update

shixian.shi

2023-05-04 a6889a31700bf3d610712c7fb5edecd06f78f0bf

update

 funasr/models/e2e_asr_contextual_paraformer.py

@@ -280,8 +280,8 @@
        decoder_outs = self.decoder(
            encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, contextual_info=contextual_info
        ) 
        decoder_out, _, attn = decoder_outs[0], decoder_outs[1], decoder_outs[2]
        
        decoder_out, _ = decoder_outs[0], decoder_outs[1]
        '''
        if self.crit_attn_weight > 0 and attn.shape[-1] > 1:
            ideal_attn = ideal_attn + self.crit_attn_smooth / (self.crit_attn_smooth + 1.0)
            attn_non_blank = attn[:,:,:,:-1]
@@ -289,7 +289,9 @@
            loss_ideal = self.attn_loss(attn_non_blank.max(1)[0], ideal_attn_non_blank.to(attn.device))
        else:
            loss_ideal = None

        '''
        loss_ideal = None
        
        if decoder_out_1st is None:
            decoder_out_1st = decoder_out
        # 2. Compute attention loss