src/run.py [214:227]:
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    val_datasets = []
    for val_filename in opts.val_datasets:
        val_datasets.append(
            problem.make_dataset(
                filename=val_filename, batch_size=opts.batch_size, num_samples=opts.val_size, 
                neighbors=opts.neighbors, knn_strat=opts.knn_strat, supervised=True, nar=False
            ))

    if opts.resume:
        epoch_resume = int(os.path.splitext(os.path.split(opts.resume)[-1])[0].split("-")[1])

        torch.set_rng_state(load_data['rng_state'])
        if opts.use_cuda:
            torch.cuda.set_rng_state_all(load_data['cuda_rng_state'])
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src/run.py [368:381]:
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    val_datasets = []
    for val_filename in opts.val_datasets:
        val_datasets.append(
            problem.make_dataset(
                filename=val_filename, batch_size=opts.batch_size, num_samples=opts.val_size, 
                neighbors=opts.neighbors, knn_strat=opts.knn_strat, supervised=True, nar=False
            ))

    if opts.resume:
        epoch_resume = int(os.path.splitext(os.path.split(opts.resume)[-1])[0].split("-")[1])

        torch.set_rng_state(load_data['rng_state'])
        if opts.use_cuda:
            torch.cuda.set_rng_state_all(load_data['cuda_rng_state'])
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