PaddlePaddle
diff --git a/‎paddle/fluid/pir/dialect/op_generator/ops_api_gen.py
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+4-2Lines changed: 4 additions & 2 deletions b/‎paddle/fluid/pir/dialect/op_generator/ops_api_gen.py
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+4-2Lines changed: 4 additions & 2 deletions
diff --git a/‎paddle/phi/api/yaml/fused_ops.yaml
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+13-3Lines changed: 13 additions & 3 deletions b/‎paddle/phi/api/yaml/fused_ops.yaml
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+13-3Lines changed: 13 additions & 3 deletions
diff --git a/‎paddle/phi/infermeta/fusion.cc
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+56-31Lines changed: 56 additions & 31 deletions b/‎paddle/phi/infermeta/fusion.cc
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+56-31Lines changed: 56 additions & 31 deletions
diff --git a/‎paddle/phi/infermeta/fusion.h
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+36-27Lines changed: 36 additions & 27 deletions b/‎paddle/phi/infermeta/fusion.h
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+36-27Lines changed: 36 additions & 27 deletions
diff --git a/‎paddle/phi/kernels/CMakeLists.txt
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+2-1Lines changed: 2 additions & 1 deletion b/‎paddle/phi/kernels/CMakeLists.txt
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+2-1Lines changed: 2 additions & 1 deletion
diff --git a/‎paddle/phi/kernels/autotune/cache.cc
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+3Lines changed: 3 additions & 0 deletions b/‎paddle/phi/kernels/autotune/cache.cc
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+3Lines changed: 3 additions & 0 deletions
diff --git a/‎paddle/phi/kernels/autotune/cache.h
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+3-2Lines changed: 3 additions & 2 deletions b/‎paddle/phi/kernels/autotune/cache.h
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+3-2Lines changed: 3 additions & 2 deletions
@@ -73,7 +73,8 @@
     'fused_embedding_eltwise_layernorm',
     'fused_fc_elementwise_layernorm',
     'fused_multi_transformer_xpu',
-    'fused_scale_bias_relu_conv_bnstats',
+    'fused_scale_bias_relu_conv_bn',
+    'fused_scale_bias_add_relu',
     'fusion_transpose_flatten_concat',
     'generate_sequence_xpu',
     'layer_norm_act_xpu',
@@ -106,7 +107,8 @@
     'embedding_grad_sparse',
     'fused_batch_norm_act_',
     'fused_bn_add_activation_',
-    'fused_scale_bias_relu_conv_bnstats',
+    'fused_scale_bias_relu_conv_bn',
+    'fused_scale_bias_add_relu',
     'memcpy',
     'print',
     'recv_v2',
 
@@ -206,14 +206,24 @@
   backward: fused_rotary_position_embedding_grad
   support_dygraph_mode : true
 
-- op : fused_scale_bias_relu_conv_bnstats
+- op : fused_scale_bias_add_relu
+  args : (Tensor x1, Tensor scale1, Tensor bias1, Tensor x2, Tensor scale2, Tensor bias2, bool fuse_dual, bool exhaustive_search)
+  optional : scale2, bias2
+  output : Tensor(y)
+  infer_meta :
+    func : FusedScaleBiasAddReluInferMeta
+  kernel :
+    func : fused_scale_bias_add_relu
+    data_type : x1
+
+- op : fused_scale_bias_relu_conv_bn
   args : (Tensor x, Tensor w, Tensor scale, Tensor bias, Tensor bn_scale, Tensor bn_bias, Tensor input_running_mean, Tensor input_running_var, int[] paddings, int[] dilations, int[] strides, str padding_algorithm, int groups, str data_format, float momentum, float epsilon, bool fuse_prologue, bool exhaustive_search, int64_t accumulation_count = 0)
   optional : scale, bias
   output : Tensor(out), Tensor(out_running_mean), Tensor(out_running_var), Tensor(saved_mean), Tensor(saved_var), Tensor(eq_scale), Tensor(eq_bias)
   infer_meta :
-    func : FusedScaleBiasReluConvBnstatsInferMeta
+    func : FusedScaleBiasReluConvBnInferMeta
   kernel :
-    func : fused_scale_bias_relu_conv_bnstats
+    func : fused_scale_bias_relu_conv_bn
     data_type : x
 
 - op : fusion_gru
 
@@ -1687,41 +1687,40 @@ void LayerNormActXPUInferMeta(const MetaTensor& x,
   y->set_layout(x.layout());
 }
 
