diff --git a/mindspore/ccsrc/plugin/device/cpu/optimizer/reg_cpu_const_input_to_attr.h b/mindspore/ccsrc/plugin/device/cpu/optimizer/reg_cpu_const_input_to_attr.h
index 93bb799ec81..d0872fb855a 100644
--- a/mindspore/ccsrc/plugin/device/cpu/optimizer/reg_cpu_const_input_to_attr.h
+++ b/mindspore/ccsrc/plugin/device/cpu/optimizer/reg_cpu_const_input_to_attr.h
@@ -26,8 +26,6 @@ RER_CPU_DYNAMIC_CONST_TO_ATTR(kCastOpName, 1);
 RER_CPU_DYNAMIC_CONST_TO_ATTR(kFillOpName, 0);
 
 RER_CPU_STATIC_CONST_TO_ATTR(kCastOpName, 1);
-RER_CPU_STATIC_CONST_TO_ATTR(kConv2DBackpropInputOpName, 2);
-RER_CPU_STATIC_CONST_TO_ATTR(kConv2DTransposeOpName, 2);
 RER_CPU_STATIC_CONST_TO_ATTR(kCOO2CSROpName, 1);
 RER_CPU_STATIC_CONST_TO_ATTR(kCSR2COOOpName, 1);
 RER_CPU_STATIC_CONST_TO_ATTR(kCSRDivOpName, 3);
diff --git a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.cc b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.cc
index d236249977c..630a683ff89 100644
--- a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.cc
@@ -36,8 +36,7 @@ constexpr size_t kWidth2DStrideIndex = 3;
 constexpr size_t k2DDilationSize = 4;
 constexpr size_t kHeight2DDilationIndex = 2;
 constexpr size_t kWidth2DDilationIndex = 3;
-constexpr auto StaticInput = 2;
-constexpr auto DynamicInput = 3;
+constexpr auto kInputDim = 3;
 
 constexpr auto k2DHeightIndexNCHW = 2;
 constexpr auto k2DHeightIndexNHWC = 1;
@@ -45,10 +44,6 @@ constexpr auto k2DHeightIndexNHWC = 1;
 using KernelRunFunc = ConvGradFilterBkwGpuKernelMod::KernelRunFunc;
 const std::vector<std::pair<KernelAttr, KernelRunFunc>> &ConvGradFilterBkwGpuKernelMod::GetFuncList() const {
   static const std::vector<std::pair<KernelAttr, KernelRunFunc>> func_list = {
-    {KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
-     &ConvGradFilterBkwGpuKernelMod::LaunchKernel<float>},
-    {KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
-     &ConvGradFilterBkwGpuKernelMod::LaunchKernel<half>},
     {KernelAttr()
        .AddInputAttr(kNumberTypeFloat32)
        .AddInputAttr(kNumberTypeFloat32)
@@ -146,11 +141,8 @@ void ConvGradFilterBkwGpuKernelMod::CalPadList(const std::vector<int> &pad_list,
 
 void ConvGradFilterBkwGpuKernelMod::CheckParam(const std::vector<KernelTensorPtr> &inputs) {
   size_t input_num = inputs.size();
-  if (input_num != StaticInput && input_num != DynamicInput) {
-    MS_LOG(EXCEPTION) << "For '" << kernel_name_ << "', the number of inputs must be 2 or 3, but got " << input_num;
-  }
-  if (input_num == DynamicInput) {
-    is_dynamic_attr_ = true;
+  if (input_num != kInputDim) {
+    MS_LOG(EXCEPTION) << "For '" << kernel_name_ << "', the number of inputs must be 3, but got " << input_num;
   }
 }
 
