def train_clean(dataset_id):
# Load the dataset
dataset = data_service.get_dataset(dataset_id)
train(dataset)
def train_existing(model_type, dataset_id):
if data_service.get_dataset(dataset_id) is None:
return jsonify({"message": "Dataset not found."}), 400
if model_type == SENTIMENT_MODEL_TYPE:
if sentiment_service.is_busy():
return jsonify(
{"message": "System is busy. Please try again later."}), 500
# endif
if config.ADDITIONAL_DEBUGGING_SUPPORT == True:
thread = threading.Thread(target=sentiment_service.train_clean,
args=(dataset_id, ))
thread.start()
else:
process = Process(target=sentiment_service.train_clean,
args=(dataset_id, ))
process.start()
elif model_type == CATEGORY_MODEL_TYPE:
if category_service.is_busy():
return jsonify(
{"message": "System is busy. Please try again later."}), 500
# endif
if config.ADDITIONAL_DEBUGGING_SUPPORT == True:
thread = threading.Thread(target=category_service.train_clean,
args=(dataset_id, ))
thread.start()
else:
process = Process(target=category_service.train_clean,
args=(dataset_id, ))
process.start()
elif model_type == STOCK_MODEL_TYPE:
if stock_service.is_busy():
return jsonify(
{"message": "System is busy. Please try again later."}), 500
# endif
if config.ADDITIONAL_DEBUGGING_SUPPORT == True:
thread = threading.Thread(target=stock_service.train_clean,
args=(dataset_id, ))
thread.start()
else:
process = Process(target=stock_service.train_clean,
args=(dataset_id, ))
process.start()
# endif
elif model_type == STOCK_V2_MODEL_TYPE:
if stock_service_v2.is_busy():
return jsonify(
{"message": "System is busy. Please try again later."}), 500
# endif
if config.ADDITIONAL_DEBUGGING_SUPPORT == True:
thread = threading.Thread(target=stock_service_v2.train_clean,
args=(dataset_id, ))
thread.start()
else:
process = Process(target=stock_service_v2.train_clean,
args=(dataset_id, ))
process.start()
# endif
return jsonify({'message': 'Training started.'})