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fix ddpg metrics

This commit is contained in:
bohanjason 2020-02-26 01:25:54 -05:00 committed by Dana Van Aken
parent a9f1556184
commit 21971e673f
1 changed files with 11 additions and 17 deletions
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28
server/website/website/tasks/async_tasks.py
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@ -152,28 +152,22 @@ def clean_metric_data(metric_matrix, metric_labels, session):
metric_cat = [session.target_objective] metric_cat = [session.target_objective]
for metric_obj in metric_objs: for metric_obj in metric_objs:
metric_cat.append(metric_obj.name) metric_cat.append(metric_obj.name)
matrix = np.array(metric_matrix)
missing_columns = sorted(set(metric_cat) - set(metric_labels)) missing_columns = sorted(set(metric_cat) - set(metric_labels))
unused_columns = set(metric_labels) - set(metric_cat) unused_columns = set(metric_labels) - set(metric_cat)
LOG.debug("clean_metric_data added %d metrics and removed %d metric.", len(missing_columns), LOG.debug("clean_metric_data added %d metrics and removed %d metric.", len(missing_columns),
len(unused_columns)) len(unused_columns))
# If columns are missing from the matrix default_val = 0
if missing_columns: metric_cat_size = len(metric_cat)
for metric in missing_columns: matrix = np.ones((len(metric_matrix), metric_cat_size)) * default_val
# append a missing column after the last column metric_labels_dict = {n: i for i, n in enumerate(metric_labels)}
index = matrix.shape[1] # pylint: disable=unsubscriptable-object # column labels in matrix has the same order as ones in metric catalog
default_val = 0 # missing values are filled with default_val
matrix = np.insert(matrix, index, default_val, axis=1) for i, metric_name in enumerate(metric_cat):
metric_labels.append(metric) if metric_name in metric_labels_dict:
index = metric_labels_dict[metric_name]
matrix[:, i] = metric_matrix[:, index]
LOG.debug(matrix.shape) LOG.debug(matrix.shape)
# If they are useless columns in the matrix return matrix, metric_cat
if unused_columns:
indexes = [i for i, n in enumerate(metric_labels) if n in unused_columns]
# Delete unused columns
matrix = np.delete(matrix, indexes, 1)
for i in sorted(indexes, reverse=True):
del metric_labels[i]
return matrix, metric_labels
def save_execution_time(start_ts, fn, result): def save_execution_time(start_ts, fn, result):