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diff --git a/‎paddle/phi/api/yaml/fused_ops.yaml
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+14-2Lines changed: 14 additions & 2 deletions b/‎paddle/phi/api/yaml/fused_ops.yaml
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+14-2Lines changed: 14 additions & 2 deletions
diff --git a/‎paddle/phi/infermeta/fusion.cc
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+13Lines changed: 13 additions & 0 deletions b/‎paddle/phi/infermeta/fusion.cc
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+13Lines changed: 13 additions & 0 deletions
diff --git a/‎paddle/phi/infermeta/fusion.h
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+8Lines changed: 8 additions & 0 deletions b/‎paddle/phi/infermeta/fusion.h
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+8Lines changed: 8 additions & 0 deletions
diff --git a/‎paddle/phi/kernels/CMakeLists.txt
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+1Lines changed: 1 addition & 0 deletions b/‎paddle/phi/kernels/CMakeLists.txt
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diff --git a/‎paddle/phi/kernels/fusion/gpu/blha_get_max_len.cu
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+68Lines changed: 68 additions & 0 deletions b/‎paddle/phi/kernels/fusion/gpu/blha_get_max_len.cu
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+68Lines changed: 68 additions & 0 deletions
diff --git a/‎paddle/phi/kernels/fusion/gpu/block_attn.h
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-17Lines changed: 0 additions & 17 deletions b/‎paddle/phi/kernels/fusion/gpu/block_attn.h
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-17Lines changed: 0 additions & 17 deletions
@@ -32,17 +32,29 @@
     func : addcmul_xpu
     data_type : x
 
+- op : blha_get_max_len
+  args : (Tensor seq_lens_encoder, Tensor seq_lens_decoder, Tensor batch_size)
+  output : Tensor(max_enc_len_this_time), Tensor(max_dec_len_this_time)
+  infer_meta :
+    func : BlhaGetMaxLenInferMeta
+  kernel :
+    func : blha_get_max_len
+    data_type : seq_lens_encoder
+  support_dygraph_mode : true
+
 - op : block_multihead_attention_
-  args : (Tensor qkv, Tensor key_cache, Tensor value_cache, Tensor seq_lens_encoder, Tensor seq_lens_decoder, Tensor seq_lens_this_time, Tensor padding_offsets, Tensor cum_offsets, Tensor cu_seqlens_q, Tensor cu_seqlens_k, Tensor block_tables, Tensor pre_key_cache, Tensor pre_value_cache, Tensor rope_emb, Tensor mask,  Tensor tgt_mask, Tensor cache_k_quant_scales, Tensor cache_v_quant_scales, Tensor cache_k_dequant_scales, Tensor cache_v_dequant_scales, Tensor qkv_out_scale, Tensor qkv_bias, Tensor out_shift, Tensor out_smooth, int max_seq_len, int block_size, bool use_neox_style, bool dynamic_cachekv_quant=false, int quant_round_type=1, float quant_max_bound=127.0, float quant_min_bound=-127.0, float out_scale=-1, str compute_dtype = "default")
+  args : (Tensor qkv, Tensor key_cache, Tensor value_cache, Tensor seq_lens_encoder, Tensor seq_lens_decoder, Tensor seq_lens_this_time, Tensor padding_offsets, Tensor cum_offsets, Tensor cu_seqlens_q, Tensor cu_seqlens_k, Tensor block_tables, Tensor pre_key_cache, Tensor pre_value_cache, Tensor rope_emb, Tensor mask,  Tensor tgt_mask, Tensor cache_k_quant_scales, Tensor cache_v_quant_scales, Tensor cache_k_dequant_scales, Tensor cache_v_dequant_scales, Tensor qkv_out_scale, Tensor qkv_bias, Tensor out_shift, Tensor out_smooth, Tensor max_enc_len_this_time, Tensor max_dec_len_this_time, int max_seq_len, int block_size, bool use_neox_style, bool dynamic_cachekv_quant=false, int quant_round_type=1, float quant_max_bound=127.0, float quant_min_bound=-127.0, float out_scale=-1, str compute_dtype = "default")
   output : Tensor(fmha_out), Tensor(qkv_out), Tensor(key_cache_out), Tensor(value_cache_out)
   infer_meta :
     func : BlockMultiheadAttentionInferMeta
   kernel :
     func : block_multihead_attention
     data_type : qkv
-  optional : pre_key_cache, pre_value_cache, rope_emb, mask, tgt_mask, cache_k_quant_scales, cache_v_quant_scales, cache_k_dequant_scales, cache_v_dequant_scales, qkv_out_scale, qkv_bias, out_shift, out_smooth
+  optional : pre_key_cache, pre_value_cache, rope_emb, mask, tgt_mask, cache_k_quant_scales, cache_v_quant_scales, cache_k_dequant_scales, cache_v_dequant_scales, qkv_out_scale, qkv_bias, out_shift, out_smooth, max_enc_len_this_time, max_dec_len_this_time
   inplace : (qkv -> qkv_out), (key_cache -> key_cache_out), (value_cache -> value_cache_out)
   support_dygraph_mode : true
+  data_transform :
+    skip_transform : max_enc_len_this_time, max_dec_len_this_time
 
