diff --git a/paddle/fluid/framework/new_executor/new_executor_defs.cc b/paddle/fluid/framework/new_executor/new_executor_defs.cc
index 6492538c6084d36968c02f1ddf97f57e187a8773..8ee7065368c2181475e233f5e9dcbd8e828dea49 100644
--- a/paddle/fluid/framework/new_executor/new_executor_defs.cc
+++ b/paddle/fluid/framework/new_executor/new_executor_defs.cc
@@ -117,7 +117,7 @@ bool InterpretercoreInferShapeContext::HasOutputs(const std::string& name,
 }
 
 AttrReader InterpretercoreInferShapeContext::Attrs() const {
-  return AttrReader(op_.Attrs());
+  return AttrReader(op_.Attrs(), op_.RuntimeAttrs());
 }
 
 std::vector<std::string> InterpretercoreInferShapeContext::Inputs(
diff --git a/paddle/fluid/framework/op_registry.cc b/paddle/fluid/framework/op_registry.cc
index a5ce5b704921b7a256fa094d6b0a20f66b5fdba8..a60563620ad651ca772328b5e62e8d1aa8dea9fc 100644
--- a/paddle/fluid/framework/op_registry.cc
+++ b/paddle/fluid/framework/op_registry.cc
@@ -65,7 +65,15 @@ std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
     op_base = std::unique_ptr<OperatorBase>(
         info.Creator()(type, inputs, outputs, attrs));
   }
-  op_base->SetRuntimeAttributeMap(runtime_attrs);
+  const auto& extra_attr_checkers =
+      operators::ExtraInfoUtils::Instance().GetExtraAttrsChecker(type);
+  if (!extra_attr_checkers.empty()) {
+    auto op_runtime_attr_map = runtime_attrs;
+    for (const auto& checker : extra_attr_checkers) {
+      checker(&op_runtime_attr_map, false);
+    }
+    op_base->SetRuntimeAttributeMap(op_runtime_attr_map);
+  }
   return op_base;
 }
 
diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc
index 04d51872852a7cf11dff9a0ae0e90a7e9e37d4e1..00a499350044903c0c987240ae4cedda5c385bc2 100644
--- a/paddle/fluid/framework/operator.cc
+++ b/paddle/fluid/framework/operator.cc
@@ -767,7 +767,9 @@ class RuntimeInferShapeContext : public InferShapeContext {
     }
   }
 
-  AttrReader Attrs() const override { return AttrReader(op_.Attrs()); }
+  AttrReader Attrs() const override {
+    return AttrReader(op_.Attrs(), op_.RuntimeAttrs());
+  }
 
   std::vector<std::string> Inputs(const std::string& name) const override {
     return op_.Inputs(name);
diff --git a/paddle/fluid/operators/abs_op.cc b/paddle/fluid/operators/abs_op.cc
index f0adfb10a9fba3020637abff4c2108c814a8c01c..465637f3ed63e773d37abb8e04a142cd8be7fa83 100644
--- a/paddle/fluid/operators/abs_op.cc
+++ b/paddle/fluid/operators/abs_op.cc
@@ -54,15 +54,6 @@ class AbsOpMaker : public framework::OpProtoAndCheckerMaker {
   void Make() override {
     AddInput("X", "(Tensor), The input tensor of abs op.");
     AddOutput("Out", "(Tensor), The output tensor of abs op.");
-    AddAttr<bool>("use_mkldnn",
-                  "(bool, default false) Only used in mkldnn kernel")
-        .SetDefault(false)
-        .AsExtra();
-    AddAttr<bool>("use_cudnn",
-                  "(bool, default false) Only used in cudnn kernel, need "
-                  "install cudnn")
-        .SetDefault(false)
-        .AsExtra();
     AddComment(R"DOC(
 Abs Operator.
 
