int pointer_size = 0;                  // Size of a pointer in bytes.
};

// CompileGraph compiles the graph_def into an object file containing a function
// that performs the graph operations.
//
// The XLA compilation options are specified in the flags.
Status CompileGraph(GraphDef graph_def, const tf2xla::Config& config,
                    const MainFlags& flags, CompileResult* compile_result);

}

static TranslateToMLIRRegistration GraphdefToSplattedMlirTranslate(
    "graphdef-to-splatted-mlir", "graphdef-to-splatted-mlir",
    GraphdefToSplattedMlirTranslateFunction);

static Status CompileGraph(tensorflow::Graph* graph,
                           xla::CompileOnlyClient* client) {
  if (!graph || !client) {
    return Status(absl::StatusCode::kInvalidArgument,
                  "Invalid graph or client");
  }

  compile_result->pointer_size =
      xla::CompileOnlyClient::PointerSizeForTriple(aot_opts.triple());
  return absl::OkStatus();
}

}  // namespace

Status CompileGraph(GraphDef graph_def, const tf2xla::Config& config,
                    const MainFlags& flags, CompileResult* compile_result) {
  // Converts the graph into an XLA computation, and compiles the
  // computation.

    const NodeDef& node_def, absl::Span<const XlaArgument> args,
    absl::Span<const DataType> result_types) {
  // TODO(b/74182462): We implement this by creating a new dummy Graph including
  // _Arg nodes, and let CompileGraph walk it. This could be optimized.
  std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global()));

  // First create the actual node we care about computing.
  TF_ASSIGN_OR_RETURN(Node * main_node, graph->AddNode(node_def));

    auto args = SampleArgsForAddXY();

    // Compiles the graph.
    XlaCompiler compiler(GetDefaultXlaOptions());

    XlaCompiler::CompilationResult compilation_result;
    TF_RETURN_IF_ERROR(compiler.CompileGraph(XlaCompiler::CompileOptions(),
                                             "graph", std::move(graph), args,
                                             &compilation_result));

    args[1].shape = TensorShape({2});

    // Compiles the graph.
    XlaCompiler compiler(DefaultXlaOptions());

    XlaCompiler::CompilationResult compilation_result;
    TF_RETURN_IF_ERROR(compiler.CompileGraph(XlaCompiler::CompileOptions(),
                                             "graph", std::move(graph), args,
                                             &compilation_result));
    return compilation_result;
  }