-void FusedScaleBiasReluConvBnstatsInferMeta(
-    const MetaTensor& x,
-    const MetaTensor& w,
-    const MetaTensor& scale,
-    const MetaTensor& bias,
-    const MetaTensor& bn_scale,
-    const MetaTensor& bn_bias,
-    const MetaTensor& input_running_mean,
-    const MetaTensor& input_running_var,
-    const std::vector<int>& paddings,
-    const std::vector<int>& dilations,
-    const std::vector<int>& strides,
-    const std::string& padding_algorithm,
-    int groups,
-    const std::string& data_format,
-    float momentum,
-    float epsilon,
-    bool fuse_prologue,
-    bool exhaustive_search,
-    int64_t accumulation_count,
-    MetaTensor* out,
-    MetaTensor* out_running_mean,
-    MetaTensor* out_running_var,
-    MetaTensor* saved_mean,
-    MetaTensor* saved_var,
-    MetaTensor* eq_scale,
-    MetaTensor* eq_bias) {
+void FusedScaleBiasReluConvBnInferMeta(const MetaTensor& x,
+                                       const MetaTensor& w,
+                                       const MetaTensor& scale,
+                                       const MetaTensor& bias,
+                                       const MetaTensor& bn_scale,
+                                       const MetaTensor& bn_bias,
+                                       const MetaTensor& input_running_mean,
+                                       const MetaTensor& input_running_var,
+                                       const std::vector<int>& paddings,
+                                       const std::vector<int>& dilations,
+                                       const std::vector<int>& strides,
+                                       const std::string& padding_algorithm,
+                                       int groups,
+                                       const std::string& data_format,
+                                       float momentum,
+                                       float epsilon,
+                                       bool fuse_prologue,
+                                       bool exhaustive_search,
+                                       int64_t accumulation_count,
+                                       MetaTensor* out,
+                                       MetaTensor* out_running_mean,
+                                       MetaTensor* out_running_var,
+                                       MetaTensor* saved_mean,
+                                       MetaTensor* saved_var,
+                                       MetaTensor* eq_scale,
+                                       MetaTensor* eq_bias) {
   auto in_dims = x.dims();
   auto filter_dims = w.dims();
   // do some checks
   PADDLE_ENFORCE_EQ(
       in_dims.size(),
       4,
       phi::errors::InvalidArgument(
-          "The input of Op(FusedScaleBiasReluConvBnstats) should be a 4-D "
+          "The input of Op(FusedScaleBiasReluConvBn) should be a 4-D "
           "Tensor. But "
           "received: input's dimension is %u, input's shape is [%s].",
           in_dims.size(),
@@ -1732,7 +1731,7 @@ void FusedScaleBiasReluConvBnstatsInferMeta(
       filter_dims.size(),
       phi::errors::InvalidArgument(
           "The input's dimension and filter's dimension of "
-          "Op(FusedScaleBiasReluConvBnstats) should be equal. But received: "
+          "Op(FusedScaleBiasReluConvBn) should be equal. But received: "
           "the input's"
           " shape is [%s], "
           "the input's dimension is %d; the filter's shape is [%s],  "
@@ -1747,7 +1746,7 @@ void FusedScaleBiasReluConvBnstatsInferMeta(
       data_format,
       "NHWC",
       phi::errors::InvalidArgument(
-          "Operator(FusedScaleBiasReluConvBnstats) only supports data format "
+          "Operator(FusedScaleBiasReluConvBn) only supports data format "
           "of "
           "channel last (NHWC) now. But recieved: data_format = '%s'.",
           data_format));
@@ -1774,7 +1773,7 @@ void FusedScaleBiasReluConvBnstatsInferMeta(
       filter_dims[1] * groups,
       phi::errors::InvalidArgument(
           "The number of input's channels should be equal to filter's channels "
-          "* groups for Op(FusedScaleBiasReluConvBnstats). But received: the "
+          "* groups for Op(FusedScaleBiasReluConvBn). But received: the "
           "input's"
           " channels is %d, "
           "the input's shape is [%s]; the filter's channels is %d, the "
@@ -1821,6 +1820,32 @@ void FusedScaleBiasReluConvBnstatsInferMeta(
   eq_bias->set_dims(c_dims);
 }
 
+void FusedScaleBiasAddReluInferMeta(const MetaTensor& x1,
+                                    const MetaTensor& scale1,
+                                    const MetaTensor& bias1,
+                                    const MetaTensor& x2,
+                                    const MetaTensor& scale2,
+                                    const MetaTensor& bias2,
+                                    bool fuse_dual,
+                                    bool exhaustive_search,
+                                    MetaTensor* y) {
+  // check optional inputs
+  if (fuse_dual) {
+    bool has_scale2 = !!scale2;
+    bool has_bias2 = !!bias2;
+    PADDLE_ENFORCE(has_scale2 && has_bias2,
+                   phi::errors::InvalidArgument(
+                       "Argument scale2 and bias2 should be provided when "
+                       "fuse_dual is set, but got has_scale2=%d, has_bias2=%d, "
+                       "fuse_dual=%d.",
+                       has_scale2,
+                       has_bias2,
+                       fuse_dual));
+  }
+  // set output dims
+  y->set_dims(x1.dims());
+}
+
 void SqueezeExcitationInferMeta(const MetaTensor& x,
                                 const MetaTensor& filter,
                                 const MetaTensor& filter_max,
 
