Method sample_orders

models/mar.py:152–160

(self, bsz)

        return x  # [n, c, h, w]

    def sample_orders(self, bsz):
        # generate a batch of random generation orders
        orders = []
        for _ in range(bsz):
            order = np.array(list(range(self.seq_len)))
            np.random.shuffle(order)
            orders.append(order)
        orders = torch.Tensor(np.array(orders)).cuda().long()
        return orders

    def random_masking(self, x, orders):
        # generate token mask