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Allow specifying cross-validation subsets of the dataset to be monitored #1560

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Allow specifying cross-validation subsets of the dataset to be monitored #1560

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5fcc7ae
Allow specifying cross-validation subsets of the dataset to be monito…
tsoontornwutikul Oct 12, 2015
2490190
Modified pylearn2/cross_validation/__init__.py to ensure compatibilit…
tsoontornwutikul Oct 12, 2015
7e8231e
Removed inadvertently introduced UTF-8 BOM and whitespaces.
tsoontornwutikul Oct 12, 2015
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12 changes: 11 additions & 1 deletion pylearn2/cross_validation/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,9 @@ class TrainCV(object):
Training model. If list, training model for each fold.
algorithm : TrainingAlgorithm
Training algorithm.
algorithm_monitoring_datasets : list or None
Subsets of the dataset to be monitored.
Leave as None to monitor all subsets.
save_path : str or None
Output filename for trained models. Also used (with modification)
for individual models if save_folds is True.
Expand All @@ -49,6 +52,7 @@ class TrainCV(object):
TrainCVExtension objects for the parent TrainCV object.
"""
def __init__(self, dataset_iterator, model, algorithm=None,
algorithm_monitoring_datasets=None,
save_path=None, save_freq=0, extensions=None,
allow_overwrite=True, save_folds=False, cv_extensions=None):
self.dataset_iterator = dataset_iterator
Expand Down Expand Up @@ -76,7 +80,13 @@ def __init__(self, dataset_iterator, model, algorithm=None,

# setup monitoring datasets
this_algorithm = deepcopy(algorithm)
this_algorithm._set_monitoring_dataset(datasets)
if algorithm_monitoring_datasets is None:
monitoring_datasets = datasets
else:
monitoring_datasets = dict(
(k, v) for (k, v) in datasets.iteritems()
if k in algorithm_monitoring_datasets)
this_algorithm._set_monitoring_dataset(monitoring_datasets)

# extensions
this_extensions = deepcopy(extensions)
Expand Down