Repeat module N times. :param int N: repeat time :param function fn: function to generate module :return: repeated modules :rtype: Mu

Add TDNN common arguments.

Run the speech decoder process. Parameters: - hidden (torch.Tensor): The output for embedding layer of the language model.

Create mask for subsequent steps (size, size). This mask is used only in decoder which works in an auto-regressive mode. This means the curre

Generates the model's next output based on the current input and state. Parameters: - inputs: The input tensor containing th

Add Subsampling common arguments.

Add Encoder common arguments.

Apply optional mask for encoder. Args: xs (torch.Tensor): padded input, (B, L, D), L for max length mask (torch.Tensor): mask fo

根据数字系统类型返回创建相应的数字系统，默认为 mid NUMBERING_TYPES = ['low', 'mid', 'high']: 中文数字系统类型 low: '兆' = '亿' * '十' = $10^{9}$, '京' = '兆' * '十', et

The inner function to generate the answer. Returns: tuple(int, str, str): ret_code, response, log