o i@s2ddlZddlmmZGdddejjZdS)Nc sVeZdZdZ   ddedededed ef fd d Zd d ZddZ ddZ Z S)CTCzCTC module. Args: odim: dimension of outputs encoder_output_size: number of encoder projection units dropout_rate: dropout rate (0.0 ~ 1.0) reduce: reduce the CTC loss into a scalar Trodimencoder_output_size dropout_ratereduceblank_idc sFt|}||_tj|||_||_tjjd|d|_ ||_ dS)Nnone) reductionblank) super__init__rtorchnnLinearctc_lorCTCLossctc_lossr)selfrrrrrkwargseprojs __class__R/home/ubuntu/.local/lib/python3.10/site-packages/funasr/models/fun_asr_nano/ctc.pyr s  z CTC.__init__cCtj||ddS)zsoftmax of frame activations Args: Tensor hs_pad: 3d tensor (B, Tmax, eprojs) Returns: torch.Tensor: softmax applied 3d tensor (B, Tmax, odim) dim)Fsoftmaxrrhs_padrrrr z CTC.softmaxcCr)zlog_softmax of frame activations Args: Tensor hs_pad: 3d tensor (B, Tmax, eprojs) Returns: torch.Tensor: log softmax applied 3d tensor (B, Tmax, odim) rr)r log_softmaxrr!rrrr$*r#zCTC.log_softmaxcCr)zargmax of frame activations Args: torch.Tensor hs_pad: 3d tensor (B, Tmax, eprojs) Returns: torch.Tensor: argmax applied 2d tensor (B, Tmax) rr)rargmaxrr!rrrr%4r#z CTC.argmax)rTr) __name__ __module__ __qualname____doc__intfloatboolr r r$r% __classcell__rrrrrs&   r)rtorch.nn.functionalr functionalrModulerrrrrs