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fixes issue #565 and removes future / deprecation warnings #566

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Merged
mfeurer merged 4 commits into from
Oct 12, 2018
Merged

fixes issue #565 and removes future / deprecation warnings #566

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2316e22
fixes issue #565 and removes future / deprecation warnings
janvanrijn Oct 6, 2018
e6392ba
removes last deprecation warning
janvanrijn Oct 6, 2018
00c8a06
added additional raised error
janvanrijn Oct 9, 2018
fef6c89
changed structure
janvanrijn Oct 9, 2018
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17 changes: 12 additions & 5 deletions openml/setups/functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,9 @@ def setup_exists(flow, model=None):
----------

flow : flow
The openml flow object.
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)

sklearn_model : BaseEstimator, optional
If given, the parameters are parsed from this model instead of the
Expand All @@ -36,11 +38,16 @@ def setup_exists(flow, model=None):
openml.flows.functions._check_flow_for_server_id(flow)

if model is None:
# model is left empty. We take the model from the flow.
model = flow.model
else:
exists = flow_exists(flow.name, flow.external_version)
if exists != flow.flow_id:
raise ValueError('This should not happen!')
if flow.model is None:
raise ValueError('Could not locate model (neither given as'
'argument nor available as flow.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!')

openml_param_settings = openml.runs.OpenMLRun._parse_parameters(flow, model)
description = xmltodict.unparse(_to_dict(flow.flow_id,
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13 changes: 6 additions & 7 deletions tests/test_runs/test_run_functions.py
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Expand Up @@ -596,22 +596,21 @@ def test_get_run_trace(self):

task = openml.tasks.get_task(task_id)
# IMPORTANT! Do not sentinel this flow. is faster if we don't wait on openml server
clf = RandomizedSearchCV(RandomForestClassifier(random_state=42),
clf = RandomizedSearchCV(RandomForestClassifier(random_state=42,
n_estimators=5),
{"max_depth": [3, None],
"max_features": [1, 2, 3, 4],
"bootstrap": [True, False],
"criterion": ["gini", "entropy"]},
num_iterations, random_state=42)
num_iterations, random_state=42, cv=3)

# [SPEED] make unit test faster by exploiting run information from the past
try:
# in case the run did not exists yet
run = openml.runs.run_model_on_task(task, clf, avoid_duplicate_runs=True)
trace = openml.runs.functions._create_trace_from_arff(
run._generate_trace_arff_dict()
)
run = openml.runs.run_model_on_task(clf, task,
avoid_duplicate_runs=True)
self.assertEqual(
len(trace.trace_iterations),
len(run.trace.trace_iterations),
num_iterations * num_folds,
)
run = run.publish()
Expand Down