# One folder for each algorithm
log_list = os.listdir(os.path.join(args.folder, algo))
successful_job_count = 0
total_jobs = 0
total_time_ms = 0.0
pipeline_counts = np.zeros(len(cfg.PIPELINES), dtype=np.int)
metrics[algo + '.makespans'] = []
dev_counts = np.zeros(len(devices))
for filename in log_list:
filepath = os.path.join(args.folder, algo, filename)
reader = LogParser(filepath)
results = reader.extract()
df = pd.DataFrame(data=results['job_pipelines'],
columns=['id', 'pipeline'])
# Update count for each pipeline
counts = df.pipeline.value_counts()
keys = counts.keys()
values = counts.values
for i in range(len(keys)):
pipeline_counts[keys[i]] += values[i]
# Throughput constraint
if T_o is None:
T_o = results['T_o'][0][1]
else:
