!20912 code check for ops

Merge pull request !20912 from Simson/codex

mindspore/ccsrc/backend/kernel_compiler/gpu/control/recv_gpu_kernel.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -39,6 +39,7 @@ class RecvGpuKernel : public GpuKernel {
     return true;
   }
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     wait_stream_ = reinterpret_cast<cudaStream_t>(GetAttr<uintptr_t>(kernel_node, "wait_event_stream"));
     wait_event_ = reinterpret_cast<cudaEvent_t>(GetAttr<uintptr_t>(kernel_node, "wait_event"));

mindspore/ccsrc/backend/kernel_compiler/gpu/control/send_gpu_kernel.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -39,6 +39,7 @@ class SendGpuKernel : public GpuKernel {
     return true;
   }
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     record_stream_ = reinterpret_cast<cudaStream_t>(GetAttr<uintptr_t>(kernel_node, "record_event_stream"));
     record_event_ = reinterpret_cast<cudaEvent_t>(GetAttr<uintptr_t>(kernel_node, "record_event"));

mindspore/ccsrc/backend/kernel_compiler/gpu/data/dataset_init_kernel.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -34,11 +34,17 @@ const std::vector<size_t> &DatasetInitKernel::GetOutputSizeList() const { return
 const std::vector<size_t> &DatasetInitKernel::GetWorkspaceSizeList() const { return workspace_size_list_; }
 
 bool DatasetInitKernel::Init(const CNodePtr &kernel_node) {
+  MS_EXCEPTION_IF_NULL(kernel_node);
   queue_name_ = GetAttr<std::string>(kernel_node, "queue_name");
   std::vector<std::vector<int>> shapes;
   std::vector<TypePtr> types;
   GetShapeAndType(kernel_node, &shapes, &types);
-
+  for (auto item : types) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
+  if (types.size() < shapes.size()) {
+    MS_LOG(EXCEPTION) << "types size is less than shapes size.";
+  }
   for (size_t i = 0; i < shapes.size(); i++) {
     int unit = UnitSizeInBytes(types[i]->type_id());
     int nums = ElementNums(shapes[i]);

mindspore/ccsrc/backend/kernel_compiler/gpu/data/dataset_iterator_kernel.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -47,12 +47,18 @@ const std::vector<size_t> &DatasetIteratorKernel::GetOutputSizeList() const { re
 const std::vector<size_t> &DatasetIteratorKernel::GetWorkspaceSizeList() const { return workspace_size_list_; }
 
 bool DatasetIteratorKernel::Init(const CNodePtr &kernel_node) {
+  MS_EXCEPTION_IF_NULL(kernel_node);
   kernel_node_ = kernel_node;
   queue_name_ = GetAttr<std::string>(kernel_node, "shared_name");
   std::vector<std::vector<int>> shapes;
   std::vector<TypePtr> types;
   GetShapeAndType(kernel_node, &shapes, &types);
-
+  for (auto item : types) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
+  if (types.size() < shapes.size()) {
+    MS_LOG(EXCEPTION) << "types size is less than shapes size.";
+  }
   for (size_t i = 0; i < shapes.size(); i++) {
     int unit = UnitSizeInBytes(types[i]->type_id());
     int nums = ElementNums(shapes[i]);

mindspore/ccsrc/backend/kernel_compiler/gpu/data/dataset_profiling.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -48,6 +48,9 @@ void GetNextProfiling::SaveProfilingData() {
     return;
   }
   for (uint32_t index = 0; index < queue_size_.size(); index++) {
+    if (index > time_stamp_.size() - 1) {
+      MS_LOG(EXCEPTION) << "index exceeds time_stamp_ size.";
+    }
     handle << Name() << " " << time_stamp_[index].first << " " << time_stamp_[index].second << " " << queue_size_[index]
            << std::endl;
   }

mindspore/ccsrc/backend/kernel_compiler/gpu/data/dataset_utils.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -68,6 +68,7 @@ int ElementNums(const std::vector<int> &shape) {
 }
 
 void GetShapeAndType(const CNodePtr &kernel_node, std::vector<std::vector<int>> *shapes, std::vector<TypePtr> *types) {
+  MS_EXCEPTION_IF_NULL(kernel_node);
   MS_EXCEPTION_IF_NULL(shapes);
   MS_EXCEPTION_IF_NULL(types);
   std::vector<std::vector<int64_t>> shapes_me =

mindspore/ccsrc/backend/kernel_compiler/gpu/debug/print_gpu_kernel.h

@@ -87,6 +87,7 @@ class PrintGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     if (AnfAlgo::HasNodeAttr("string_pos", kernel_node)) {
       string_value_ = GetAttr<std::vector<std::string>>(kernel_node, "string_value");

mindspore/ccsrc/backend/kernel_compiler/gpu/nccl/nccl_collective_gpu_kernel.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -77,6 +77,7 @@ class NcclCollectiveGpuKernel : public NcclGpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     nccl_data_type_ = nccl_dtype(AnfAlgo::GetInputDeviceDataType(kernel_node, 0));
     InferCommType(kernel_node);

mindspore/ccsrc/backend/kernel_compiler/gpu/other/assign_gpu_kernel.h

@@ -49,6 +49,7 @@ class AssignGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     if (!CheckParam(kernel_node)) {
       return false;
@@ -71,6 +72,7 @@ class AssignGpuKernel : public GpuKernel {
 
  private:
   bool CheckParam(const CNodePtr &kernel_node) {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 2) {
       MS_LOG(ERROR) << "Input number is " << input_num << ", but AssignGpuKernel needs 2 output.";

mindspore/ccsrc/backend/kernel_compiler/gpu/other/boundingbox_decode_gpu_kernel.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -62,6 +62,7 @@ class BoundingBoxDecodeGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 2) {
       MS_LOG(ERROR) << "Input number is " << input_num << ", but BoundingBoxDecode needs 2 inputs.";
@@ -89,10 +90,11 @@ class BoundingBoxDecodeGpuKernel : public GpuKernel {
     InitSizeLists();
 
     const size_t coordinate_size = 4;
-    if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means")->isa<ValueTuple>() ||
+    auto means = AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means");
-        AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means")->isa<ValueList>()) {
+    MS_EXCEPTION_IF_NULL(means);
+    if (means->isa<ValueTuple>() || means->isa<ValueList>()) {
       means_ = GetAttr<std::vector<float>>(kernel_node, "means");
-    } else if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means")->isa<FloatImm>()) {
+    } else if (means->isa<FloatImm>()) {
       float mean = GetAttr<float>(kernel_node, "means");
       for (size_t i = 0; i < coordinate_size; i++) {
         means_.emplace_back(mean);
@@ -101,10 +103,11 @@ class BoundingBoxDecodeGpuKernel : public GpuKernel {
       MS_LOG(EXCEPTION) << "Attribute means type is invalid.";
     }
 
-    if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds")->isa<ValueTuple>() ||
+    auto stds = AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds");
-        AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds")->isa<ValueList>()) {
+    MS_EXCEPTION_IF_NULL(stds);
+    if (stds->isa<ValueTuple>() || stds->isa<ValueList>()) {
       stds_ = GetAttr<std::vector<float>>(kernel_node, "stds");
-    } else if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds")->isa<FloatImm>()) {
+    } else if (stds->isa<FloatImm>()) {
       float std = GetAttr<float>(kernel_node, "stds");
       for (size_t i = 0; i < coordinate_size; i++) {
         stds_.emplace_back(std);

mindspore/ccsrc/backend/kernel_compiler/gpu/other/boundingbox_encode_gpu_kernel.h

@@ -61,6 +61,7 @@ class BoundingBoxEncodeGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 2) {
       MS_LOG(ERROR) << "Input number is " << input_num << ", but BoundingBoxEncode needs 2 inputs.";
@@ -88,10 +89,11 @@ class BoundingBoxEncodeGpuKernel : public GpuKernel {
     InitSizeLists();
 
     const size_t coordinate_size = 4;
-    if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means")->isa<ValueTuple>() ||
+    auto means = AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means");
-        AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means")->isa<ValueList>()) {
+    MS_EXCEPTION_IF_NULL(means);
+    if (means->isa<ValueTuple>() || means->isa<ValueList>()) {
       means_ = GetAttr<std::vector<float>>(kernel_node, "means");
-    } else if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("means")->isa<FloatImm>()) {
+    } else if (means->isa<FloatImm>()) {
       float mean = GetAttr<float>(kernel_node, "means");
       for (size_t i = 0; i < coordinate_size; i++) {
         means_.emplace_back(mean);
@@ -99,11 +101,11 @@ class BoundingBoxEncodeGpuKernel : public GpuKernel {
     } else {
       MS_LOG(EXCEPTION) << "Attribute means type is invalid.";
     }
-
+    auto stds = AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds");
-    if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds")->isa<ValueTuple>() ||
+    MS_EXCEPTION_IF_NULL(stds);
-        AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds")->isa<ValueList>()) {
+    if (stds->isa<ValueTuple>() || stds->isa<ValueList>()) {
       stds_ = GetAttr<std::vector<float>>(kernel_node, "stds");
-    } else if (AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("stds")->isa<FloatImm>()) {
+    } else if (stds->isa<FloatImm>()) {
       float std = GetAttr<float>(kernel_node, "stds");
       for (size_t i = 0; i < coordinate_size; i++) {
         stds_.emplace_back(std);

mindspore/ccsrc/backend/kernel_compiler/gpu/other/check_valid_gpu_kernel.h

@@ -55,6 +55,7 @@ class CheckValidGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 2) {
       MS_LOG(ERROR) << "Input number is " << input_num << ", but CheckValid needs 2 inputs.";

mindspore/ccsrc/backend/kernel_compiler/gpu/other/gpu_convert_to_dynamic_shape_gpu_kernel.h

@@ -59,6 +59,7 @@ class GpuConvertToDynamicShapeGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     size_t input_count = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_count != 1) {

mindspore/ccsrc/backend/kernel_compiler/gpu/other/iou_gpu_kernel.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -59,6 +59,7 @@ class IOUGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 2) {
       MS_LOG(ERROR) << "Input number is " << input_num << ", but IOU needs 2 inputs.";

mindspore/ccsrc/backend/kernel_compiler/gpu/random/random_categorical_gpu_kernel.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -89,6 +89,7 @@ class RandomCategoricalGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 3) {

mindspore/ccsrc/backend/kernel_compiler/gpu/random/random_choice_with_mask_gpu_kernel.h

@@ -70,6 +70,7 @@ class RandomChoiceWithMaskGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     uint32_t time_interval = std::chrono::system_clock::now().time_since_epoch().count();
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 1) {

mindspore/ccsrc/backend/kernel_compiler/gpu/random/uniform_candidate_sampler_gpu_kernel.h

@@ -76,6 +76,7 @@ class UniformCandidateSamplerGpuKernel : public GpuKernel {
   }
 
   bool Init(const CNodePtr &kernel_node) override {
+    MS_EXCEPTION_IF_NULL(kernel_node);
     kernel_node_ = kernel_node;
     size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
     if (input_num != 1) {
@@ -173,6 +174,7 @@ class UniformCandidateSamplerGpuKernel : public GpuKernel {
       MS_LOG(EXCEPTION) << "range_max_ failed to cast";
     }
     range = static_cast<S>(range_max_);
+    MS_EXCEPTION_IF_ZERO("range", range);
     return static_cast<S>(1.0f / range);
   }
 

mindspore/core/ops/fusion/activation.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/activation.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/add_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/add_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/adder_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -42,6 +42,7 @@ void AdderFusion::set_activation_type(const ActivationType activation_type) {
 
 ActivationType AdderFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameAdderFusion, AdderFusion);

mindspore/core/ops/fusion/adder_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/arg_max_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -31,9 +31,21 @@ void ArgMaxFusion::set_out_max_value(const bool out_max_value) {
 }
 void ArgMaxFusion::set_top_k(const int64_t top_k) { (void)this->AddAttr(kTopK, MakeValue(top_k)); }
 
-bool ArgMaxFusion::get_keep_dims() const { return GetValue<bool>(GetAttr(kKeepDims)); }
+bool ArgMaxFusion::get_keep_dims() const {
-bool ArgMaxFusion::get_out_max_value() const { return GetValue<bool>(GetAttr(kOutMaxValue)); }
+  auto keep_dims = GetAttr(kKeepDims);
-int64_t ArgMaxFusion::get_top_k() const { return GetValue<int64_t>(GetAttr(kTopK)); }
+  MS_EXCEPTION_IF_NULL(keep_dims);
+  return GetValue<bool>(keep_dims);
+}
+bool ArgMaxFusion::get_out_max_value() const {
+  auto out_maxv = GetAttr(kOutMaxValue);
+  MS_EXCEPTION_IF_NULL(out_maxv);
+  return GetValue<bool>(out_maxv);
+}
+int64_t ArgMaxFusion::get_top_k() const {
+  auto topk = GetAttr(kTopK);
+  MS_EXCEPTION_IF_NULL(topk);
+  return GetValue<int64_t>(topk);
+}
 
 REGISTER_PRIMITIVE_C(kNameArgMaxFusion, ArgMaxFusion);
 }  // namespace ops

mindspore/core/ops/fusion/arg_max_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/arg_min_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -29,14 +29,21 @@ void ArgMinFusion::set_keep_dims(const bool keep_dims) { (void)this->AddAttr(kKe
 void ArgMinFusion::set_out_max_value(bool out_max_value) { (void)AddAttr(kOutMaxValue, MakeValue(out_max_value)); }
 void ArgMinFusion::set_top_k(int64_t top_k) { (void)this->AddAttr(kTopK, MakeValue(top_k)); }
 
-bool ArgMinFusion::get_keep_dims() const { return GetValue<bool>(GetAttr(kKeepDims)); }
+bool ArgMinFusion::get_keep_dims() const {
+  auto keep_dims = GetAttr(kKeepDims);
+  MS_EXCEPTION_IF_NULL(keep_dims);
+  return GetValue<bool>(keep_dims);
+}
+
 bool ArgMinFusion::get_out_max_value() const {
   auto value_ptr = GetAttr(kOutMaxValue);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 
 int64_t ArgMinFusion::get_top_k() const {
   auto value_ptr = GetAttr(kTopK);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 

mindspore/core/ops/fusion/arg_min_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/avg_pool_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -40,17 +40,22 @@ void AvgPoolFusion::set_activation_type(ActivationType activation_type) {
 
 bool AvgPoolFusion::get_global() const {
   auto value_ptr = GetAttr(kGlobal);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 
 ActivationType AvgPoolFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 
 namespace {
 abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
+  for (auto item : input_args) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
   auto op_name = primitive->name();
   auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->GetShapeTrack())[kShape];
   auto format = Format(GetValue<int64_t>(primitive->GetAttr(kFormat)));
@@ -66,6 +71,7 @@ abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<A
   auto in_w = in_shape[3];
 
   auto strides = GetValue<std::vector<int64_t>>(primitive->GetAttr(kStrides));
+  (void)CheckAndConvertUtils::CheckPositiveVector(kStride, strides, op_name);
   auto kernel_h = kernel_size[2];
   auto kernel_w = kernel_size[3];
   auto stride_h = strides[2];
@@ -90,8 +96,8 @@ abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<A
 }
 
 TypePtr InferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
-  if (std::any_of(input_args.begin(), input_args.end(), [](AbstractBasePtr arg) { return arg == nullptr; })) {
+  for (auto item : input_args) {
-    MS_LOG(EXCEPTION) << "nullptr";
+    MS_EXCEPTION_IF_NULL(item);
   }
   return input_args[0]->BuildType();
 }

mindspore/core/ops/fusion/avg_pool_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/conv2d_backprop_filter_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -52,11 +52,13 @@ void Conv2DBackpropFilterFusion::set_in_channel(const int64_t in_channel) {
 
 ActivationType Conv2DBackpropFilterFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 
 int64_t Conv2DBackpropFilterFusion::get_in_channel() const {
   auto value_ptr = GetAttr(kInChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameConv2DBackpropFilterFusion, Conv2DBackpropFilterFusion);

mindspore/core/ops/fusion/conv2d_backprop_filter_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/conv2d_backprop_input_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -51,11 +51,13 @@ void Conv2DBackpropInputFusion::set_activation_type(const ActivationType &activa
 }
 int64_t Conv2DBackpropInputFusion::get_in_channel() const {
   auto value_ptr = GetAttr(kInChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
 ActivationType Conv2DBackpropInputFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameConv2DBackpropInputFusion, Conv2DBackpropInputFusion);

mindspore/core/ops/fusion/conv2d_backprop_input_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/conv2d_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -48,14 +48,17 @@ void Conv2DFusion::set_activation_type(const ActivationType &activation_type) {
 }
 int64_t Conv2DFusion::get_in_channel() const {
   auto value_ptr = GetAttr(kInChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 std::vector<int64_t> Conv2DFusion::get_pad_list() const {
   auto value_ptr = GetAttr(kPadList);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 ActivationType Conv2DFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameConv2DFusion, Conv2DFusion);

mindspore/core/ops/fusion/conv2d_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/conv2d_transpose_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -71,11 +71,13 @@ void Conv2dTransposeFusion::set_activation_type(ActivationType activation_type)
 
 std::vector<int64_t> Conv2dTransposeFusion::get_output_paddings() const {
   auto value_ptr = GetAttr(kOutputPaddings);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
 ActivationType Conv2dTransposeFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 

mindspore/core/ops/fusion/conv2d_transpose_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/div_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -29,6 +29,7 @@ void DivFusion::set_activation_type(const ActivationType &activation_type) {
 
 ActivationType DivFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameDivFusion, DivFusion);

mindspore/core/ops/fusion/div_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/embedding_lookup_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -23,6 +23,7 @@ namespace ops {
 void EmbeddingLookupFusion::set_max_norm(const float max_norm) { (void)this->AddAttr(kMaxNorm, MakeValue(max_norm)); }
 float EmbeddingLookupFusion::get_max_norm() const {
   auto value_ptr = GetAttr(kMaxNorm);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 void EmbeddingLookupFusion::Init(const float max_norm) { this->set_max_norm(max_norm); }

mindspore/core/ops/fusion/embedding_lookup_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/exp_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -37,14 +37,17 @@ void ExpFusion::set_shift(const float shift) { (void)this->AddAttr(kShift, MakeV
 
 float ExpFusion::get_base() const {
   auto value_ptr = GetAttr(kBase);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 float ExpFusion::get_scale() const {
   auto value_ptr = GetAttr(kScale);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 float ExpFusion::get_shift() const {
   auto value_ptr = GetAttr(kShift);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 

mindspore/core/ops/fusion/exp_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/full_connection.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -22,13 +22,25 @@ namespace mindspore {
 namespace ops {
 void FullConnection::set_has_bias(const bool has_bias) { (void)this->AddAttr(kHasBias, MakeValue(has_bias)); }
 
-bool FullConnection::get_has_bias() const { return GetValue<bool>(GetAttr(kHasBias)); }
+bool FullConnection::get_has_bias() const {
+  auto value_ptr = GetAttr(kHasBias);
+  MS_EXCEPTION_IF_NULL(value_ptr);
+  return GetValue<bool>(value_ptr);
+}
 
 void FullConnection::set_axis(const int64_t axis) { (void)this->AddAttr(kAxis, MakeValue(axis)); }
-int64_t FullConnection::get_axis() const { return GetValue<int64_t>(GetAttr(kAxis)); }
+int64_t FullConnection::get_axis() const {
+  auto value_ptr = GetAttr(kAxis);
+  MS_EXCEPTION_IF_NULL(value_ptr);
+  return GetValue<int64_t>(value_ptr);
+}
 
 void FullConnection::set_use_axis(const bool use_axis) { (void)this->AddAttr(kUseAxis, MakeValue(use_axis)); }
-bool FullConnection::get_use_axis() const { return GetValue<bool>(GetAttr(kUseAxis)); }
+bool FullConnection::get_use_axis() const {
+  auto value_ptr = GetAttr(kUseAxis);
+  MS_EXCEPTION_IF_NULL(value_ptr);
+  return GetValue<bool>(value_ptr);
+}
 
 void FullConnection::set_activation_type(const ActivationType &activation_type) {
   int64_t swi = activation_type;
@@ -36,6 +48,7 @@ void FullConnection::set_activation_type(const ActivationType &activation_type)
 }
 ActivationType FullConnection::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 void FullConnection::Init(const bool has_bias, const int64_t axis, const bool use_axis,
@@ -57,14 +70,16 @@ AbstractBasePtr FullConnectionInfer(const abstract::AnalysisEnginePtr &, const P
   auto input1_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input1->BuildShape())[kShape];
   auto prim_axis = GetValue<int64_t>(primitive->GetAttr(kAxis));
   auto has_bias = GetValue<bool>(primitive->GetAttr(kHasBias));
+  const int64_t input_num_bias = 3;
+  const int64_t input_num = 2;
   if (has_bias) {
-    (void)CheckAndConvertUtils::CheckInteger("input_args.size()", input_args.size(), kEqual, 3, prim_name);
+    (void)CheckAndConvertUtils::CheckInteger("input_args.size()", input_args.size(), kEqual, input_num_bias, prim_name);
   } else {
-    (void)CheckAndConvertUtils::CheckInteger("input_args.size()", input_args.size(), kEqual, 2, prim_name);
+    (void)CheckAndConvertUtils::CheckInteger("input_args.size()", input_args.size(), kEqual, input_num, prim_name);
   }
   auto use_axis = GetValue<bool>(primitive->GetAttr(kUseAxis));
   if (use_axis && (prim_axis < 1 || prim_axis > (int64_t)input0_shape.size())) {
-    MS_EXCEPTION(ValueError) << "Full Connection axis invalid";
+    MS_EXCEPTION(ValueError) << "Full Connection axis is invalid";
   }
   int64_t new_k = 1;
   if (use_axis) {
@@ -72,7 +87,7 @@ AbstractBasePtr FullConnectionInfer(const abstract::AnalysisEnginePtr &, const P
       new_k *= input0_shape[t];
     }
     if (new_k != input1_shape[1]) {
-      MS_EXCEPTION(ValueError) << "Input1 size invalid";
+      MS_EXCEPTION(ValueError) << "Input1 size is invalid";
     }
   } else {
     new_k = input1_shape[1];
@@ -80,7 +95,7 @@ AbstractBasePtr FullConnectionInfer(const abstract::AnalysisEnginePtr &, const P
   if (has_bias) {
     auto input2_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[2]->BuildShape())[kShape];
     if (input2_shape[0] != input1_shape[0]) {
-      MS_EXCEPTION(ValueError) << "Bias size invalid";
+      MS_EXCEPTION(ValueError) << "Bias size is invalid";
     }
   }
   std::vector<int64_t> out_shape = {(int64_t)input0_shape.size()};

mindspore/core/ops/fusion/full_connection.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/l2_normalize_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -34,6 +34,7 @@ void L2NormalizeFusion::set_activation_type(const ActivationType &activation_typ
 
 ActivationType L2NormalizeFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameL2NormalizeFusion, L2NormalizeFusion);

mindspore/core/ops/fusion/l2_normalize_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/layer_norm_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -32,6 +32,7 @@ void LayerNormFusion::set_elementwise_affine(const bool elementwise_affine) {
 
 bool LayerNormFusion::get_elementwise_affine() const {
   auto value_ptr = GetAttr(kElementwiseAffine);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameLayerNormFusion, LayerNormFusion);

mindspore/core/ops/fusion/layer_norm_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/max_pool_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -40,24 +40,28 @@ void MaxPoolFusion::set_activation_type(ActivationType activation_type) {
 
 bool MaxPoolFusion::get_global() const {
   auto value_ptr = GetAttr(kGlobal);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 
 ActivationType MaxPoolFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 
 namespace {
 abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
+  MS_EXCEPTION_IF_NULL(input_args[0]);
   auto op_name = primitive->name();
   auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->GetShapeTrack())[kShape];
   auto format = Format(GetValue<int64_t>(primitive->GetAttr(kFormat)));
   if (format == NHWC) {
     in_shape = {in_shape[0], in_shape[3], in_shape[1], in_shape[2]};
   }
-  (void)CheckAndConvertUtils::CheckInteger("x_rank", SizeToLong(in_shape.size()), kEqual, 4, op_name);
+  const int64_t in_shape_size = 4;
+  (void)CheckAndConvertUtils::CheckInteger("x_rank", SizeToLong(in_shape.size()), kEqual, in_shape_size, op_name);
   auto kernel_size = GetValue<std::vector<int64_t>>(primitive->GetAttr(kKernelSize));
   auto pad_mode = PadMode(GetValue<int64_t>(primitive->GetAttr(kPadMode)));
   auto batch = in_shape[0];
@@ -84,21 +88,22 @@ abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<A
     out_shape = {batch, out_h, out_w, channel};
   }
   if (std::any_of(out_shape.begin(), out_shape.end(), [](int64_t a) { return a <= 0; })) {
-    MS_LOG(EXCEPTION) << "Kernel size is not valid.";
+    MS_LOG(EXCEPTION) << "Kernel size is invalid.";
   }
   return std::make_shared<abstract::Shape>(out_shape);
 }
 
 TypePtr InferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
-  if (std::any_of(input_args.begin(), input_args.end(), [](AbstractBasePtr a) { return a == nullptr; })) {
-    MS_LOG(EXCEPTION) << "nullptr";
-  }
   return input_args[0]->BuildType();
 }
 }  // namespace
 
 AbstractBasePtr MaxPoolFusionInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                    const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  for (auto item : input_args) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
   return std::make_shared<abstract::AbstractTensor>(InferType(primitive, input_args),
                                                     InferShape(primitive, input_args)->shape());
 }

mindspore/core/ops/fusion/max_pool_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/mul_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -29,6 +29,7 @@ void MulFusion::set_activation_type(const ActivationType &activation_type) {
 }
 ActivationType MulFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 void MulFusion::Init(const ActivationType &activation_type) { this->set_activation_type(activation_type); }

mindspore/core/ops/fusion/mul_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/pad_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -39,10 +39,12 @@ void PadFusion::set_constant_value(const float constant_value) {
 
 PaddingMode PadFusion::get_padding_mode() const {
   auto value_ptr = GetAttr(kPaddingMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return PaddingMode(GetValue<int64_t>(value_ptr));
 }
 float PadFusion::get_constant_value() const {
   auto value_ptr = GetAttr(kConstantValue);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 

mindspore/core/ops/fusion/pad_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/partial_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -25,6 +25,7 @@ void PartialFusion::set_sub_graph_index(const int64_t sub_graph_index) {
 }
 int64_t PartialFusion::get_sub_graph_index() const {
   auto value_ptr = GetAttr(kSubGraphIndex);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNamePartialFusion, PartialFusion);

mindspore/core/ops/fusion/partial_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/pow_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -42,6 +42,7 @@ abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<A
 }
 
 TypePtr InferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(prim);
   for (const auto &item : input_args) {
     MS_EXCEPTION_IF_NULL(item);
   }
@@ -54,6 +55,10 @@ TypePtr InferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &
 
 AbstractBasePtr PowFusionInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  const int64_t input_num = 2;
+  CheckAndConvertUtils::CheckInteger("PowFusion infer", SizeToLong(input_args.size()), kGreaterEqual, input_num,
+                                     primitive->name());
   return std::make_shared<abstract::AbstractTensor>(InferType(primitive, input_args),
                                                     InferShape(primitive, input_args)->shape());
 }

mindspore/core/ops/fusion/pow_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/prelu_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -36,10 +36,12 @@ void PReLUFusion::set_slope(const std::vector<float> &slope) { (void)this->AddAt
 
 bool PReLUFusion::get_channel_shared() const {
   auto value_ptr = GetAttr(kChannelShared);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 std::vector<float> PReLUFusion::get_slope() const {
   auto value_ptr = GetAttr(kSlope);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<float>>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNamePReLUFusion, PReLUFusion);

mindspore/core/ops/fusion/prelu_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/reduce_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -41,21 +41,25 @@ void ReduceFusion::set_coeff(const float coeff) { (void)this->AddAttr(kCoeff, Ma
 
 bool ReduceFusion::get_keep_dims() const {
   auto value_ptr = GetAttr(kKeepDims);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 
 ReduceMode ReduceFusion::get_mode() const {
   auto value_ptr = GetAttr(kMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ReduceMode(GetValue<int64_t>(value_ptr));
 }
 
 bool ReduceFusion::get_reduce_to_end() const {
   auto value_ptr = GetAttr(kReduceToEnd);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 
 float ReduceFusion::get_coeff() const {
   auto value_ptr = GetAttr(kCoeff);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 

mindspore/core/ops/fusion/reduce_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/scale_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -32,6 +32,7 @@ void ScaleFusion::set_activation_type(const ActivationType &activation_type) {
 
 ActivationType ScaleFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameScaleFusion, ScaleFusion);

mindspore/core/ops/fusion/scale_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/slice_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -26,6 +26,7 @@ void SliceFusion::set_axes(const std::vector<int64_t> &axes) { (void)this->AddAt
 
 std::vector<int64_t> SliceFusion::get_axes() const {
   auto value_ptr = GetAttr(kAxes);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -39,6 +40,8 @@ AbstractBasePtr SliceFusionInfer(const abstract::AnalysisEnginePtr &, const Prim
   auto size_v = input_args[2]->BuildValue();
   auto x_type = input_args[0]->BuildType();
   MS_EXCEPTION_IF_NULL(x_type);
+  MS_EXCEPTION_IF_NULL(begin_v);
+  MS_EXCEPTION_IF_NULL(size_v);
   auto tensor_type = x_type->cast<TensorTypePtr>();
   MS_EXCEPTION_IF_NULL(tensor_type);
   auto data_type = tensor_type->element();

mindspore/core/ops/fusion/slice_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/sub_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -29,6 +29,7 @@ void SubFusion::set_activation_type(const ActivationType &activation_type) {
 
 ActivationType SubFusion::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 REGISTER_PRIMITIVE_C(kNameSubFusion, SubFusion);

mindspore/core/ops/fusion/sub_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/tile_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -26,6 +26,7 @@ void TileFusion::set_dims(const std::vector<int64_t> &dims) { (void)this->AddAtt
 
 std::vector<int64_t> TileFusion::get_dims() const {
   auto value_ptr = GetAttr(kDims);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameTileFusion, TileFusion);

mindspore/core/ops/fusion/tile_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/fusion/topk_fusion.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -32,11 +32,13 @@ void TopKFusion::set_largest(const int64_t largest) { (void)this->AddAttr(kLarge
 
 int64_t TopKFusion::get_axis() const {
   auto value_ptr = GetAttr(kAxis);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
 int64_t TopKFusion::get_largest() const {
   auto value_ptr = GetAttr(kLargest);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameTopKFusion, TopKFusion);

mindspore/core/ops/fusion/topk_fusion.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/activation_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -38,6 +38,7 @@ void ActivationGrad::set_activation_type(const ActivationType &type) {
 