diff --git a/paddle/fluid/operators/addmm_op.cc b/paddle/fluid/operators/addmm_op.cc
index c54e6924c1ae8650aa469b8dc53266f2bc01b2d0..8642d572e2d2720703b2500dbeae324b26411e2b 100644
--- a/paddle/fluid/operators/addmm_op.cc
+++ b/paddle/fluid/operators/addmm_op.cc
@@ -72,10 +72,6 @@ class AddMMOpMaker : public framework::OpProtoAndCheckerMaker {
     AddInput("X", "(Tensor), The first input tensor for mul.");
     AddInput("Y", "(Tensor), The second input tensor for mul.");
     AddOutput("Out", "(Tensor), The output tensor of addmm op.");
-    AddAttr<bool>("use_mkldnn",
-                  "(bool, default false) Only used in mkldnn kernel")
-        .SetDefault(false)
-        .AsExtra();
     AddAttr<float>("Alpha", "coefficient of x*y.").SetDefault(1.0f);
     AddAttr<float>("Beta", "coefficient of input.").SetDefault(1.0f);
     AddComment(R"DOC(
diff --git a/paddle/fluid/operators/affine_grid_op.cc b/paddle/fluid/operators/affine_grid_op.cc
index 6eecb5e6b3e86427c36437598d2f9842b80f9920..a459196b7611dfbb7a0af1332fabc23b2f36523b 100644
--- a/paddle/fluid/operators/affine_grid_op.cc
+++ b/paddle/fluid/operators/affine_grid_op.cc
@@ -158,11 +158,6 @@ class AffineGridOpMaker : public framework::OpProtoAndCheckerMaker {
              "(Tensor) The shape of target image with format [N, C, H, W].")
         .AsDispensable();
     AddOutput("Output", "(Tensor) Output Tensor with shape [N, H, W, 2].");
-    AddAttr<bool>(
-        "use_cudnn",
-        "(bool, default false) Only used in cudnn kernel, need install cudnn")
-        .SetDefault(true)
-        .AsExtra();
     AddAttr<bool>("align_corners",
                   "(bool, default false) Whether to align the corners of input"
                   "and output.")
diff --git a/paddle/fluid/operators/angle_op.cc b/paddle/fluid/operators/angle_op.cc
index e787feb7dab943b37a71a697d65553034676c6a2..5c18f4c6fcc7df1753dc7020a91e71e1151e565c 100644
--- a/paddle/fluid/operators/angle_op.cc
+++ b/paddle/fluid/operators/angle_op.cc
@@ -39,15 +39,6 @@ class AngleOpMaker : public framework::OpProtoAndCheckerMaker {
   void Make() override {
     AddInput("X", "(Tensor), The input tensor of angle op.");
     AddOutput("Out", "(Tensor), The output tensor of angle op.");
-    AddAttr<bool>("use_mkldnn",
-                  "(bool, default false) Only used in mkldnn kernel")
-        .SetDefault(false)
-        .AsExtra();
-    AddAttr<bool>("use_cudnn",
-                  "(bool, default false) Only used in cudnn kernel, need "
-                  "install cudnn")
-        .SetDefault(false)
-        .AsExtra();
     AddComment(R"DOC(
 Angle Operator.
 
diff --git a/paddle/fluid/operators/batch_norm_op.cc b/paddle/fluid/operators/batch_norm_op.cc
index 9ad55c21f10254b4e5122a45dddec4e973714843..a4a3f3cd2b054d09c56e5c0b50e47c5c589c90ed 100644
--- a/paddle/fluid/operators/batch_norm_op.cc
+++ b/paddle/fluid/operators/batch_norm_op.cc
@@ -293,14 +293,6 @@ void BatchNormOpMaker::Make() {
             "NHWC kernel")
       .AsDispensable()
       .AsExtra();
-  AddAttr<bool>("use_mkldnn",
-                "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<bool>("fuse_with_relu",
-                "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
   AddAttr<bool>("use_global_stats",
                 "(bool, default false) Whether to use global mean and "
                 "variance. In inference or test mode, set use_global_stats "
diff --git a/paddle/fluid/operators/clip_op.cc b/paddle/fluid/operators/clip_op.cc
index ee632c77f19dcde872bcee89a10f78de206319ef..7994dacf08794f1d6f9c8e0d6397ee0b73b9676d 100644
--- a/paddle/fluid/operators/clip_op.cc
+++ b/paddle/fluid/operators/clip_op.cc
@@ -64,16 +64,6 @@ class ClipOpMaker : public framework::OpProtoAndCheckerMaker {
         "input(x)");
     AddAttr<AttrType>("min", "float number, the minimum value to clip by.");
     AddAttr<AttrType>("max", "float number, the maximum value to clip by.");
-    AddAttr<bool>("use_mkldnn",
-                  "(bool, default false) Only used in mkldnn kernel")
-        .SetDefault(false)
-        .AsExtra();
-    AddAttr<std::string>(
-        "mkldnn_data_type",
-        "(string, default \"float32\"). Data type of mkldnn kernel")
-        .SetDefault("float32")
-        .InEnum({"float32", "bfloat16"})
-        .AsExtra();
     AddComment(R"DOC(
 Clip Operator.
 
