ParseRNN.cxx

Go to the documentation of this file.

#include "TMVA/RModelParser_ONNX.hxx"
#include "TMVA/ROperator_RNN.hxx"
#include "onnx_proto3.pb.h"
 
namespace TMVA {
namespace Experimental {
namespace SOFIE {
 
ParserFuncSignature ParseRNN = [](RModelParser_ONNX &parser, const onnx::NodeProto &nodeproto) {
   ETensorType input_type;
 
   auto input_name = nodeproto.input(0);
   if (parser.IsRegisteredTensorType(input_name)) {
      input_type = parser.GetTensorType(input_name);
   } else {
      throw std::runtime_error("TMVA::SOFIE ONNX Parser RNN op has input tensor " + input_name +
                               " but its type is not yet registered");
   }
 
   std::unique_ptr<ROperator> op;
 
   std::vector<float> attr_activation_alpha = {};
   std::vector<float> attr_activation_beta = {};
   std::vector<std::string> attr_activations = {};
   float attr_clip = 0.;
   std::string attr_direction = "forward";
   size_t attr_hidden_size = 0;
   size_t attr_layout = 0;
 
   for (int_t i = 0; i < nodeproto.attribute_size(); i++) {
      std::string attribute_name = nodeproto.attribute(i).name();
      if (attribute_name == "activation_alpha") {
         attr_activation_alpha = {nodeproto.attribute(i).floats().begin(), nodeproto.attribute(i).floats().end()};
      } else if (attribute_name == "activation_beta") {
         attr_activation_beta = {nodeproto.attribute(i).floats().begin(), nodeproto.attribute(i).floats().end()};
      } else if (attribute_name == "activations") {
         attr_activations = {nodeproto.attribute(i).strings().begin(), nodeproto.attribute(i).strings().end()};
      } else if (attribute_name == "clip") {
         attr_clip = nodeproto.attribute(i).i();
      } else if (attribute_name == "direction") {
         attr_direction = nodeproto.attribute(i).s();
      } else if (attribute_name == "hidden_size") {
         attr_hidden_size = nodeproto.attribute(i).i();
      } else if (attribute_name == "layout") {
         attr_layout = nodeproto.attribute(i).i();
      } else {
         std::cout << "TMVA SOFIE Warning - Model Loading - Attribute " << attribute_name << " in OperatorNode "
                   << nodeproto.name() << " is not defined in ONNX IR and not applied!\n";
      }
   }
 
   // Optional inputs and outputs
   std::string name_b = "";
   std::string name_sequence_lens = "";
   std::string name_initial_h = "";
   std::string name_y = "";
   std::string name_y_h = "";
   if (nodeproto.input_size() > 3) {
      name_b = nodeproto.input(3);
   }
   if (nodeproto.input_size() > 4) {
      name_sequence_lens = nodeproto.input(4);
   }
   if (nodeproto.input_size() > 5) {
      name_initial_h = nodeproto.input(5);
   }
   if (nodeproto.output_size() > 0) {
      name_y = nodeproto.output(0);
   }
   if (nodeproto.output_size() > 1) {
      name_y_h = nodeproto.output(1);
   }
 
   switch (input_type) {
   case ETensorType::FLOAT:
      op.reset(new ROperator_RNN<float>(attr_activation_alpha, attr_activation_beta, attr_activations, attr_clip,
                                        attr_direction, attr_hidden_size, attr_layout, nodeproto.input(0),
                                        nodeproto.input(1), nodeproto.input(2), name_b, name_sequence_lens,
                                        name_initial_h, name_y, name_y_h));
      break;
   default:
      throw std::runtime_error("TMVA::SOFIE - Unsupported - Operator RNN does not yet support input type " +
                               std::to_string(static_cast<int>(input_type)));
   }
 
   for (const auto &name : {name_y, name_y_h}) {
      if (!parser.IsRegisteredTensorType(name)) {
         parser.RegisterTensorType(name, input_type);
      }
   }
 
   return op;
};
 
} // namespace SOFIE
} // namespace Experimental
} // namespace TMVA