@@ -273,9 +265,7 @@ bool ConvGradFilterBkwGpuKernelMod::Init(const BaseOperatorPtr &base_operator,
   if (format_attr_ == kOpFormat_NHWC) {
     data_format_ = kOpFormat_NHWC;
   }
-  if (!is_dynamic_attr_) {
-    filter_shape_ = GetValue<std::vector<int64_t>>(prim->GetAttr("filter_sizes"));
-  }
+
   group_ = static_cast<int>(GetValue<int64_t>(prim->GetAttr("group")));
   CHECK_CUDNN_RET_WITH_EXCEPT_NOTRACE(cudnnSetConvolutionGroupCount(conv_desc_, group_),
                                       "cudnnSetConvGroupCount failed");
@@ -306,14 +296,12 @@ int ConvGradFilterBkwGpuKernelMod::Resize(const BaseOperatorPtr &base_operator,
   if (is_null_input_) {
     return KRET_OK;
   }
-  if (is_dynamic_attr_) {
-    constexpr size_t kShapeIndex = 2;
-    auto value_res = TryGetIntValueFromInputs(inputs, kShapeIndex, kernel_name_, true);
-    if (!value_res.has_value()) {
-      MS_LOG(EXCEPTION) << "Fail to get filter_sizes from inputs";
-    }
-    filter_shape_ = value_res.value();
+
+  constexpr size_t kShapeIndex = 2;
+  if (!TryGetIntValue(inputs, kShapeIndex, kernel_name_, &filter_shape_, true)) {
+    MS_LOG(EXCEPTION) << "For " << kernel_name_ << " can't get filter_sizes input!";
   }
+
   auto filter_shape = filter_shape_;
   if (!CheckTensorSize({in_shape, dy_shape, filter_shape})) {
     return KRET_RESIZE_FAILED;
diff --git a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.h b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.h
index 4a719490deb..7a4ad9b8d89 100644
--- a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.h
+++ b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_filter_gpu_kernel.h
@@ -117,7 +117,6 @@ class ConvGradFilterBkwGpuKernelMod : public NativeGpuKernelMod,
   size_t padded_size_;
   size_t workspace_size_;
   bool use_pad_;
-  bool is_dynamic_attr_{false};
   std::vector<int64_t> filter_shape_;
   std::vector<int> pad_list_;
   void *stream_ptr_{nullptr};
diff --git a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.cc b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.cc
index 38778582e85..bc30bf8e668 100644
--- a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.cc
@@ -37,8 +37,7 @@ constexpr size_t kWidth2DStrideIndex = 1;
 constexpr size_t k2DDilationSize = 4;
 constexpr size_t kHeight2DDilationIndex = 2;
 constexpr size_t kWidth2DDilationIndex = 3;
-constexpr auto StaticInput = 2;
-constexpr auto DynamicInput = 3;
+constexpr auto kInputDim = 3;
 
 constexpr auto k2DHeightIndexNCHW = 2;
 constexpr auto k2DHeightIndexNHWC = 1;
@@ -46,10 +45,6 @@ constexpr auto k2DHeightIndexNHWC = 1;
 using KernelRunFunc = ConvGradInputBkwGpuKernelMod::KernelRunFunc;
 const std::vector<std::pair<KernelAttr, KernelRunFunc>> &ConvGradInputBkwGpuKernelMod::GetFuncList() const {
   static const std::vector<std::pair<KernelAttr, KernelRunFunc>> func_list = {
-    {KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
-     &ConvGradInputBkwGpuKernelMod::LaunchKernel<float>},
-    {KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
-     &ConvGradInputBkwGpuKernelMod::LaunchKernel<half>},
     {KernelAttr()
        .AddInputAttr(kNumberTypeFloat32)
        .AddInputAttr(kNumberTypeFloat32)
@@ -163,11 +158,8 @@ void ConvGradInputBkwGpuKernelMod::CalPadList(const ShapeVector input_shape, con
 
 void ConvGradInputBkwGpuKernelMod::CheckParam(const std::vector<KernelTensorPtr> &inputs) {
   size_t input_num = inputs.size();
-  if (input_num != StaticInput && input_num != DynamicInput) {
-    MS_LOG(EXCEPTION) << "For '" << kernel_name_ << "', the number of inputs must be 2 or 3, but got " << input_num;
-  }
-  if (input_num == DynamicInput) {
-    is_dynamic_attr_ = true;
+  if (input_num != kInputDim) {
+    MS_LOG(EXCEPTION) << "For '" << kernel_name_ << "', the number of inputs must be 3, but got " << input_num;
   }
 }
 
