Is there a problem with sample loading?

[lkq111]

    model = None
    if args.hf_model is not None:
        model = create_wrapped_hf_model(args)
    else:
        # Optional: Use meta device
        with torch.device("meta" if args.experimental_meta_device and args.fsdp else args.device):
            model = create_model(args)

    args.vocab_size = model.vocab_size
    args.seq_len = model.seq_len
    if args.train_num_samples is not `None:`
        args.train_num_samples //= args.seq_len
        print(f"Training num samples (tokens): {args.train_num_samples} / seq_len: {args.seq_len} = {args.train_num_samples // args.seq_len} sequences")
    if args.val_num_samples is not None:
        if args.val_num_samples // args.seq_len == 0:
            raise ValueError(
                f"number of requested evaluation val_num_samples (tokens): {args.val_num_samples} is less than seq_len: {args.seq_len}"
            )
        args.val_num_samples //= args.seq_len

why args.train_num_samples //= args.seq_len ??? I don't understand, could you please explain?