!5022 delete GetPrimitiveT

Merge pull request !5022 from yeyunpeng2020/master

mindspore/lite/tools/converter/converter.cc

@@ -73,13 +73,11 @@ void Converter::FreeFuncGraph(const FuncGraphPtr &func_graph) {
       return;
     }
     if (primT->value.type == schema::PrimitiveType_TupleGetItem ||
-        primT->value.type == schema::PrimitiveType_MakeTuple ||
-        primT->value.type == schema::PrimitiveType_Return) {
+        primT->value.type == schema::PrimitiveType_MakeTuple || primT->value.type == schema::PrimitiveType_Return) {
       delete primT;
       primitiveT_value->SetPrimitiveT(nullptr);
     }
   }
-  return;
 }
 MetaGraphT *Converter::Convert(const converter::Flags *flag) {
   // parse the model and weight file to generate inference data structure

mindspore/lite/tools/converter/quantizer/quantize_util.cc

@@ -93,7 +93,7 @@ bool QuantStrategy::CanOpPostQuantized(AnfNodePtr &node) const {
     return false;
   }
 
-  auto type = primitiveT_value->GetPrimitiveT()->value.type;
+  auto type = (schema::PrimitiveType)primitiveT_value->Type();
   MS_LOG(INFO) << "Primitive type: " << type;
   static const std::vector<schema::PrimitiveType> uint8OpList = {
     schema::PrimitiveType_Nchw2Nhwc, schema::PrimitiveType_Nhwc2Nchw,

mindspore/lite/tools/optimizer/common/gllo_utils.cc

@@ -170,7 +170,7 @@ bool AnfEqual(const BaseRef &a, const BaseRef &b) {
   if (a.m_ptr->isa<lite::PrimitiveC>() && b.m_ptr->isa<lite::PrimitiveC>()) {
     auto a_value_node_ptr = a.m_ptr->cast<PrimitiveCPtr>();
     auto b_value_node_ptr = b.m_ptr->cast<PrimitiveCPtr>();
-    return a_value_node_ptr->GetPrimitiveT()->value.type == b_value_node_ptr->GetPrimitiveT()->value.type;
+    return a_value_node_ptr->Type() == b_value_node_ptr->Type();
   }
 
   return a == b;
@@ -316,7 +316,7 @@ schema::PrimitiveType GetCNodeType(const BaseRef &n) {
   if (utils::isa<PrimitiveCPtr>(value)) {
     auto primitive = value->cast<PrimitiveCPtr>();
     MS_ASSERT(primitive != nullptr);
-    return primitive->GetPrimitiveT()->value.type;
+    return (schema::PrimitiveType)primitive->Type();
   } else if (utils::isa<Primitive>(value)) {
     auto primitive = value->cast<PrimitivePtr>();
     MS_ASSERT(primitive != nullptr);

mindspore/lite/tools/optimizer/fusion/constant_folding_fusion.cc

@@ -73,26 +73,6 @@ const std::vector<Tensor *> GetCNodeInputTensors(const CNodePtr &CNode) {
   }
   return input_tensors;
 }
-schema::Primitive *PackPrimitiveT(const CNodePtr &cnode) {
-  auto primitiveT_value = GetValueNode<std::shared_ptr<PrimitiveC>>(cnode->input(0));
-  if (primitiveT_value == nullptr) {
-    MS_LOG(ERROR) << "PrimitiveT_value is nullptr";
-    return nullptr;
-  }
-
-  auto *lite_primitive = primitiveT_value->GetPrimitiveT();
-  if (lite_primitive == nullptr) {
-    MS_LOG(ERROR) << "Primitive in primitiveT_value is nullptr";
-    return nullptr;
-  }
-
-  flatbuffers::FlatBufferBuilder builder(1024);
-  auto offset = schema::Primitive::Pack(builder, lite_primitive);
-  builder.Finish(offset);
-  auto buf = builder.GetBufferPointer();
-  auto primitive = flatbuffers::GetRoot<schema::Primitive>(buf);
-  return const_cast<schema::Primitive *>(primitive);
-}
 const ParameterPtr CreateNewParamter(const FuncGraphPtr &func_graph, Tensor *tensor) {
   auto parameter = func_graph->add_parameter();
   std::vector<int> shape;
@@ -175,16 +155,10 @@ const AnfNodePtr ConstFoldPass::Process(const FuncGraphPtr &func_graph, const An
       }
       MS_LOG(INFO) << "Begin fold node:" << input_node->fullname_with_scope();
       auto output_nums = GetOutputTensorNum(input_cnode);
+      auto primitiveT_value = GetValueNode<std::shared_ptr<PrimitiveC>>(input_cnode->input(0));
       std::vector<Tensor *> output_tensors{output_nums, new Tensor()};
-      auto scheam_primitive = PackPrimitiveT(input_cnode);
-      auto lite_primitive = mindspore::lite::PrimitiveC::UnPackFromSchemaPrimitive(scheam_primitive);
-      if (lite_primitive == nullptr) {
-        MS_LOG(ERROR) << "constant_folding schedule node lite primitive nullptr";
-        FreeInputTensor(&input_tensors);
-        return nullptr;
-      }
-      lite_primitive->InferShape(input_tensors, output_tensors);
-      auto lite_kernel = GetLiteKernel(input_tensors, output_tensors, lite_primitive);
+      primitiveT_value->InferShape(input_tensors, output_tensors);
+      auto lite_kernel = GetLiteKernel(input_tensors, output_tensors, primitiveT_value.get());
       if (lite_kernel == nullptr) {
         MS_LOG(ERROR) << "constant_folding schedule node lite kernel nullptr";
         FreeInputTensor(&input_tensors);