diff --git a/paddle/fluid/operators/concat_op.cc b/paddle/fluid/operators/concat_op.cc
index 75dbb9b037944bdc7294a207f8b870353fd9edd1..7c3a8103e1dbb2a4207d8b5dbf6b24e6178b2f07 100644
--- a/paddle/fluid/operators/concat_op.cc
+++ b/paddle/fluid/operators/concat_op.cc
@@ -81,11 +81,6 @@ class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
   void Make() override {
     AddInput("X", "Input tensors of concat operator.").AsDuplicable();
     AddOutput("Out", "Output tensor of concat operator.");
-    AddAttr<bool>(
-        "use_mkldnn",
-        "(bool, default false) Indicates if MKL-DNN kernel will be used")
-        .SetDefault(false)
-        .AsExtra();
     AddAttr<int>("axis",
                  "The axis along which the input tensors will be concatenated."
                  "The axis could also be negative numbers. Negative axis is "
@@ -99,18 +94,6 @@ class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
              "It has higher priority than Attr(axis). "
              "The shape of AxisTensor must be [1].")
         .AsDispensable();
-    AddAttr<bool>(
-        "use_quantizer",
-        "(bool, default false) "
-        "This parameter is no longer used. Use 'mkldnn_data_type' instead.")
-        .SetDefault(false)
-        .AsExtra();
-    AddAttr<std::string>(
-        "mkldnn_data_type",
-        "(string, default \"float32\"). Data type of mkldnn kernel")
-        .SetDefault("float32")
-        .InEnum({"float32", "int8", "bfloat16"})
-        .AsExtra();
     AddComment(R"DOC(
 Concat Operator.
 
diff --git a/paddle/fluid/operators/conv_op.cc b/paddle/fluid/operators/conv_op.cc
index ab222f3cb36c1a9cec2fb68761a5d3273ebc3796..d9c1332191ac75017cb84e8526eeefc02497e9e4 100644
--- a/paddle/fluid/operators/conv_op.cc
+++ b/paddle/fluid/operators/conv_op.cc
@@ -285,11 +285,6 @@ framework::OpKernelType ConvOp::GetKernelTypeForVar(
 }
 
 void Conv2DOpMaker::Make() {
-  AddAttr<bool>("is_test",
-                "(bool, default false) Set to true for inference only, false "
-                "for training. Some layers may run faster when this is true.")
-      .SetDefault(false)
-      .AsExtra();
   AddInput("Input",
            "(Tensor) The input tensor of convolution operator. "
            "The format of input tensor is NCHW or NHWC, where N is batch size, "
@@ -356,22 +351,6 @@ void Conv2DOpMaker::Make() {
       "the input will be transformed automatically. ")
       .SetDefault("NCHW");
   // TODO(dzhwinter): need to registered layout transform function
-  AddAttr<int>("workspace_size_MB",
-               "Only used in cudnn kernel. Need set use_cudnn to true."
-               "workspace size for cudnn, in MB, "
-               "workspace is a section of GPU memory which will be "
-               "allocated/freed each time the operator runs, larger "
-               "workspace size can increase performance but also requires "
-               "better hardware. This size should be chosen carefully.")
-      .SetDefault(platform::GetDefaultConvWorkspaceSizeLimitMB())
-      .AsExtra();
-  AddAttr<bool>("exhaustive_search",
-                "(bool, default false) cuDNN has many algorithm to calculation "
-                "convolution, whether enable exhaustive search "
-                "for cuDNN convolution or not, default is False.")
-      .SetDefault(false)
-      .AsExtra();
-
   AddComment(R"DOC(
 Convolution Operator.
 
