def forward(self, indices, offsets, dense_feature):
        r"""
        Args:
            indices (Tensor): a list of indices for all tables
            offsets (Tensor): a list of offsets for all tables
            dense_feature (Tensor): dense feature to be cat
        Returns:
            output shape of `(batch_size, feature_size)` which feature_size = emb_dim * (num of tables + 1).
        """
        return merged_embeddingbag_with_cat(
            self.weights,
            indices,
            offsets,
            dense_feature,
        )

        Args:
            indices (Tensor): a list of indices for all tables
            offsets (Tensor): a list of offsets for all tables
            dense_feature (Tensor): dense feature to be cat
        Returns:
            output shape of `(batch_size, feature_size)` which feature_size = emb_dim * (num of tables + 1).
        
intel_extension_for_pytorch/nn/modules/merged_embeddingbag.py