 - op : bn_act_xpu
   args : (Tensor x, Tensor mean, Tensor variance, Tensor scale, Tensor bias, float momentum, float epsilon, str data_format, int act_type)
 
@@ -232,6 +232,17 @@ void FusedMultiTransformerInferMeta(
   out->set_dims(x.dims());
 }
 
+void BlhaGetMaxLenInferMeta(const MetaTensor& seq_lens_encoder,
+                            const MetaTensor& seq_lens_decoder,
+                            const MetaTensor& batch_size,
+                            MetaTensor* max_enc_len_this_time,
+                            MetaTensor* max_dec_len_this_time) {
+  max_enc_len_this_time->set_dims({1});
+  max_enc_len_this_time->set_dtype(phi::DataType::INT32);
+  max_dec_len_this_time->set_dims({1});
+  max_dec_len_this_time->set_dtype(phi::DataType::INT32);
+}
+
 void BlockMultiheadAttentionInferMeta(const MetaTensor& qkv,
                                       const MetaTensor& key_cache,
                                       const MetaTensor& value_cache,
@@ -256,6 +267,8 @@ void BlockMultiheadAttentionInferMeta(const MetaTensor& qkv,
                                       const MetaTensor& qkv_bias,
                                       const MetaTensor& out_shift,
                                       const MetaTensor& out_smooth,
+                                      const MetaTensor& max_enc_len_this_time,
+                                      const MetaTensor& max_dec_len_this_time,
                                       int max_seq_len,
                                       int block_size,
                                       bool use_neox_style,
 
@@ -77,6 +77,12 @@ void GroupNormalizeSiluXPUInferMeta(const MetaTensor& x,
                                     float epsilon,
                                     MetaTensor* out);
 
+void BlhaGetMaxLenInferMeta(const MetaTensor& seq_lens_encoder,
+                            const MetaTensor& seq_lens_decoder,
+                            const MetaTensor& batch_size,
+                            MetaTensor* max_enc_len_this_time,
+                            MetaTensor* max_dec_len_this_time);
+
 void BlockMultiheadAttentionInferMeta(const MetaTensor& qkv,
                                       const MetaTensor& key_cache,
                                       const MetaTensor& value_cache,
@@ -101,6 +107,8 @@ void BlockMultiheadAttentionInferMeta(const MetaTensor& qkv,
                                       const MetaTensor& qkv_bias,
                                       const MetaTensor& out_shift,
                                       const MetaTensor& out_smooth,
+                                      const MetaTensor& max_enc_len_this_time,
+                                      const MetaTensor& max_dec_len_this_time,
                                       int max_seq_len,
                                       int block_size,
                                       bool use_neox_style,
 