 ActivationType ActivationGrad::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 
@@ -45,6 +46,7 @@ void ActivationGrad::set_alpha(const float alpha) { (void)this->AddAttr(kAlpha,
 
 float ActivationGrad::get_alpha() const {
   auto value_ptr = GetAttr(kAlpha);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameActivationGrad, ActivationGrad);

mindspore/core/ops/grad/activation_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/add_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/add_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/avg_pool_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/avg_pool_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/batch_norm_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -31,6 +31,7 @@ void BatchNormGrad::set_epsilon(const float epsilon) { (void)this->AddAttr(kEpsi
 
 float BatchNormGrad::get_epsilon() const {
   auto value_ptr = this->GetAttr(kEpsilon);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 
@@ -38,15 +39,19 @@ void BatchNormGrad::set_is_training(const bool is_training) { this->AddAttr(kIsT
 
 bool BatchNormGrad::get_is_training() const {
   auto value_ptr = this->GetAttr(kIsTraining);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 
 AbstractBasePtr BatchNormGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                    const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
-  MS_EXCEPTION_IF_NULL(input_args[1]);
+  for (auto item : input_args) {
-  MS_EXCEPTION_IF_NULL(input_args[2]);
+    MS_EXCEPTION_IF_NULL(item);
-  MS_EXCEPTION_IF_NULL(input_args[3]);
+  }
+  const int64_t input_num = 5;
+  CheckAndConvertUtils::CheckInteger("BatchNormGrad infer", SizeToLong(input_args.size()), kGreaterEqual, input_num,
+                                     primitive->name());
   auto y_backprop_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[kShape];
   auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[1]->BuildShape())[kShape];
   CheckAndConvertUtils::Check("BatchNorm y_backprop_shape", y_backprop_shape, kEqual, "BatchNorm x_shape", x_shape);

mindspore/core/ops/grad/batch_norm_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/binary_cross_entropy_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -38,9 +38,6 @@ abstract::ShapePtr BinaryCrossEntroyGradInferShape(const PrimitivePtr &primitive
 }
 
 TypePtr BinaryCrossEntroyGradInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
-  for (const auto &item : input_args) {
-    MS_EXCEPTION_IF_NULL(item);
-  }
   const std::set<TypePtr> valid_types = {kFloat16, kFloat32};
   std::map<std::string, TypePtr> types;
   types.emplace("x_shape", input_args[0]->BuildType());
@@ -67,6 +64,13 @@ Reduction BinaryCrossEntropyGrad::get_reduction() const {
 
 AbstractBasePtr BinaryCrossEntropyGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                             const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  for (const auto &item : input_args) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
+  const int64_t input_num = 4;
+  CheckAndConvertUtils::CheckInteger("BinaryCrossEntropyGrad infer", SizeToLong(input_args.size()), kGreaterEqual,
+                                     input_num, primitive->name());
   return std::make_shared<abstract::AbstractTensor>(BinaryCrossEntroyGradInferType(primitive, input_args),
                                                     BinaryCrossEntroyGradInferShape(primitive, input_args)->shape());
 }

mindspore/core/ops/grad/binary_cross_entropy_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/bn_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -30,6 +30,7 @@ void BNGrad::set_eps(const float eps) { (void)this->AddAttr(kEps, MakeValue(eps)
 
 float BNGrad::get_eps() const {
   auto value_ptr = this->GetAttr(kEps);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 
@@ -37,6 +38,7 @@ void BNGrad::set_momentum(const float momentum) { (void)this->AddAttr(kMomentum,
 
 float BNGrad::get_momentum() const {
   auto value_ptr = this->GetAttr(kMomentum);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameBNGrad, BNGrad);

mindspore/core/ops/grad/bn_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/conv2d_backprop_filter.cc

@@ -71,6 +71,7 @@ void Conv2DBackpropFilter::set_out_channel(const int64_t out_channel) {
 
 int64_t Conv2DBackpropFilter::get_out_channel() const {
   auto value_ptr = GetAttr(kOutChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -80,6 +81,7 @@ void Conv2DBackpropFilter::set_kernel_size(const std::vector<int64_t> &kernel_si
 
 std::vector<int64_t> Conv2DBackpropFilter::get_kernel_size() const {
   auto value_ptr = GetAttr(kKernelSize);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -90,6 +92,7 @@ void Conv2DBackpropFilter::set_pad_mode(const PadMode &pad_mode) {
 
 PadMode Conv2DBackpropFilter::get_pad_mode() const {
   auto value_ptr = GetAttr(kPadMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return PadMode(GetValue<int64_t>(value_ptr));
 }
 
@@ -99,6 +102,7 @@ void Conv2DBackpropFilter::set_pad_list(const std::vector<int64_t> &pad_list) {
 
 std::vector<int64_t> Conv2DBackpropFilter::get_pad_list() const {
   auto value_ptr = GetAttr(kPadList);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -106,6 +110,7 @@ void Conv2DBackpropFilter::set_mode(const int64_t mode) { (void)this->AddAttr(kM
 
 int64_t Conv2DBackpropFilter::get_mode() const {
   auto value_ptr = GetAttr(kMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -113,6 +118,7 @@ void Conv2DBackpropFilter::set_stride(const std::vector<int64_t> &stride) { this
 
 std::vector<int64_t> Conv2DBackpropFilter::get_stride() const {
   auto value_ptr = GetAttr(kStride);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -122,6 +128,7 @@ void Conv2DBackpropFilter::set_dilation(const std::vector<int64_t> &dilation) {
 
 std::vector<int64_t> Conv2DBackpropFilter::get_dilation() const {
   auto value_ptr = GetAttr(kDilation);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -129,6 +136,7 @@ void Conv2DBackpropFilter::set_group(const int64_t group) { (void)this->AddAttr(
 
 int64_t Conv2DBackpropFilter::get_group() const {
   auto value_ptr = GetAttr(kGroup);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -139,6 +147,7 @@ void Conv2DBackpropFilter::set_format(const Format &format) {
 
