diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.cc
index 334550b213..157110d25c 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.cc
@@ -23,6 +23,11 @@ MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOut
 MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
                       ActivationGpuFwdKernel, half)
 
+MS_REG_GPU_KERNEL_ONE(ReLU6, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
+                      ActivationGpuFwdKernel, float)
+MS_REG_GPU_KERNEL_ONE(ReLU6, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
+                      ActivationGpuFwdKernel, half)
+
 MS_REG_GPU_KERNEL_ONE(Tanh, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
                       ActivationGpuFwdKernel, float)
 MS_REG_GPU_KERNEL_ONE(Tanh, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.h
index 14fc721889..b49e3b86a1 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.h
+++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.h
@@ -83,7 +83,8 @@ class ActivationGpuFwdKernel : public GpuKernel {
       return true;
     }
     std::vector<int> shape;
-    CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_NOT_PROPAGATE_NAN, 0.0),
+    double coef = (mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) ? 6.0 : 0.0;
+    CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_NOT_PROPAGATE_NAN, coef),
                                 "cudnnSetActivationDescriptor failed");
 
     const int split_dim = 4;
@@ -132,6 +133,7 @@ class ActivationGpuFwdKernel : public GpuKernel {
   }
 
   std::map<std::string, cudnnActivationMode_t> kernel_map = {{"ReLU", CUDNN_ACTIVATION_RELU},
+                                                             {"ReLU6", CUDNN_ACTIVATION_CLIPPED_RELU},
                                                              {"Tanh", CUDNN_ACTIVATION_TANH},
                                                              {"ELU", CUDNN_ACTIVATION_ELU},
                                                              {"Sigmoid", CUDNN_ACTIVATION_SIGMOID}};
diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc
index 8fd486c08c..8e6f568031 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc
@@ -27,6 +27,15 @@ MS_REG_GPU_KERNEL_ONE(
   KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
   ActivationGradGpuKernel, half)
 
+MS_REG_GPU_KERNEL_ONE(
+  ReLU6Grad,
+  KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
+  ActivationGradGpuKernel, float)
+MS_REG_GPU_KERNEL_ONE(
+  ReLU6Grad,
+  KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
+  ActivationGradGpuKernel, half)
+
 MS_REG_GPU_KERNEL_ONE(
   TanhGrad,
   KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h
index e2f040f6be..c6fd1a0921 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h
+++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h
@@ -49,7 +49,7 @@ class ActivationGradGpuKernel : public GpuKernel {
     }
     T *dy = nullptr;
     T *y = nullptr;
-    if (mode_ == CUDNN_ACTIVATION_RELU || mode_ == CUDNN_ACTIVATION_ELU) {
+    if (mode_ == CUDNN_ACTIVATION_RELU || mode_ == CUDNN_ACTIVATION_ELU || mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) {
       dy = GetDeviceAddress<T>(inputs, 0);
       y = GetDeviceAddress<T>(inputs, 1);
     } else {
@@ -90,7 +90,8 @@ class ActivationGradGpuKernel : public GpuKernel {
       return true;
     }
     std::vector<int> shape;
-    CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_PROPAGATE_NAN, 0.0),
+    double coef = (mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) ? 5.999999 : 0.0;
+    CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_PROPAGATE_NAN, coef),
                                 "SetActivationDescriptor failed");
 
     const int split_dim = 4;
@@ -138,6 +139,7 @@ class ActivationGradGpuKernel : public GpuKernel {
   }
 
   std::map<std::string, cudnnActivationMode_t> kernel_map = {{"ReluGrad", CUDNN_ACTIVATION_RELU},
+                                                             {"ReLU6Grad", CUDNN_ACTIVATION_CLIPPED_RELU},
                                                              {"TanhGrad", CUDNN_ACTIVATION_TANH},
                                                              {"ELUGrad", CUDNN_ACTIVATION_ELU},
                                                              {"SigmoidGrad", CUDNN_ACTIVATION_SIGMOID}};
diff --git a/mindspore/ccsrc/runtime/device/gpu/kernel_info_setter.h b/mindspore/ccsrc/runtime/device/gpu/kernel_info_setter.h
index e6ef029fb2..2034220097 100644
--- a/mindspore/ccsrc/runtime/device/gpu/kernel_info_setter.h
+++ b/mindspore/ccsrc/runtime/device/gpu/kernel_info_setter.h
@@ -54,6 +54,8 @@ static std::map<std::string, std::pair<std::vector<size_t>, std::vector<size_t>>
   // Format insensitive.
   {prim::kPrimRelu->name(), {{0}, {0}}},
   {prim::kPrimReluGrad->name(), {{0, 1}, {0}}},
+  {prim::kPrimRelu6->name(), {{0}, {0}}},
+  {prim::kPrimRelu6Grad->name(), {{0, 1}, {0}}},
   {kSliceOpName, {{0}, {0}}},
   {kTensorAddOpName, {{0, 1}, {0}}},
   {prim::kPrimConcat->name(), {{}, {0}}},
diff --git a/mindspore/core/base/core_ops.h b/mindspore/core/base/core_ops.h
index 48c07a8d03..58f15c79b4 100644
--- a/mindspore/core/base/core_ops.h
+++ b/mindspore/core/base/core_ops.h
@@ -127,6 +127,7 @@ inline const PrimitivePtr kPrimFusedBatchNormGradEx = std::make_shared<Primitive
 inline const PrimitivePtr kPrimBatchNorm = std::make_shared<Primitive>("BatchNorm");
 inline const PrimitivePtr kPrimBatchNormGrad = std::make_shared<Primitive>("BatchNormGrad");
 inline const PrimitivePtr kPrimReluGrad = std::make_shared<Primitive>("ReluGrad");
+inline const PrimitivePtr kPrimRelu6Grad = std::make_shared<Primitive>("ReLU6Grad");
 inline const PrimitivePtr kPrimConv2DBackpropInput = std::make_shared<Primitive>("Conv2DBackpropInput");
 inline const PrimitivePtr kPrimConv2DBackpropFilter = std::make_shared<Primitive>("Conv2DBackpropFilter");
 inline const PrimitivePtr kPrimDepthwiseConv2dNative = std::make_shared<Primitive>("DepthwiseConv2dNative");
@@ -151,6 +152,7 @@ inline const PrimitivePtr kPrimOneHot = std::make_shared<Primitive>("OneHot");
 inline const PrimitivePtr kPrimGelu = std::make_shared<Primitive>("Gelu");
 inline const PrimitivePtr kPrimGeluGrad = std::make_shared<Primitive>("GeluGrad");
 inline const PrimitivePtr kPrimRelu = std::make_shared<Primitive>("ReLU");
+inline const PrimitivePtr kPrimRelu6 = std::make_shared<Primitive>("ReLU6");
 inline const PrimitivePtr kPrimReluV2 = std::make_shared<Primitive>("ReLUV2");
 inline const PrimitivePtr kPrimZerosLike = std::make_shared<Primitive>("ZerosLike");
 inline const PrimitivePtr kPrimBpropCut = std::make_shared<Primitive>("bprop_cut");