def _repeat_kv(self, hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
        """
        This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
        num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
        """
        batch, num_key_value_heads, slen, head_dim = hidden_states.shape
        if n_rep == 1:
            return hidden_states
        hidden_states = hidden_states[:, :, None, :, :].expand(
            batch, num_key_value_heads, n_rep, slen, head_dim
        )
        return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim)

        This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
        num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
        
intel_extension_for_pytorch/transformers/models/reference/fusions/mha_fusion.py