#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {

PathConfig::PathConfig(const string& output_dir, const string& source_dir,
                       const string& api_dir_list,
                       const std::vector<string> op_names)
    : output_path(output_dir), op_names(op_names) {
  api_dirs = str_util::Split(api_dir_list, ",", str_util::SkipEmpty());

  setenv("TF_DUMP_GRAPH_PREFIX", testing::TmpDir().c_str(), 1);
  std::string filepath =
      testing::TmpDir() + "/" + mlir::TF::kStandardPipelineBefore + ".mlir";

  std::string output_dump = testing::TmpDir() + "/" + "output_dump.txt";

  TF_ASSERT_OK(mlir::TF::RunBridgeWithStandardPipeline(
      module_ref.get(),
      /*enable_logging=*/true, /*enable_inliner=*/false));

  std::string errorMessage;

  const OpDef* op_def;
  TF_RETURN_IF_ERROR(OpRegistry::Global()->LookUpOpDef(node_def.op(), &op_def));
  DataTypeVector input_dtys, output_dtys;
  TF_RETURN_IF_ERROR(InputTypesForNode(node_def, *op_def, &input_dtys));
  TF_RETURN_IF_ERROR(OutputTypesForNode(node_def, *op_def, &output_dtys));

  mlir::MLIRContext* context = tfr_module_.getContext();
  llvm::SmallVector<mlir::Type, 4> input_tys, output_tys;