def __init__(self, model, csv_path, sample_size, dt=30, lr=0.001, opt_id=0):
    self.model = model
    self.model.init_params()
    self.model_id = opt_id
    self.device = torch.device(('cuda:0' if torch.cuda.is_available() else 'cpu'))
    (self.train_dataloader, self.test_dataloader) = dataset_creator(csv_path, int(sample_size), int(dt))
    self.optimizer = torch.optim.Adam([self.model.params, self.model.cooling], lr=lr)
def __init__(self, model, csv_path, sample_size, dt=30, lr=0.001, opt_id=0):
    self.model = model
    self.model.init_params()
    self.model_id = opt_id
    self.device = torch.device(('cuda:0' if torch.cuda.is_available() else 'cpu'))
    (self.train_dataloader, self.test_dataloader) = dataset_creator(csv_path, int(sample_size), int(dt))
    self.optimizer = torch.optim.Adam([self.model.params, self.model.cooling], lr=lr)