decoding

游雁

2024-06-14 59bc02b089f7a626fe67907dcfc695eae6883f82

 funasr/datasets/openai_datasets/datasets.py

@@ -64,6 +64,8 @@
        self.max_token_length = kwargs.get("max_token_length", 1024)
        self.batch_size_scale_ratio_max = kwargs.get("batch_size_scale_ratio_max", 1.5)
        self.batch_size_token_max = kwargs.get("batch_size_token_max", 2500)
        self.audio_adaptor_downsample_rate = kwargs.get("audio_adaptor_downsample_rate", 2)
        self.audio_encoder_downsample_rate = kwargs.get("audio_encoder_downsample_rate", 4)

    def get_source_len(self, index):
        item = self.index_ds[index]
@@ -136,10 +138,13 @@
                                speech = speech.permute(0, 2, 1)
                            # if speech_lengths > self.batch_size:
                            #     continue
                            if self.audio_encoder_downsample_rate == 4:
                                olens = 1 + (speech_lengths[0].item() - 3 + 2 * 1) // 2
                                olens = 1 + (olens - 3 + 2 * 1) // 2
                            elif self.audio_encoder_downsample_rate == 1:
                                olens = speech_lengths[0].item()

                            olens = 1 + (speech_lengths[0].item() - 3 + 2 * 1) // 2
                            olens = 1 + (olens - 3 + 2 * 1) // 2
                            sub_token_len = (olens - 1) // 2 + 1
                            sub_token_len = (olens - 1) // self.audio_adaptor_downsample_rate + 1
                            sub_token = [0] * sub_token_len
                            fbank_beg_i = [len(source_ids)]
                            source_ids += sub_token