[Solved] Reproducibility: Where is the randomness coming in?

[harikrishnanrajeev (hari rajeev)]

@Pomo

def random_seed(seed_value, use_cuda):
    np.random.seed(seed_value) # cpu vars
    torch.manual_seed(seed_value) # cpu  vars
    random.seed(seed_value) # Python
    if use_cuda: 
        torch.cuda.manual_seed(seed_value)
        torch.cuda.manual_seed_all(seed_value) # gpu vars
        torch.backends.cudnn.deterministic = True  #needed
        torch.backends.cudnn.benchmark = False

running a tabular model , was able to reproduce exact same validation loss and metrics using the random_seed() and placing random_seed(0,use_cuda=False ) before tabular_learner and also fit_one_cycle

many thanks to @Pomo , @rpcoelho and others