o ip@s8dZddlZdejfddZddZdejfdd ZdS) z Mask module.NcpucCs tj||||d}tj||dS)a#Create mask for subsequent steps (size, size). :param int size: size of mask :param str device: "cpu" or "cuda" or torch.Tensor.device :param torch.dtype dtype: result dtype :rtype: torch.Tensor >>> subsequent_mask(3) [[1, 0, 0], [1, 1, 0], [1, 1, 1]] devicedtype)out)torchonestril)sizerrretr X/home/ubuntu/.local/lib/python3.10/site-packages/funasr/models/transformer/utils/mask.pysubsequent_mask s rcCs0||k}t|d|jdd}|d|@S)zCreate mask for decoder self-attention. :param torch.Tensor ys_pad: batch of padded target sequences (B, Lmax) :param int ignore_id: index of padding :param torch.dtype dtype: result dtype :rtype: torch.Tensor (B, Lmax, Lmax) )rr)rr r unsqueeze) ys_in_pad ignore_idys_maskmr r r target_masksrcCs\tj||||d}|dks||kr|Stj|d||||d}||d|d|df<|S)a Create mask for decoder self-attention. :param int size: size of mask :param int vad_pos: index of vad index :param str device: "cpu" or "cuda" or torch.Tensor.device :param torch.dtype dtype: result dtype :rtype: torch.Tensor (B, Lmax, Lmax) rrN)rrzeros)r vad_posrrr sub_cornerr r r vad_mask&s  r)__doc__rboolrrrr r r r s