Files
drift/archive/lightning/run_pipeline.py
T
Mark Aron Szulyovszky d047b7417e feat(WalkForward): added regression/classification switch, archived old experiments, wrapped the process into run_whole_pipeline() (#10)
* refactor(WalkForward): cleaned up training & evaluation code

* refactor: added run_whole_pipeline(), moved all previous models to archive
2021-12-14 18:16:17 +01:00

41 lines
1.4 KiB
Python

#%%
from create_dataset import load_format_data, create_dataloaders
from train_predict import train_model, predict
from models.built_in_models import create_TemporalFusionTransformer
from models.custom_model import create_FullyConnectedModel
from options import training_options, model_options_tft, model_options_fcn, dataset_options_tft, dataset_options_fcn
import warnings
warnings.filterwarnings("ignore")
#%%
def run_pipeline(model_name, data_dir):
data = load_format_data(data_dir)
dataset_options, model_options, _create_model = select_model(model_name)
training_dataset, train_dataloader, val_dataloader = create_dataloaders(data, dataset_options)
model = _create_model( training_dataset, model_options )
trainer = train_model(model, train_dataloader, val_dataloader, training_options)
predict(trainer, model, val_dataloader)
#%%
def select_model(model_name):
if model_name == "FullyConnectedLayer":
return dataset_options_fcn, model_options_fcn, create_FullyConnectedModel
elif model_name == "TemporalFusionTransformer":
return dataset_options_tft, model_options_tft, create_TemporalFusionTransformer
else:
assert False, "No such model exists."
#%%
run_pipeline("FullyConnectedLayer", '../data/')
# #%%
# if __name__ == '__main__':
# run_pipeline("FullyConnectedLayer", '../data/')