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Remove test target from scoring #535

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merged 1 commit into from
Oct 6, 2023
Merged

Remove test target from scoring #535

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21 changes: 5 additions & 16 deletions scoring/scoring.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@


def generate_eval_cols(metrics):
splits = ['train', 'validation', 'test']
splits = ['train', 'validation']
return [f'{split}/{col}' for split, col in itertools.product(splits, metrics)]


Expand Down Expand Up @@ -108,15 +108,13 @@ def get_index_that_reaches_best(workload_df, metric_col):

def get_index_that_reaches_target(workload_df,
validation_metric,
test_metric,
validation_target,
test_target):
validation_target):
"""Get the eval index in which a workload reaches the target metric_col.

Args:
workload_df: A subset of a submission's trials DataFrame that
includes only the trials in a single workload.
metric_col: Name of array column in workload_df (e.g., `validation/l1_loss`).
metric_col: Name of array column in workload_df (e.g. `validation/l1_loss`).
target: Target value for metric_col.

Returns:
Expand All @@ -125,20 +123,13 @@ def get_index_that_reaches_target(workload_df,
"""
is_minimized = check_if_minimized(validation_metric)
validation_series = workload_df[validation_metric]
test_series = workload_df[test_metric]

validation_series = validation_series[validation_series != np.nan]
validation_series = validation_series[test_series != np.nan]
test_series = test_series[validation_series != np.nan]
test_series = test_series[test_series != np.nan]

op = operator.le if is_minimized else operator.ge
validation_target_reached = validation_series.apply(
lambda x: op(x, validation_target))
test_target_reached = test_series.apply(lambda x: op(x, test_target))

target_reached = pd.Series(validation_target_reached[0]
& test_target_reached[0])
target_reached = pd.Series(validation_target_reached[0])
# Remove trials that never reach the target
target_reached = target_reached[target_reached.apply(np.any)]

Expand Down Expand Up @@ -188,12 +179,10 @@ def get_times_for_submission(submission,
workload_init_kwargs=workload_init_kwargs)
metric_name = workload_obj.target_metric_name
validation_metric = f'validation/{metric_name}'
test_metric = f'test/{metric_name}'
validation_target = workload_obj.validation_target_value
test_target = workload_obj.test_target_value

trial_idx, time_idx = get_index_that_reaches_target(
group, validation_metric, test_metric, validation_target, test_target)
group, validation_metric, validation_target)
if time_idx > -1:
time_val = group[time_col].loc[trial_idx][time_idx]
else:
Expand Down