mindspore/lite/tools/optimizer/fusion/conv_bn_fusion.cc

@@ -22,6 +22,8 @@
 #include "utils/utils.h"
 #include "tools/optimizer/common/gllo_utils.h"
 #include "securec/include/securec.h"
+#include "src/ops/batch_norm.h"
+#include "src/ops/fused_batchnorm.h"
 
 namespace mindspore::opt {
 namespace {
@@ -94,7 +96,7 @@ const BaseRef ConvBatchNormFusion::DefinePattern() const {
   auto bn_mean_var = std::make_shared<CondVar>(IsParamNode);
   auto bn_variable_var = std::make_shared<CondVar>(IsParamNode);
   auto bn_other_var = std::make_shared<SeqVar>();
-  return VectorRef({bn_var, conv_var, bn_mean_var, bn_variable_var, bn_other_var});;
+  return VectorRef({bn_var, conv_var, bn_mean_var, bn_variable_var, bn_other_var});
 }
 // BatchNorm weight Tensor definition:
 // caffe
@@ -106,7 +108,7 @@ const BaseRef ConvBatchNormFusion::DefinePattern() const {
 //   estimated_mean  --2
 //   estimated_variance  --3
 const void ConvBatchNormFusion::InitTransParam(const CNodePtr &bn_node, int kernel_num, float *trans_scale,
-                                                       float *trans_bias) const {
+                                               float *trans_bias) const {
   MS_ASSERT(bn_node != nullptr);
   AnfNodePtr bn_mean_node = nullptr;
   AnfNodePtr bn_variance_node = nullptr;
@@ -119,13 +121,19 @@ const void ConvBatchNormFusion::InitTransParam(const CNodePtr &bn_node, int kern
     bn_variance_node = bn_node->input(kCaffeBNVarIndex);
     CheckIfNodeIsParam(bn_mean_node);
     CheckIfNodeIsParam(bn_variance_node);
-    eps = primitiveT_value->GetPrimitiveT()->value.AsBatchNorm()->epsilon;
+    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::BatchNorm>>(primitiveT_value));
+    auto primc = utils::cast<std::shared_ptr<mindspore::lite::BatchNorm>>(primitiveT_value);
+    MS_ASSERT(primc != nullptr);
+    eps = primc->GetEpsilon();
   } else if (GetCNodeType(bn_node) == schema::PrimitiveType_FusedBatchNorm) {
     bn_scale_node = bn_node->input(kTFBNScaleIndex);
     bn_bias_node = bn_node->input(kTFBNBiasIndex);
     bn_mean_node = bn_node->input(kTFBNMeanIndex);
     bn_variance_node = bn_node->input(kTFBNVarIndex);
-    eps = primitiveT_value->GetPrimitiveT()->value.AsFusedBatchNorm()->epsilon;
+    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::FusedBatchNorm>>(primitiveT_value));
+    auto primc = utils::cast<std::shared_ptr<mindspore::lite::FusedBatchNorm>>(primitiveT_value);
+    MS_ASSERT(primc != nullptr);
+    eps = primc->GetEpsilon();
   } else {
     MS_LOG(EXCEPTION) << "not caffe or tf batchnorm op.";
   }