def _get_feat_extract_output_lengths(self, input_lengths: torch.LongTensor):
        """
        Computes the output length of the convolutional layers
        """

        def _conv_out_length(input_length, kernel_size, stride):
            return torch.floor((input_length - kernel_size) / stride + 1)

        conv_cfg_list = eval(self.cfg.conv_feature_layers)

        for i in range(len(conv_cfg_list)):
            input_lengths = _conv_out_length(
                input_lengths, conv_cfg_list[i][1], conv_cfg_list[i][2]
            )

        return input_lengths.to(torch.long)

        Computes the output length of the convolutional layers
        
structured_prompting/fairseq-version/fairseq/fairseq/models/wav2vec/wav2vec2.py