    def forward_latent(self, last_layer_feats, padding_mask, **kwargs):
        """
        Arguments
            features - [TxBxD] Acoustic feature with shape
            padding_mask - [BxT]     Padding Mask
        """
        if padding_mask is not None:
            feat_mask = (~padding_mask).to(last_layer_feats.dtype)
        else:
            feat_mask = None
        feat = self.linear(last_layer_feats)
        feat = fn_mean(feat, feat_mask)
        return feat
Arguments
features - [TxBxD] Acoustic feature with shape
padding_mask - [BxT]     Padding Mask
fairseq/models/wav2vec/wav2vec2_classification.py