add mha_kvcache (#261)

* add mha_kvcache

* repair gqa-api bug

csrc/models/llama/llama_attention.cpp

@@ -4,6 +4,7 @@
 #include "infinicore/nn/linear.hpp"
 #include "infinicore/nn/rope.hpp"
 #include "infinicore/ops.hpp"
+#include "infinicore/ops/mha_kvcache.hpp"
 #include "infinicore/ops/mha_varlen.hpp"
 #include "infinicore/ops/mul.hpp"
 
@@ -330,6 +331,23 @@ infinicore::Tensor LlamaAttention::forward_paged_(const infinicore::Tensor &hidd
                 std::nullopt,
                 scaling_);
         }
+    } else {
+        if (attention_backend_ == backends::AttentionBackend::FlashAttn) {
+            // FA2 decode path: flash::mha_fwd_kvcache
+            // In paged-attn mode, seq_len = actual batch_size (one query token per sequence).
+            // q_reshaped: [seq_len, num_heads, head_dim] → [seq_len, 1, num_heads, head_dim]
+            // k/v cache:  [num_blocks, num_kv_heads, block_size, head_dim]
+            //           → permute {0,2,1,3} → [num_blocks, block_size, num_kv_heads, head_dim]
+            auto q_for_fa = q_reshaped->view({seq_len, 1, num_attention_heads_, head_dim_});
+            auto attn_out_4d = infinicore::op::mha_kvcache(
+                q_for_fa,
+                k_total->permute({0, 2, 1, 3}),  // [num_blocks, block_size, num_kv_heads, head_dim]
+                v_total->permute({0, 2, 1, 3}),
+                total_sequence_lengths.value(),  // [seq_len] int32 (one entry per sequence)
+                block_tables.value(),            // [seq_len, max_num_blocks_per_seq] int32
+                std::nullopt,
+                scaling_);
+            attn_output = attn_out_4d->view({seq_len, num_attention_heads_, head_dim_});
         } else {
             infinicore::op::paged_attention_(
                 attn_output,
@@ -341,6 +359,8 @@ infinicore::Tensor LlamaAttention::forward_paged_(const infinicore::Tensor &hidd
                 std::nullopt,
                 scaling_);
         }
+    }
+    
 
     // 7. Project output
     attn_output