def _split_heads(self, fused_qkv: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
        """
        Split the last dimension into (num_heads, head_dim), results share same memory storage as `fused_qkv`

        Args:
            fused_qkv (`torch.tensor`, *required*): [batch_size, seq_length, num_heads * 3 * head_dim]

        Returns:
            query: [batch_size, seq_length, num_heads, head_dim] key: [batch_size, seq_length, num_heads, head_dim]
            value: [batch_size, seq_length, num_heads, head_dim]
        """
        if self.new_decoder_architecture:
            batch, seq_len, _ = fused_qkv.shape
            qkv = fused_qkv.view(batch, seq_len, -1, self.num_heads // self.num_kv_heads + 2, self.head_dim)
            query = qkv[:, :, :, :-2]
            key = qkv[:, :, :, [-2]]
            value = qkv[:, :, :, [-1]]
            key = torch.broadcast_to(key, query.shape)
            value = torch.broadcast_to(value, query.shape)

            query, key, value = [x.flatten(2, 3) for x in (query, key, value)]
            return query, key, value
        elif not self.multi_query:
            batch_size, seq_length, three_times_hidden_size = fused_qkv.shape
            fused_qkv = fused_qkv.view(batch_size, seq_length, self.num_heads, 3, self.head_dim)
            return fused_qkv[..., 0, :], fused_qkv[..., 1, :], fused_qkv[..., 2, :]
        else:
            batch_size, seq_length, three_times_hidden_size = fused_qkv.shape
            fused_qkv = fused_qkv.view(batch_size, seq_length, self.num_heads + 2, self.head_dim)
            return fused_qkv[..., :-2, :], fused_qkv[..., [-2], :], fused_qkv[..., [-1], :]

        Split the last dimension into (num_heads, head_dim), results share same memory storage as `fused_qkv`

        Args:
            fused_qkv (`torch.tensor`, *required*): [batch_size, seq_length, num_heads * 3 * head_dim]

        Returns:
            query: [batch_size, seq_length, num_heads, head_dim] key: [batch_size, seq_length, num_heads, head_dim]
            value: [batch_size, seq_length, num_heads, head_dim]
        
dpkd/transformers/src/transformers/models/falcon/modeling_falcon.py