def forward(
        self,
        hidden_states: torch.Tensor,
    ):
        """
        Args:
            hidden_states (`torch.Tensor` of shape `(batch, len_seq, dim_model)`):
                Hidden states before feed forward layer.
        """
        ln_outputs = self.layernorm_before_ffn(hidden_states)
        outputs = self.ffn(ln_outputs)
        if self.dropout is not None:
            outputs = self.dropout(outputs)
        hidden_states = hidden_states + outputs
        return hidden_states

        Args:
            hidden_states (`torch.Tensor` of shape `(batch, len_seq, dim_model)`):
                Hidden states before feed forward layer.
        
dpkd/transformers/src/transformers/models/cpmant/modeling_cpmant.py