@@ -403,12 +382,18 @@ $$
   Apply();
 }
 
+class DepthwiseConv2DOpMaker : public Conv2DOpMaker {
+ protected:
+  void Apply() override {
+    AddAttr<bool>(
+        "use_cudnn",
+        "(bool, default false) Only used in cudnn kernel, need install cudnn")
+        .SetDefault(false)
+        .AsExtra();
+  }
+};
+
 void Conv3DOpMaker::Make() {
-  AddAttr<bool>("is_test",
-                "(bool, default false) Set to true for inference only, false "
-                "for training. Some layers may run faster when this is true.")
-      .SetDefault(false)
-      .AsExtra();
   AddInput(
       "Input",
       "(Tensor) The input tensor of convolution operator. "
@@ -465,47 +450,6 @@ void Conv3DOpMaker::Make() {
                             "dilations(d_dilation, h_dilation, w_dilation) of "
                             "convolution operator.")
       .SetDefault({1, 1, 1});
-  AddAttr<bool>(
-      "use_cudnn",
-      "(bool, default false) Only used in cudnn kernel, need install cudnn")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<bool>("use_mkldnn",
-                "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<std::string>(
-      "mkldnn_data_type",
-      "(string, default \"float32\"). Data type of mkldnn kernel")
-      .SetDefault("float32")
-      .InEnum({"float32", "int8", "bfloat16"})
-      .AsExtra();
-  AddAttr<bool>("fuse_relu", "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<std::string>("fuse_activation",
-                       "(string, default \"\") Only used in mkldnn kernel")
-      .SetDefault("")
-      .AsExtra();
-  AddAttr<float>("fuse_alpha",
-                 "(float, default 0.0) Only used in mkldnn kernel")
-      .SetDefault(0.0f)
-      .AsExtra();
-  AddAttr<float>("fuse_beta", "(float, default 0.0) Only used in mkldnn kernel")
-      .SetDefault(0.0f)
-      .AsExtra();
-  AddAttr<bool>(
-      "use_addto",
-      "(bool, default false) If use addto strategy or not, only used in "
-      "cudnn kernel")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<bool>("fuse_residual_connection",
-                "(bool, default false) Only used in mkldnn kernel. Used "
-                "whenever convolution output is as an input to residual "
-                "connection.")
-      .SetDefault(false)
-      .AsExtra();
   AddAttr<std::string>(
       "data_format",
       "(string, default NCDHW) Only used in "
@@ -513,25 +457,6 @@ void Conv3DOpMaker::Make() {
       "Defaults to \"NDHWC\". Specify the data format of the output data, "
       "the input will be transformed automatically. ")
       .SetDefault("NCDHW");
-  AddAttr<bool>("force_fp32_output",
-                "(bool, default false) Only used in mkldnn INT8 kernel")
-      .SetDefault(false)
-      .AsExtra();
-  // TODO(dzhwinter): need to registered layout transform function
-  AddAttr<int>("workspace_size_MB",
-               "Only used in cudnn kernel. workspace size for cudnn, in MB, "
-               "workspace is a section of GPU memory which will be "
-               "allocated/freed each time the operator runs, larger "
-               "workspace size can increase performance but also requires "
-               "better hardware. This size should be chosen carefully.")
-      .SetDefault(platform::GetDefaultConvWorkspaceSizeLimitMB())
-      .AsExtra();
-  AddAttr<bool>("exhaustive_search",
-                "(bool, default false) cuDNN has many algorithm to calculation "
-                "convolution, whether enable exhaustive search "
-                "for cuDNN convolution or not, default is False.")
-      .SetDefault(false)
-      .AsExtra();
   AddComment(R"DOC(
 Convolution3D Operator.
 
@@ -811,7 +736,7 @@ REGISTER_OPERATOR(conv2d_grad_grad, ops::ConvOpDoubleGrad);
 // depthwise convolution op
 REGISTER_OPERATOR(depthwise_conv2d,
                   ops::ConvOp,
-                  ops::Conv2DOpMaker,
+                  ops::DepthwiseConv2DOpMaker,
                   ops::ConvOpInferVarType,
                   ops::Conv2DGradMaker<paddle::framework::OpDesc>,
                   ops::Conv2DGradMaker<paddle::imperative::OpBase>);
diff --git a/paddle/fluid/operators/conv_transpose_op.cc b/paddle/fluid/operators/conv_transpose_op.cc
index 3205d5b353887c21f6029c1b4e5dc1c55437cd53..56875c2d433e1a0a444b9b3be8cc69b8728a4e73 100644
--- a/paddle/fluid/operators/conv_transpose_op.cc
+++ b/paddle/fluid/operators/conv_transpose_op.cc
@@ -91,11 +91,6 @@ framework::OpKernelType ConvTransposeOp::GetKernelTypeForVar(
 }
 