@@ -254,9 +246,7 @@ bool ConvGradInputBkwGpuKernelMod::Init(const BaseOperatorPtr &base_operator,
   data_format_ = mindspore::FormatEnumToString(inputs[0]->GetFormat());
   auto prim = base_operator->GetPrim();
   MS_EXCEPTION_IF_NULL(prim);
-  if (!is_dynamic_attr_) {
-    input_shape_ = GetValue<std::vector<int64_t>>(prim->GetAttr("input_sizes"));
-  }
+
   format_attr_ = GetValue<std::string>(prim->GetAttr("format"));
   if (format_attr_ == kOpFormat_NHWC) {
     data_format_ = kOpFormat_NHWC;
@@ -295,14 +285,12 @@ int ConvGradInputBkwGpuKernelMod::Resize(const BaseOperatorPtr &base_operator,
   if (is_null_input_) {
     return KRET_OK;
   }
-  if (is_dynamic_attr_) {
-    constexpr size_t kShapeIndex = 2;
-    auto value_res = TryGetIntValueFromInputs(inputs, kShapeIndex, kernel_name_, true);
-    if (!value_res.has_value()) {
-      MS_LOG(EXCEPTION) << "Fail to get filter_sizes from inputs";
-    }
-    input_shape_ = value_res.value();
+
+  constexpr size_t kShapeIndex = 2;
+  if (!TryGetIntValue(inputs, kShapeIndex, kernel_name_, &input_shape_, true)) {
+    MS_LOG(EXCEPTION) << "For " << kernel_name_ << " can't get input_sizes input!";
   }
+
   auto input_shape = input_shape_;
   int h_index = k2DHeightIndexNCHW;
   int w_index = k2DHeightIndexNCHW + 1;
diff --git a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.h b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.h
index 08b17574ebf..8a984ea87ab 100644
--- a/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.h
+++ b/mindspore/ccsrc/plugin/device/gpu/kernel/nn/conv2d_grad_input_gpu_kernel.h
@@ -117,7 +117,6 @@ class ConvGradInputBkwGpuKernelMod : public NativeGpuKernelMod, public MatchKern
   size_t workspace_size_;
   bool use_pad_;
   float beta_;
-  bool is_dynamic_attr_{false};
   bool get_dynamic_attr_value_{false};
   std::vector<int64_t> input_shape_;
   static constexpr size_t kShapeIndex_{2};
diff --git a/mindspore/ccsrc/plugin/device/gpu/optimizer/reg_gpu_const_input_to_attr.h b/mindspore/ccsrc/plugin/device/gpu/optimizer/reg_gpu_const_input_to_attr.h
index 87989b96a54..a1d19ba71ae 100644
--- a/mindspore/ccsrc/plugin/device/gpu/optimizer/reg_gpu_const_input_to_attr.h
+++ b/mindspore/ccsrc/plugin/device/gpu/optimizer/reg_gpu_const_input_to_attr.h
@@ -25,9 +25,6 @@ namespace mindspore::opt {
 RER_GPU_DYNAMIC_CONST_TO_ATTR(kCastOpName, 1);
 RER_GPU_DYNAMIC_CONST_TO_ATTR(kFillOpName, 0);
 RER_GPU_STATIC_CONST_TO_ATTR(kCastOpName, 1);
-RER_GPU_STATIC_CONST_TO_ATTR(kConv2DBackpropFilterOpName, 2);
-RER_GPU_STATIC_CONST_TO_ATTR(kConv2DBackpropInputOpName, 2);
-RER_GPU_STATIC_CONST_TO_ATTR(kConv2DTransposeOpName, 2);
 RER_GPU_STATIC_CONST_TO_ATTR(kCOO2CSROpName, 1);
 RER_GPU_STATIC_CONST_TO_ATTR(kCSR2COOOpName, 1);
 RER_GPU_STATIC_CONST_TO_ATTR(kCSRDivOpName, 3);