def forward(self, memory_text: torch.Tensor, text_attention_mask: torch.Tensor):
        """

        Args:
            text_attention_mask: bs, num_token
            memory_text: bs, num_token, d_model

        Raises:
            RuntimeError: _description_

        Returns:
            output: bs, num_token, d_model
        """

        output = memory_text.transpose(0, 1)

        for layer in self.layers:
            output = layer(output, src_key_padding_mask=text_attention_mask)

        if self.norm is not None:
            output = self.norm(output)

        return output.transpose(0, 1)


        Args:
            text_attention_mask: bs, num_token
            memory_text: bs, num_token, d_model

        Raises:
            RuntimeError: _description_

        Returns:
            output: bs, num_token, d_model
        
groundingdino/models/GroundingDINO/transformer_vanilla.py