@@ -451,33 +451,42 @@ void LayerNormActXPUInferMeta(const MetaTensor& x,
                               float act_param,
                               MetaTensor* y);
 
-void FusedScaleBiasReluConvBnstatsInferMeta(
-    const MetaTensor& x,
-    const MetaTensor& w,
-    const MetaTensor& scale,
-    const MetaTensor& bias,
-    const MetaTensor& bn_scale,
-    const MetaTensor& bn_bias,
-    const MetaTensor& input_running_mean,
-    const MetaTensor& input_running_var,
-    const std::vector<int>& paddings,
-    const std::vector<int>& dilations,
-    const std::vector<int>& strides,
-    const std::string& padding_algorithm,
-    int groups,
-    const std::string& data_format,
-    float momentum,
-    float epsilon,
-    bool fuse_prologue,
-    bool exhaustive_search,
-    int64_t accumulation_count,
-    MetaTensor* out,
-    MetaTensor* out_running_mean,
-    MetaTensor* out_running_var,
-    MetaTensor* saved_mean,
-    MetaTensor* saved_var,
-    MetaTensor* eq_scale,
-    MetaTensor* eq_bias);
+void FusedScaleBiasReluConvBnInferMeta(const MetaTensor& x,
+                                       const MetaTensor& w,
+                                       const MetaTensor& scale,
+                                       const MetaTensor& bias,
+                                       const MetaTensor& bn_scale,
+                                       const MetaTensor& bn_bias,
+                                       const MetaTensor& input_running_mean,
+                                       const MetaTensor& input_running_var,
+                                       const std::vector<int>& paddings,
+                                       const std::vector<int>& dilations,
+                                       const std::vector<int>& strides,
+                                       const std::string& padding_algorithm,
+                                       int groups,
+                                       const std::string& data_format,
+                                       float momentum,
+                                       float epsilon,
+                                       bool fuse_prologue,
+                                       bool exhaustive_search,
+                                       int64_t accumulation_count,
+                                       MetaTensor* out,
+                                       MetaTensor* out_running_mean,
+                                       MetaTensor* out_running_var,
+                                       MetaTensor* saved_mean,
+                                       MetaTensor* saved_var,
+                                       MetaTensor* eq_scale,
+                                       MetaTensor* eq_bias);
+
+void FusedScaleBiasAddReluInferMeta(const MetaTensor& x1,
+                                    const MetaTensor& scale1,
+                                    const MetaTensor& bias1,
+                                    const MetaTensor& x2,
+                                    const MetaTensor& scale2,
+                                    const MetaTensor& bias2,
+                                    bool fuse_prologue,
+                                    bool exhaustive_search,
+                                    MetaTensor* y);
 
 void SqueezeExcitationInferMeta(const MetaTensor& x,
                                 const MetaTensor& filter,
 
@@ -108,7 +108,8 @@ endif()
 
 if(NOT WITH_CUDNN_FRONTEND)
   list(REMOVE_ITEM kernel_cu
-       "fusion/gpu/fused_scale_bias_relu_conv_bnstats_kernel.cu")
+       "fusion/gpu/fused_scale_bias_relu_conv_bn_kernel.cu"
+       "fusion/gpu/fused_scale_bias_add_relu_kernel.cu")
 endif()
 
 set(cc_search_pattern
 
@@ -52,6 +52,9 @@ std::string AlgorithmTypeString(int64_t algo_type) {
     return "scale_bias_relu_conv_bnstats";
   } else if (algo_type == static_cast<int64_t>(AlgorithmType::kBNFinalize)) {
     return "bn_finalize";
+  } else if (algo_type ==
+             static_cast<int64_t>(AlgorithmType::kScaleBiasAddRelu)) {
+    return "scale_bias_add_relu";
   }
 #endif
   return std::to_string(algo_type);
 
@@ -57,7 +57,8 @@ enum class AlgorithmType {
   kConvBackwardFilterV8 = 12,
   kScaleBiasReluConvBNstats = 13,
   kBNFinalize = 14,
-  kAlgorithmCount = 15
+  kScaleBiasAddRelu = 15,
+  kAlgorithmCount = 16
 #endif
 };
 
@@ -181,7 +182,7 @@ class AutoTuneCache {
       }
 #ifdef PADDLE_WITH_CUDNN_FRONTEND
     } else if (algo_type >= AlgorithmType::kConvForwardV8 &&
-               algo_type <= AlgorithmType::kBNFinalize) {
+               algo_type < AlgorithmType::kAlgorithmCount) {
       int64_t key = static_cast<int64_t>(algo_type);
       if (cudnn_v8_auto_tune_map_.find(key) == cudnn_v8_auto_tune_map_.end()) {
         CudnnFrontendPlanCache cache;