def setup_exists(flow, model=None):
'''
Checks whether a hyperparameter configuration already exists on the server.
Parameter
---------
flow : flow
The openml flow object.
sklearn_model : BaseEstimator, optional
If given, the parameters are parsed from this model instead of the
model in the flow. If not given, parameters are parsed from
``flow.model``.
Returns
-------
setup_id : int
setup id iff exists, False otherwise
'''
# sadly, this api call relies on a run object
openml.flows.functions._check_flow_for_server_id(flow)
if model is None:
model = flow.model
else:
exists = flow_exists(flow.name, flow.external_version)
if exists != flow.flow_id:
raise ValueError('This should not happen!')
openml_param_settings = openml.runs.OpenMLRun._parse_parameters(
flow, model)
description = xmltodict.unparse(_to_dict(flow.flow_id,
openml_param_settings),
pretty=True)
file_elements = {'description': ('description.arff', description)}
result = openml._api_calls._perform_api_call('/setup/exists/',
file_elements=file_elements)
result_dict = xmltodict.parse(result)
setup_id = int(result_dict['oml:setup_exists']['oml:id'])
if setup_id > 0:
return setup_id
else:
return False
def setup_exists(flow) -> int:
"""
Checks whether a hyperparameter configuration already exists on the server.
Parameters
----------
flow : flow
The openml flow object. Should have flow id present for the main flow
and all subflows (i.e., it should be downloaded from the server by
means of flow.get, and not instantiated locally)
Returns
-------
setup_id : int
setup id iff exists, False otherwise
"""
# sadly, this api call relies on a run object
openml.flows.functions._check_flow_for_server_id(flow)
if flow.model is None:
raise ValueError(
'Flow should have model field set with the actual model.')
if flow.extension is None:
raise ValueError(
'Flow should have model field set with the correct extension.')
# checks whether the flow exists on the server and flow ids align
exists = flow_exists(flow.name, flow.external_version)
if exists != flow.flow_id:
raise ValueError('This should not happen!')
openml_param_settings = flow.extension.obtain_parameter_values(flow)
description = xmltodict.unparse(_to_dict(flow.flow_id,
openml_param_settings),
pretty=True)
file_elements = {'description': ('description.arff', description)}
result = openml._api_calls._perform_api_call('/setup/exists/',
'post',
file_elements=file_elements)
result_dict = xmltodict.parse(result)
setup_id = int(result_dict['oml:setup_exists']['oml:id'])
if setup_id > 0:
return setup_id
else:
return False
def setup_exists(flow):
"""
Checks whether a hyperparameter configuration already exists on the server.
Parameters
----------
flow : flow
The openml flow object. Should have flow id present for the main flow
and all subflows (i.e., it should be downloaded from the server by
means of flow.get, and not instantiated locally)
Returns
-------
setup_id : int
setup id iff exists, False otherwise
"""
# sadly, this api call relies on a run object
openml.flows.functions._check_flow_for_server_id(flow)
if flow.model is None:
raise ValueError('Flow should have model field set with the actual '
'model. ')
# checks whether the flow exists on the server and flow ids align
exists = flow_exists(flow.name, flow.external_version)
if exists != flow.flow_id:
raise ValueError('This should not happen!')
# TODO: currently hard-coded sklearn assumption
openml_param_settings = openml.flows.obtain_parameter_values(flow)
description = xmltodict.unparse(_to_dict(flow.flow_id,
openml_param_settings),
pretty=True)
file_elements = {'description': ('description.arff', description)}
result = openml._api_calls._perform_api_call('/setup/exists/',
file_elements=file_elements)
result_dict = xmltodict.parse(result)
setup_id = int(result_dict['oml:setup_exists']['oml:id'])
if setup_id > 0:
return setup_id
else:
return False