def forward(
        self,
        src,
    ):
        """
        Arguments
        ----------
        src : torch.Tensor
            Tensor shape [B, L, N],
            where, B = Batchsize,
                   L = time points
                   N = number of filters
            The sequence to the encoder layer (required).
        src_mask : tensor
            The mask for the src sequence (optional).
        src_key_padding_mask : tensor
            The mask for the src keys per batch (optional).
        """
        output = self.mossformerM(src)
        output = self.norm(output)

        return output

        Arguments
        ----------
        src : torch.Tensor
            Tensor shape [B, L, N],
            where, B = Batchsize,
                   L = time points
                   N = number of filters
            The sequence to the encoder layer (required).
        src_mask : tensor
            The mask for the src sequence (optional).
        src_key_padding_mask : tensor
            The mask for the src keys per batch (optional).
        
clearvoice/clearvoice/models/mossformer2_se/mossformer2.py