Changed reinterpret_cast to static_cast

Author: RajivChitale

MLModelRunner/PTModelRunner/PTModelRunner.cpp

@@ -36,7 +36,7 @@ namespace MLBridge
   void *PTModelRunner::evaluateUntyped()
   {
 
-    if ((*reinterpret_cast<TensorVec*>(this->SerDes->getRequest())).empty())
+    if ((*static_cast<TensorVec*>(this->SerDes->getRequest())).empty())
     {
       llvm::errs() << "Input vector is empty.\n";
       return nullptr;
@@ -45,8 +45,8 @@ namespace MLBridge
     try
     {
 
-      std::vector<torch::Tensor> *outputTensors = reinterpret_cast<std::vector<torch::Tensor>*>(this->SerDes->getResponse());
-      auto outputs = reinterpret_cast<torch::inductor::AOTIModelContainerRunnerCpu*>(this->CompiledModel)->run((*reinterpret_cast<TensorVec*>(this->SerDes->getRequest())));
+      std::vector<torch::Tensor> *outputTensors = static_cast<std::vector<torch::Tensor>*>(this->SerDes->getResponse());
+      auto outputs = static_cast<torch::inductor::AOTIModelContainerRunnerCpu*>(this->CompiledModel)->run((*static_cast<TensorVec*>(this->SerDes->getRequest())));
       for (auto i = outputs.begin(); i != outputs.end(); ++i)
         (*(outputTensors)).push_back(*i);
       void *rawData = this->SerDes->deserializeUntyped(outputTensors);

SerDes/pytorchSerDes/pytorchSerDes.cpp

@@ -24,54 +24,54 @@ PytorchSerDes::PytorchSerDes() : BaseSerDes(BaseSerDes::Kind::Pytorch)  {
 
 void PytorchSerDes::setFeature(const std::string &Name, const int Value) {
     auto tensor = torch::tensor({Value}, torch::kInt32);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const long Value) {
     auto tensor = torch::tensor({Value}, torch::kInt64);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const float Value) {
     auto tensor = torch::tensor({Value}, torch::kFloat32);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const double Value) {
     auto tensor = torch::tensor({Value}, torch::kFloat64);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::string Value) {
     std::vector<int8_t> encoded_str(Value.begin(), Value.end());
     auto tensor = torch::tensor(encoded_str, torch::kInt8);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const bool Value) {
     auto tensor = torch::tensor({Value}, torch::kBool);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::vector<int> &Value) {
     auto tensor = torch::tensor(Value, torch::kInt32);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::vector<long> &Value) {
     auto tensor = torch::tensor(Value, torch::kInt64);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::vector<float> &Value) {
     auto tensor = torch::tensor(Value, torch::kFloat32);
     tensor = tensor.reshape({1, Value.size()});
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::vector<double> &Value) {
     auto tensor = torch::tensor(Value, torch::kFloat64);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::vector<std::string> &Value) {
@@ -81,21 +81,21 @@ void PytorchSerDes::setFeature(const std::string &Name, const std::vector<std::s
         flat_vec.push_back('\0'); // Null-terminate each string
     }
     auto tensor = torch::tensor(flat_vec, torch::kInt8);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 void PytorchSerDes::setFeature(const std::string &Name, const std::vector<bool> &Value) {
     std::vector<uint8_t> bool_vec(Value.begin(), Value.end());
     auto tensor = torch::tensor(bool_vec, torch::kUInt8);
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
+    static_cast<TensorVec*>(this->RequestVoid)->push_back(tensor.clone());
 }
 
 // void PytorchSerDes::setRequest(void *Request) {
-//     CompiledModel = reinterpret_cast<torch::inductor::AOTIModelContainerRunnerCpu *>(Request);
+//     CompiledModel = static_cast<torch::inductor::AOTIModelContainerRunnerCpu *>(Request);
 // }
 
 void PytorchSerDes::cleanDataStructures() {
-    reinterpret_cast<TensorVec*>(this->RequestVoid)->clear(); // Clear the input vector
+    static_cast<TensorVec*>(this->RequestVoid)->clear(); // Clear the input vector
 }
 
 void *PytorchSerDes::deserializeUntyped(void *Data) {
@@ -104,7 +104,7 @@ void *PytorchSerDes::deserializeUntyped(void *Data) {
     }
 
     // Assume Data is a pointer to a vector of tensors
-    std::vector<torch::Tensor> *serializedTensors = reinterpret_cast<TensorVec *>(Data);
+    std::vector<torch::Tensor> *serializedTensors = static_cast<TensorVec *>(Data);
 
     if (serializedTensors->empty()) {
         return nullptr;
@@ -138,7 +138,7 @@ void *PytorchSerDes::deserializeUntyped(void *Data) {
 
 void *PytorchSerDes::getSerializedData() {
     return this->ResponseVoid;   // TODO - check
-    // TensorVec serializedData = *reinterpret_cast<TensorVec*>(this->ReponseVoid);
+    // TensorVec serializedData = *static_cast<TensorVec*>(this->ReponseVoid);
 
     // // Allocate memory for the output and copy the serialized data
     // auto *output = new TensorVec(serializedData);
@@ -148,7 +148,7 @@ void *PytorchSerDes::getSerializedData() {
  template <typename T>
     std::vector<T> *PytorchSerDes::copyTensorToVect(void *serializedTensors) {
         auto *ret = new std::vector<T>();
-        for (const auto &tensor : *reinterpret_cast<TensorVec*>(serializedTensors)) {
+        for (const auto &tensor : *static_cast<TensorVec*>(serializedTensors)) {
             ret->insert(ret->end(), tensor.data_ptr<T>(), tensor.data_ptr<T>() + tensor.numel());
         }
         return ret;