def finalize()

in whisper/decoding.py [0:0]

• 19 lines of code
• 10 McCabe index (conditional complexity)

    def finalize(self, preceding_tokens: Tensor, sum_logprobs: Tensor):
        # collect all finished sequences, including patience, and add unfinished ones if not enough
        sum_logprobs = sum_logprobs.cpu()
        for i, sequences in enumerate(self.finished_sequences):
            if (
                len(sequences) < self.beam_size
            ):  # when not enough sequences are finished
                for j in list(np.argsort(sum_logprobs[i]))[::-1]:
                    sequence = preceding_tokens[i, j].tolist() + [self.eot]
                    sequences[tuple(sequence)] = sum_logprobs[i][j].item()
                    if len(sequences) >= self.beam_size:
                        break

        tokens: List[List[Tensor]] = [
            [torch.tensor(seq) for seq in sequences.keys()]
            for sequences in self.finished_sequences
        ]
        sum_logprobs: List[List[float]] = [
            list(sequences.values()) for sequences in self.finished_sequences
        ]
        return tokens, sum_logprobs