Function main

trainer.py:214–256

(dataset, times)

def main(dataset, times):
    args = parameter_parser()
    args.dataset = dataset

    args.device = th.device('cuda') if th.cuda.is_available() else th.device('cpu')
    args.nhid = 200
    args.max_epoch = 200
    args.dropout = 0.5
    args.val_ratio = 0.1
    args.early_stopping = 10
    args.lr = 0.02
    model = GCN

    print(args)

    predata = PrepareData(args)
    cudause = CudaUse()

    record = LogResult()
    seed_lst = list()
    for ind, seed in enumerate(return_seed(times)):
        print(f"\n\n==> {ind}, seed:{seed}")
        args.seed = seed
        seed_lst.append(seed)

        framework = TextGCNTrainer(model=model, args=args, pre_data=predata)
        framework.fit()

        if th.cuda.is_available():
            gpu_mem = cudause.gpu_mem_get(_id=0)
            record.log_single(key="gpu_mem", value=gpu_mem)

        record.log(framework.test())

        del framework
        gc.collect()

        if th.cuda.is_available():
            th.cuda.empty_cache()

    print("==> seed set:")
    print(seed_lst)
    record.show_str()


if __name__ == '__main__':