 Format Conv2DBackpropFilter::get_format() const {
   auto value_ptr = GetAttr(kFormat);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return Format(GetValue<int64_t>(value_ptr));
 }
 

mindspore/core/ops/grad/conv2d_backprop_filter.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/conv2d_backprop_input.cc

@@ -172,51 +172,61 @@ void Conv2DBackpropInput::set_pad_list(const std::vector<int64_t> &pad_list) {
 
 int64_t Conv2DBackpropInput::get_out_channel() const {
   auto value_ptr = GetAttr(kOutChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
 std::vector<int64_t> Conv2DBackpropInput::get_kernel_size() const {
   auto value_ptr = GetAttr(kKernelSize);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
 std::vector<int64_t> Conv2DBackpropInput::get_stride() const {
   auto value_ptr = GetAttr(kStride);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
 std::vector<int64_t> Conv2DBackpropInput::get_dilation() const {
   auto value_ptr = GetAttr(kDilation);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
 PadMode Conv2DBackpropInput::get_pad_mode() const {
   auto value_ptr = GetAttr(kPadMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return PadMode(GetValue<int64_t>(value_ptr));
 }
 
 std::vector<int64_t> Conv2DBackpropInput::get_pad() const {
   auto value_ptr = GetAttr(kPad);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
 int64_t Conv2DBackpropInput::get_mode() const {
   auto value_ptr = GetAttr(kMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
 int64_t Conv2DBackpropInput::get_group() const {
   auto value_ptr = GetAttr(kGroup);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
 Format Conv2DBackpropInput::get_format() const {
   auto value_ptr = GetAttr(kFormat);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return Format(GetValue<int64_t>(value_ptr));
 }
 
 std::vector<int64_t> Conv2DBackpropInput::get_pad_list() const {
   auto value_ptr = GetAttr(kPadList);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 REGISTER_PRIMITIVE_EVAL_IMPL(Conv2DBackpropInput, prim::kPrimConv2DBackpropInput, Conv2DBackpropInputInfer, nullptr,

mindspore/core/ops/grad/conv2d_backprop_input.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/de_conv2d_grad_filter.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -45,6 +45,7 @@ void DeConv2DGradFilter::set_in_channel(const int64_t in_channel) {
 
 int64_t DeConv2DGradFilter::get_in_channel() const {
   auto value_ptr = GetAttr(kInChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -54,6 +55,7 @@ void DeConv2DGradFilter::set_out_channel(const int64_t out_channel) {
 
 int64_t DeConv2DGradFilter::get_out_channel() const {
   auto value_ptr = GetAttr(kOutChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -63,6 +65,7 @@ void DeConv2DGradFilter::set_kernel_size(const std::vector<int64_t> &kernel_size
 
 std::vector<int64_t> DeConv2DGradFilter::get_kernel_size() const {
   auto value_ptr = GetAttr(kKernelSize);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -73,6 +76,7 @@ void DeConv2DGradFilter::set_pad_mode(const PadMode &pad_mode) {
 
 PadMode DeConv2DGradFilter::get_pad_mode() const {
   auto value_ptr = GetAttr(kPadMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return PadMode(GetValue<int64_t>(value_ptr));
 }
 
@@ -82,6 +86,7 @@ void DeConv2DGradFilter::set_pad_list(const std::vector<int64_t> &pad_list) {
 
 std::vector<int64_t> DeConv2DGradFilter::get_pad_list() const {
   auto value_ptr = GetAttr(kPadList);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -91,6 +96,7 @@ void DeConv2DGradFilter::set_stride(const std::vector<int64_t> &stride) {
 
 std::vector<int64_t> DeConv2DGradFilter::get_stride() const {
   auto value_ptr = GetAttr(kStride);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -100,6 +106,7 @@ void DeConv2DGradFilter::set_dilation(const std::vector<int64_t> &dilation) {
 
 std::vector<int64_t> DeConv2DGradFilter::get_dilation() const {
   auto value_ptr = GetAttr(kDilation);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -107,6 +114,7 @@ void DeConv2DGradFilter::set_group(const int64_t group) { (void)this->AddAttr(kG
 
 int64_t DeConv2DGradFilter::get_group() const {
   auto value_ptr = GetAttr(kGroup);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -117,6 +125,7 @@ void DeConv2DGradFilter::set_format(const Format &format) {
 
 Format DeConv2DGradFilter::get_format() const {
   auto value_ptr = GetAttr(kFormat);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return Format(GetValue<int64_t>(value_ptr));
 }
 
@@ -127,6 +136,7 @@ void DeConv2DGradFilter::set_activation_type(const ActivationType &activation_ty
 
 ActivationType DeConv2DGradFilter::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 
@@ -134,6 +144,7 @@ void DeConv2DGradFilter::set_has_bias(const bool has_bias) { (void)this->AddAttr
 
 bool DeConv2DGradFilter::get_has_bias() const {
   auto value_ptr = GetAttr(kHasBias);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 REGISTER_PRIMITIVE_C(kNameDeConv2DGradFilter, DeConv2DGradFilter);

mindspore/core/ops/grad/de_conv2d_grad_filter.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/div_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/div_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/dropout_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -28,6 +28,7 @@ void DropoutGrad::set_keep_prob(const float keep_prob) {
 
 float DropoutGrad::get_keep_prob() const {
   auto value_ptr = GetAttr(kKeepProb);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<float>(value_ptr);
 }
 
@@ -55,6 +56,13 @@ TypePtr DropoutGradInferType(const PrimitivePtr &prim, const std::vector<Abstrac
 