 void Conv2DTransposeOpMaker::Make() {
-  AddAttr<bool>("is_test",
-                "(bool, default false) Set to true for inference only, false "
-                "for training. Some layers may run faster when this is true.")
-      .SetDefault(false)
-      .AsExtra();
   AddInput("Input",
            "(Tensor) The input tensor of convolution transpose operator. "
            "The format of input tensor is NCHW or NHWC. Where N is batch size, "
@@ -146,40 +141,6 @@ void Conv2DTransposeOpMaker::Make() {
       "(vector<int> default:{0, 0}), the paddings(h_pad, w_pad) of convolution "
       "transpose operator.")
       .SetDefault({0, 0});
-  AddAttr<bool>(
-      "use_cudnn",
-      "(bool, default false) Only used in cudnn kernel, need install cudnn")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<bool>("use_mkldnn",
-                "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<bool>("force_fp32_output",
-                "(bool, default false) Force BF16 kernel output FP32, only "
-                "used in MKL-DNN BF16")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<std::string>(
-      "mkldnn_data_type",
-      "(string, default \"float32\"). Data type of mkldnn kernel")
-      .SetDefault("float32")
-      .InEnum({"float32", "bfloat16"})
-      .AsExtra();
-  AddAttr<bool>("fuse_relu", "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<std::string>("fuse_activation",
-                       "(string, default \"\") Only used in mkldnn kernel")
-      .SetDefault("")
-      .AsExtra();
-  AddAttr<float>("fuse_alpha",
-                 "(float, default 0.0) Only used in mkldnn kernel")
-      .SetDefault(0.0f)
-      .AsExtra();
-  AddAttr<float>("fuse_beta", "(float, default 0.0) Only used in mkldnn kernel")
-      .SetDefault(0.0f)
-      .AsExtra();
   AddAttr<std::string>(
       "data_format",
       "(string, default NCHW) Only used in "
@@ -193,14 +154,6 @@ void Conv2DTransposeOpMaker::Make() {
       "\"SAME\",\"VALID\". Set to \"EXPLICIT\" for explicit padding. "
       "Set to \"SAME\" or \"VALID\" for algorithm of padding. ")
       .SetDefault("EXPLICIT");
-  AddAttr<int>("workspace_size_MB",
-               "Used in cudnn kernel only. workspace size for cudnn, in MB, "
-               "workspace is a section of GPU memory which will be "
-               "allocated/freed each time the operator runs, larger "
-               "workspace size can increase performance but also requires "
-               "better hardward. This size should be carefully set.")
-      .SetDefault(platform::GetDefaultConvWorkspaceSizeLimitMB())
-      .AsExtra();
   AddComment(R"DOC(
 Convolution2D Transpose Operator.
 
@@ -280,15 +233,6 @@ void Conv3DTransposeOpMaker::Make() {
                "(int default:1), the groups number of the convolution3d "
                "transpose operator. ")
       .SetDefault(1);
-  AddAttr<bool>(
-      "use_cudnn",
-      "(bool, default false) Only used in cudnn kernel, need install cudnn")
-      .SetDefault(false)
-      .AsExtra();
-  AddAttr<bool>("use_mkldnn",
-                "(bool, default false) Only used in mkldnn kernel")
-      .SetDefault(false)
-      .AsExtra();
   AddAttr<std::string>(
       "data_format",
       "(string, default NCHW) Only used in "
@@ -302,14 +246,6 @@ void Conv3DTransposeOpMaker::Make() {
       "\"SAME\",\"VALID\". Set to \"EXPLICIT\" for explicit padding. "
       "Set to \"SAME\" or \"VALID\" for algorithm of padding. ")
       .SetDefault("EXPLICIT");
-  AddAttr<int>("workspace_size_MB",
-               "Used in cudnn kernel only. workspace size for cudnn, in MB, "
-               "workspace is a section of GPU memory which will be "
-               "allocated/freed each time the operator runs, larger "
-               "workspace size can increase performance but also requires "
-               "better hardward. This size should be carefully set.")
-      .SetDefault(platform::GetDefaultConvWorkspaceSizeLimitMB())
-      .AsExtra();
   AddComment(R"DOC(
 Convolution3D Transpose Operator.
 