@@ -215,6 +215,7 @@ if(WITH_ROCM)
     "gpu/qr_kernel.cu"
     "gpu/svd_kernel.cu"
     "gpudnn/mha_cudnn_frontend.cu"
+    "fusion/gpu/blha_get_max_len.cu"
     "fusion/gpu/block_multi_head_attention_kernel.cu"
     "fusion/gpu/fused_bn_add_activation_grad_kernel.cu"
     "fusion/gpu/fused_bn_add_activation_kernel.cu"
 
@@ -0,0 +1,68 @@
+// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     https://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/flash_attn_kernel.h"
+#include "paddle/phi/kernels/funcs/broadcast_function.h"
+#include "paddle/phi/kernels/funcs/elementwise_functor.h"
+#include "paddle/phi/kernels/fusion/cutlass/variable_length_memory_efficient_attention.h"
+#include "paddle/phi/kernels/fusion/gpu/block_attn.h"
+#include "paddle/phi/kernels/gpu/flash_attn_utils.h"
+#include "paddle/phi/kernels/memcpy_kernel.h"
+#include "paddle/utils/none.h"
+
+namespace phi {
+namespace fusion {
+
+void GetMaxLenTensor(const phi::GPUContext& dev_ctx,
+                     const phi::DenseTensor& seq_lens_tensor,
+                     const phi::DenseTensor& batch_size,
+                     DenseTensor* out) {
+  phi::DenseTensor max_len_tensor;
+  max_len_tensor.Resize({{1}});
+  auto* max_len_tensor_data = dev_ctx.template Alloc<int>(
+      &max_len_tensor, max_len_tensor.numel() * sizeof(int));
+  const int bsz = batch_size.dims()[0];
+  constexpr int blockSize = 128;
+  int max_len_cpu = 0;
+  GetMaxLenKernel<blockSize><<<1, blockSize, 0, dev_ctx.stream()>>>(
+      seq_lens_tensor.data<int>(), max_len_tensor.data<int>(), bsz);
+  MemcpyD2HKernel(dev_ctx, max_len_tensor, 0, out);
+}
+
+template <typename T, typename Context>
+void BlhaGetMaxLenKernel(const Context& dev_ctx,
+                         const DenseTensor& seq_lens_encoder,
+                         const DenseTensor& seq_lens_decoder,
+                         const phi::DenseTensor& batch_size,
+                         DenseTensor* max_enc_len_this_time,
+                         DenseTensor* max_dec_len_this_time) {
+  // decoder
+  max_dec_len_this_time->Resize({{1}});
+  GetMaxLenTensor(dev_ctx, seq_lens_decoder, batch_size, max_dec_len_this_time);
+
+  // encoder
+  max_enc_len_this_time->Resize({{1}});
+  GetMaxLenTensor(dev_ctx, seq_lens_encoder, batch_size, max_enc_len_this_time);
+}
+}  // namespace fusion
+}  // namespace phi
+
+PD_REGISTER_KERNEL(blha_get_max_len,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::fusion::BlhaGetMaxLenKernel,
+                   int,
+                   int64_t) {}
@@ -2717,23 +2717,6 @@ __global__ void GetMaxLenKernel(const int *seq_lens,
   }
 }
 
-int GetMaxLen(const phi::GPUContext &dev_ctx,
-              const phi::DenseTensor &seq_lens_tensor,
-              phi::DenseTensor *max_len_tensor,
-              const int batch_size) {
-  constexpr int blockSize = 128;
-  int max_len_cpu = 0;
-  GetMaxLenKernel<blockSize><<<1, blockSize, 0, dev_ctx.stream()>>>(
-      seq_lens_tensor.data<int>(), max_len_tensor->data<int>(), batch_size);
-  memory_utils::Copy(phi::CPUPlace(),
-                     &max_len_cpu,
-                     dev_ctx.GetPlace(),
-                     max_len_tensor->data<int>(),
-                     sizeof(int),
-                     dev_ctx.stream());
-  return max_len_cpu;
-}
-
 template <typename T, int VecSize>
 __global__ void InitOutValueKernel(T *output_data,
                                    const int64_t numel,