def predict()

in submission_code/best_ctx.py [0:0]

• 8 lines of code
• 2 McCabe index (conditional complexity)

    def predict(self, text, util, beam_width):
        text = text + ' ' + self.ctx.get(util, '')
        text_enc = self.text_tokenizer.encode(text)
        tokens = torch.tensor([bos_id] + text_enc[:self.config.max_src_len] + [eos_id]).long()
        
        with torch.no_grad():
            pred = beam_search(tokens, self.model.tr, pad_id, bos_id, eos_id, max_len=self.config.max_tgt_len, k=beam_width)
        
        pred = [(self.cmd_tokenizer.decode(list(map(int, x))), proba) for x, proba in pred]
        return pred