diff --git a/paddle/phi/api/yaml/api_compat.yaml b/paddle/phi/api/yaml/api_compat.yaml
index e2d714e3620285591f4d9398ff6b8017d43f5678..912d63a776b43ec04660b91617fca781ca3ea6ca 100644
--- a/paddle/phi/api/yaml/api_compat.yaml
+++ b/paddle/phi/api/yaml/api_compat.yaml
@@ -1,7 +1,22 @@
-# - api : conv3d_transpose
-#   backward : conv3d_transpose_grad
-#   extra :
-#     attrs : [bool use_cudnn = true, bool use_mkldnn = false, int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
+- api : abs
+  backward : abs_grad
+  extra :
+    attrs : [bool use_cudnn = false, bool use_mkldnn = false]
+
+- api : addmm
+  backward : addmm_grad
+  extra :
+    attrs : [bool use_mkldnn = false]
+
+- api : affine_grid
+  backward : affine_grid_grad
+  extra :
+    attrs : [bool use_cudnn = true]
+
+- api : angle
+  backward : angle_grad
+  extra :
+    attrs : [bool use_cudnn = false, bool use_mkldnn = false]
 
 - api : atan2
   inputs :
@@ -9,6 +24,11 @@
   outputs :
     out : Out
 
+- api : batch_norm
+  backward : batch_norm_grad
+  extra :
+    attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]
+
 - api : bernoulli
   inputs :
     x : X
@@ -27,24 +47,55 @@
   outputs :
     out : Out
 
+- api : clip
+  backward : clip_grad
+  extra :
+    attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
+
+- api : concat
+  backward : concat_grad
+  extra :
+    attrs : [bool use_mkldnn = false, bool use_quantizer = false, str mkldnn_data_type = "float32"]
+
 - api : conv2d
   backward : conv2d_grad
   extra :
-    attrs : [bool use_cudnn = true, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
+    attrs : [bool is_test = false, bool use_cudnn = true, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
              bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
              str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, bool use_addto = false,
              bool fuse_residual_connection = false, float Scale_in = 1.0f, float Scale_out = 1.0f,
              float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
-             int workspace_size_MB = 512, bool exhaustive_search = false]
+             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
 
 - api : conv2d_fusion
   extra :
-    attrs : [bool use_cudnn = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
+    attrs : [bool is_test = false, bool use_cudnn = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
              bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
              str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, bool use_addto = false,
              bool fuse_residual_connection = false, float Scale_in = 1.0f, float Scale_out = 1.0f,
              float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
-             int workspace_size_MB = 512, bool exhaustive_search = false]
+             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
+
+- api : conv2d_transpose
+  backward : conv2d_transpose_grad
+  extra :
+    attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, bool force_fp32_output = false,
+             str mkldnn_data_type = "float32", bool fuse_relu = false,
+             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
+             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
+
+- api : conv3d
+  backward : conv3d_grad
+  extra :
+    attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
+             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
+             bool use_addto = false, bool fuse_residual_connection = false, bool force_fp32_output = false,
+             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
+
+- api : conv3d_transpose
+  backward : conv3d_transpose_grad
+  extra :
+    attrs : [bool use_cudnn = true, bool use_mkldnn = false, int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
 
 - api : cross
   inputs :
@@ -57,12 +108,20 @@
 - api : depthwise_conv2d
   backward : depthwise_conv2d_grad
   extra :
-    attrs : [bool use_cudnn = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
+    attrs : [bool is_test = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
              bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
              str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, bool use_addto = false,
              bool fuse_residual_connection = false, float Scale_in = 1.0f, float Scale_out = 1.0f,
              float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
-             int workspace_size_MB = 512, bool exhaustive_search = false]
+             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
+
+- api : depthwise_conv2d_transpose
+  backward : depthwise_conv2d_transpose_grad
+  extra :
+    attrs : [bool is_test = false, bool use_cudnn = false, bool use_mkldnn = false, bool force_fp32_output = false,
+             str mkldnn_data_type = "float32", bool fuse_relu = false,
+             str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
+             int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
 
 - api : diag
   op_name : diag_v2
@@ -108,6 +167,11 @@
   outputs :
     out : Out
 
+- api : inplace_abn
+  backward : inplace_abn_grad
+  extra :
+    attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]
+
 - api : lgamma
   inputs :
     x : X
@@ -132,6 +196,11 @@
   outputs :
     out : Out
 
+- api : sync_batch_norm
+  backward : sync_batch_norm_grad
+  extra :
+    attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]
+
 - api : trace
   inputs :
     x : Input