headers = ['timestamp']
for n in list(itertools.islice(metrics, 1))[0].names:
headers.extend(['{0} cost'.format(n), '{0} action'.format(n)])
headers.extend(['prob', 'file'])
data = itertools.chain.from_iterable(
map(lambda x: x.tabulate_data(), metrics))
if top:
data = itertools.islice(data, top)
return tabulate(data, headers)
# reproduce training, by using trackback files
model_history = list(
common.get_checkpoint_models(block_blob_service,
start_date_withlookback, end_date))
with Pool(5) as p:
model_history = p.map(
lambda x: common.CheckpointedModel(block_blob_service, x[
0], cache_folder, x[1], x[2]), model_history)
for m in model_history:
if m.model_id is not None:
global_model_idx[m.model_id] = m
model_history.sort(key=lambda jd: jd.ts)
# create scoring directories for [start_date, end_date] range
scoring_dir = os.path.join(cache_folder, 'scoring')
if not os.path.exists(scoring_dir):
os.makedirs(scoring_dir)
def tabulate_metrics(metrics, top = None):
headers = ['timestamp']
for n in list(itertools.islice(metrics, 1))[0].names:
headers.extend(['{0} cost'.format(n), '{0} action'.format(n)])
headers.extend(['prob', 'file'])
data = itertools.chain.from_iterable(map(lambda x : x.tabulate_data(), metrics))
if top:
data = itertools.islice(data, top)
return tabulate(data, headers)
# reproduce training, by using trackback files
model_history = list(common.get_checkpoint_models(block_blob_service, start_date_withlookback, end_date))
with Pool(5) as p:
model_history = p.map(lambda x: common.CheckpointedModel(block_blob_service, x[0], cache_folder, x[1], x[2]), model_history)
for m in model_history:
if m.model_id is not None:
global_model_idx[m.model_id] = m
model_history.sort(key=lambda jd: jd.ts)
# create scoring directories for [start_date, end_date] range
scoring_dir = os.path.join(cache_folder, 'scoring')
os.makedirs(scoring_dir, exist_ok=True)
for local_date in common.dates_in_range(start_date, end_date):
scoring_dir_date = os.path.join(scoring_dir, local_date.strftime('%Y/%m/%d'))
if os.path.exists(scoring_dir_date):