def sample(self, inputs, states=None, max_len=20):
        out = []
        for i in range(max_len):
            lstm_out, states = self.lstm(inputs, states)
            lstm_out = torch.squeeze(lstm_out, 1)
            linear_out = self.linear(lstm_out)
            word = linear_out.max(1)[1]
            out.append(word.item())
            inputs = torch.unsqueeze(self.embed(word), 1)

        return out