 AbstractBasePtr DropoutGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                  const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  for (auto item : input_args) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
+  const int64_t input_num = 2;
+  CheckAndConvertUtils::CheckInteger("DropoutGrad infer", SizeToLong(input_args.size()), kGreaterEqual, input_num,
+                                     primitive->name());
   return std::make_shared<abstract::AbstractTensor>(DropoutGradInferType(primitive, input_args),
                                                     DropoutGradInferShape(primitive, input_args)->shape());
 }

mindspore/core/ops/grad/dropout_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/flatten_grad.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -22,7 +22,8 @@ AbstractBasePtr FlattenGradInfer(const abstract::AnalysisEnginePtr &, const Prim
                                  const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
   auto prim_name = primitive->name();
-  (void)CheckAndConvertUtils::CheckInteger("input number", SizeToLong(input_args.size()), kEqual, 2, prim_name);
+  const int64_t input_num = 2;
+  (void)CheckAndConvertUtils::CheckInteger("input number", SizeToLong(input_args.size()), kEqual, input_num, prim_name);
   for (const auto &item : input_args) {
     MS_EXCEPTION_IF_NULL(item);
   }

mindspore/core/ops/grad/flatten_grad.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/group_conv2d_grad_input.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -46,6 +46,7 @@ void GroupConv2DGradInput::set_in_channel(const int64_t &in_channel) {
 
 int64_t GroupConv2DGradInput::get_in_channel() const {
   auto value_ptr = GetAttr(kInChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -55,6 +56,7 @@ void GroupConv2DGradInput::set_out_channel(const int64_t &out_channel) {
 
 int64_t GroupConv2DGradInput::get_out_channel() const {
   auto value_ptr = GetAttr(kOutChannel);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -64,6 +66,7 @@ void GroupConv2DGradInput::set_kernel_size(const std::vector<int64_t> &kernel_si
 
 std::vector<int64_t> GroupConv2DGradInput::get_kernel_size() const {
   auto value_ptr = GetAttr(kKernelSize);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -74,6 +77,7 @@ void GroupConv2DGradInput::set_pad_mode(const PadMode &pad_mode) {
 
 PadMode GroupConv2DGradInput::get_pad_mode() const {
   auto value_ptr = GetAttr(kPadMode);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return PadMode(GetValue<int64_t>(value_ptr));
 }
 
@@ -83,6 +87,7 @@ void GroupConv2DGradInput::set_pad_list(const std::vector<int64_t> &pad_list) {
 
 std::vector<int64_t> GroupConv2DGradInput::get_pad_list() const {
   auto value_ptr = GetAttr(kPadList);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -90,6 +95,7 @@ void GroupConv2DGradInput::set_stride(const std::vector<int64_t> &stride) { this
 
 std::vector<int64_t> GroupConv2DGradInput::get_stride() const {
   auto value_ptr = GetAttr(kStride);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -99,6 +105,7 @@ void GroupConv2DGradInput::set_dilation(const std::vector<int64_t> &dilation) {
 
 std::vector<int64_t> GroupConv2DGradInput::get_dilation() const {
   auto value_ptr = GetAttr(kDilation);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
@@ -106,6 +113,7 @@ void GroupConv2DGradInput::set_group(const int64_t &group) { (void)this->AddAttr
 
 int64_t GroupConv2DGradInput::get_group() const {
   auto value_ptr = GetAttr(kGroup);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 
@@ -114,7 +122,9 @@ void GroupConv2DGradInput::set_input_shape(const std::vector<int64_t> &input_sha
 }
 
 std::vector<int64_t> GroupConv2DGradInput::get_input_shape() const {
-  return GetValue<std::vector<int64_t>>(GetAttr(kInputShape));
+  auto value_ptr = GetAttr(kInputShape);
+  MS_EXCEPTION_IF_NULL(value_ptr);
+  return GetValue<std::vector<int64_t>>(value_ptr);
 }
 
 void GroupConv2DGradInput::set_format(const Format &format) {
@@ -124,6 +134,7 @@ void GroupConv2DGradInput::set_format(const Format &format) {
 
 Format GroupConv2DGradInput::get_format() const {
   auto value_ptr = GetAttr(kFormat);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return Format(GetValue<int64_t>(value_ptr));
 }
 
@@ -134,6 +145,7 @@ void GroupConv2DGradInput::set_activation_type(const ActivationType &activation_
 
 ActivationType GroupConv2DGradInput::get_activation_type() const {
   auto value_ptr = GetAttr(kActivationType);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return ActivationType(GetValue<int64_t>(value_ptr));
 }
 
@@ -141,6 +153,7 @@ void GroupConv2DGradInput::set_has_bias(const bool has_bias) { (void)this->AddAt
 
 bool GroupConv2DGradInput::get_has_bias() const {
   auto value_ptr = GetAttr(kHasBias);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<bool>(value_ptr);
 }
 AbstractBasePtr GroupConv2DGradInputInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
@@ -152,11 +165,16 @@ AbstractBasePtr GroupConv2DGradInputInfer(const abstract::AnalysisEnginePtr &, c
   MS_EXCEPTION_IF_NULL(input_args[0]);
 
   // Infer shape
-  auto shape = GetValue<std::vector<int64_t>>(primitive->GetAttr(kInputShape));
+  auto shape_ptr = primitive->GetAttr(kInputShape);
+  MS_EXCEPTION_IF_NULL(shape_ptr);
+  auto shape = GetValue<std::vector<int64_t>>(shape_ptr);
 
   // Infer type
-  auto type = input_args[0]->BuildType()->cast<TensorTypePtr>()->element();
+  auto type_ptr = input_args[0]->BuildType();
-
+  MS_EXCEPTION_IF_NULL(type_ptr);
+  auto type_tensor_ptr = type_ptr->cast<TensorTypePtr>();
+  MS_EXCEPTION_IF_NULL(type_tensor_ptr);
+  auto type = type_tensor_ptr->element();
   return std::make_shared<abstract::AbstractTensor>(type, shape);
 }
 REGISTER_PRIMITIVE_C(kNameGroupConv2DGradInput, GroupConv2DGradInput);

mindspore/core/ops/grad/group_conv2d_grad_input.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.

mindspore/core/ops/grad/layer_norm_grad.cc

@@ -48,10 +48,12 @@ void LayerNormGrad::set_begin_params_axis(const int64_t begin_params_axis) {
 }
 int64_t LayerNormGrad::get_begin_norm_axis() const {
   auto value_ptr = this->GetAttr(kBeginNormAxis);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 int64_t LayerNormGrad::get_begin_params_axis() const {
   auto value_ptr = this->GetAttr(kBeginParamsAxis);
+  MS_EXCEPTION_IF_NULL(value_ptr);
   return GetValue<int64_t>(value_ptr);
 }
 REGISTER_PRIMITIVE_EVAL_IMPL(LayerNormGrad, prim::kPrimLayerNormGrad, LayerNormGradInfer, nullptr, true);