def main():
# Parse input
dir_path = sys.argv[1]
train_instances_file_name = os.path.join(dir_path, 'subflow_data.pickle')
runs = eval(sys.argv[4])
# construct socket to communicate with backend
send_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
send_sock.connect((sys.argv[2], int(sys.argv[3])))
try:
flow_ids = eval(sys.argv[5])
for flow_id in flow_ids:
flow_file_name = os.path.join(dir_path, flow_id + '.pickle')
# Unpickle the flow and train_instances
with open(flow_file_name, 'rb') as flow_file:
flow = pickle.load(flow_file)
with open(train_instances_file_name, 'rb') as train_instances_file:
train_instances = pickle.load(train_instances_file)
try:
# Execute the flow
# .. note:: the here executed flows can not store anything
# meta data of result collection is NOT updated!
_, result_collection = flow(train_instances=train_instances,
runs=runs)
# Store results
result_file_name = flow_file_name.replace(
'.pickle', '_result.pickle')
with open(result_file_name, 'wb') as result_file:
pickle.dump(result_collection,
result_file,
protocol=pickle.HIGHEST_PROTOCOL)
finally:
# Delete the flow_file since we don't need it any more
# training_file is may be used by other flows so don't delete it
os.remove(flow_file_name)
# Inform Backend that this flow has finished
send_sock = LoadLevelerComHandler(
send_sock, sys.argv[2], int(sys.argv[3]),
LoadLevelerComHandler.MESSAGES.FINISHED, flow_id)
# give backend some time to get information
time.sleep(1)
finally:
send_sock.shutdown(socket.SHUT_RDWR)
send_sock.close()
def main():
# Parse input
dir_path = sys.argv[1]
train_instances_file_name = os.path.join(dir_path,
'subflow_data.pickle')
runs = eval(sys.argv[4])
# construct socket to communicate with backend
send_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
send_sock.connect((sys.argv[2], int(sys.argv[3])))
try:
flow_ids = eval(sys.argv[5])
for flow_id in flow_ids:
flow_file_name = os.path.join(dir_path, flow_id + '.pickle')
# Unpickle the flow and train_instances
with open(flow_file_name, 'rb') as flow_file:
flow = pickle.load(flow_file)
with open(train_instances_file_name, 'rb') as train_instances_file:
train_instances = pickle.load(train_instances_file)
try:
# Execute the flow
# .. note:: the here executed flows can not store anything
# meta data of result collection is NOT updated!
_, result_collection = flow(train_instances=train_instances, runs=runs)
# Store results
result_file_name = flow_file_name.replace('.pickle', '_result.pickle')
with open(result_file_name, 'wb') as result_file:
pickle.dump(result_collection, result_file, protocol=pickle.HIGHEST_PROTOCOL)
finally:
# Delete the flow_file since we don't need it any more
# training_file is may be used by other flows so don't delete it
os.remove(flow_file_name)
# Inform Backend that this flow has finished
send_sock = LoadLevelerComHandler(send_sock, sys.argv[2], int(sys.argv[3]),
LoadLevelerComHandler.MESSAGES.FINISHED, flow_id)
# give backend some time to get information
time.sleep(1)
finally:
send_sock.shutdown(socket.SHUT_RDWR)
send_sock.close()