def main():
experiment = Experiment(log_code=True)
experiment.log_parameters(hyperparameters)
train_loader, test_loader, test_IDs = load_dataset(
window_size=hyperparameters["window_size"])
experiment._log_parameter("test_split", test_IDs, 0)
model = Net(rnn_size=hyperparameters["rnn_size"],
output_size=hyperparameters["output_size"]).to(device)
TRAIN = True
if TRAIN:
train(model, train_loader, experiment)
save(model, './model.pt')
else:
model.load_state_dict(torch.load('./model.pt'))
test(model, test_loader, experiment)
