style fixes

scoring/performance_profile.py

@@ -34,7 +34,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import scoring_utils
+from scoring import scoring_utils
 
 import algorithmic_efficiency.workloads.workloads as workloads_registry
 
@@ -180,7 +180,6 @@ def get_times_for_submission(submission,
       logging.warning(f'Expecting {NUM_TRIALS} trials for workload '
                       f'{workload} but found {num_trials} trials.')
     validation_metric, validation_target = scoring_utils.get_workload_validation_target(workload)
-    validation_target = validation_target
 
     trial_idx, time_idx = get_index_that_reaches_target(
         group, validation_metric, validation_target)

scoring/score_submission.py

@@ -10,7 +10,6 @@
 from tabulate import tabulate
 
 from scoring import performance_profile
-from scoring.performance_profile import check_if_minimized
 
 flags.DEFINE_string(
     'experiment_path',
@@ -28,7 +27,7 @@
 
 def get_summary_df(workload, workload_df):
   validation_metric, validation_target = scoring_utils.get_workload_validation_target(workload)
-  is_minimized = check_if_minimized(validation_metric)
+  is_minimized = performance_profile.check_if_minimized(validation_metric)
   target_op = operator.le if is_minimized else operator.ge
   best_op = min if is_minimized else max
   idx_op = np.argmin if is_minimized else np.argmax
@@ -65,7 +64,7 @@ def main(_):
     dfs.append(summary_df)
 
   df = pd.concat(dfs)
-  print(tabulate(df, headers='keys', tablefmt='psql'))
+  logging.info(tabulate(df, headers='keys', tablefmt='psql'))
 
   if FLAGS.compute_performance_profiles:
     performance_profile_df = performance_profile.compute_performance_profiles(

scoring/scoring_utils.py

@@ -140,7 +140,7 @@ def get_trials_df(logfile):
 def get_experiment_df(experiment_dir):
   """Gets a df of per trial results from an experiment dir.
   The output df can be provided as input to 
-  score_profilecompute_performance_profiles. 
+  performance_profile.compute_performance_profiles. 
   Args:
       experiment_dir: path to experiment directory containing 
         results for workloads.
@@ -196,8 +196,7 @@ def get_experiment_df(experiment_dir):
 
 ## Get workload properties
 def get_workload_validation_target(workload):
-  """Returns workload target metric name and value.
-  """
+  """Returns workload target metric name and value."""
   workload_name = re.match(WORKLOAD_NAME_PATTERN, workload).group(1)
   framework = re.match(WORKLOAD_NAME_PATTERN, workload).group(2)
   workload_metadata = copy.copy(WORKLOADS[workload_name])
@@ -208,7 +207,6 @@ def get_workload_validation_target(workload):
       workload_metadata['workload_path'] + f'{framework}',
       'workload.py')
   workload_init_kwargs = {}
-  print(workload_metadata['workload_path'])
   workload_obj = workloads_registry.import_workload(
       workload_path=workload_metadata['workload_path'],
       workload_class_name=workload_metadata['workload_class_name'],