model direcotry. The function
returns :class:`~determined.experimental.ExperimentReference` of the experiment.
Arguments:
config(string, pathlib.Path, dictionary): experiment config filename (.yaml)
or a dict.
model_dir(string): directory containing model definition.
"""
check.is_instance(config, (str, pathlib.Path, dict),
"config parameter must be dictionary or path")
if isinstance(config, str):
with open(config) as f:
experiment_config = util.safe_load_yaml_with_exceptions(f)
elif isinstance(config, pathlib.Path):
with config.open() as f:
experiment_config = util.safe_load_yaml_with_exceptions(f)
elif isinstance(config, Dict):
experiment_config = config
model_context = _path_to_files(pathlib.Path(model_dir))
experiment_request = V1CreateExperimentRequest(
model_definition=model_context,
config=yaml.safe_dump(experiment_config),
)
experiment_response = self._internal.determined_create_experiment(
experiment_request)
return experiment.ExperimentReference(
experiment_response.experiment.id,
self._session._master,
self._experiments,
)
