(i.e. `obj[0]["x"]`).

    The function arg attribute
    `tf_saved_model.bound_input = @some_symbol_name` references a
    `tf_saved_model.global_tensor` that is bound to that function argument
    and implicitly passed in when the function is invoked from a user-level API.
    TODO(silvasean): Consider replacing tf_saved_model.bound_input arg attrs
    with "get_global @some_global_tensor" in the function body.
  }];

module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 975 : i32}, tf_saved_model.semantics}  {
  func.func @serving_default(%arg0: tensor<1x32x32x128xf32> {tf_saved_model.index_path = ["a"]}) -> (tensor<1x64x64x128xf32> {tf_saved_model.index_path = ["b"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "c:0", outputs = "d:0"}, tf_saved_model.exported_names = ["serving_default"]} {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"

namespace mlir {
namespace tf_saved_model {
namespace {

#define GEN_PASS_DEF_OPTIMIZEGLOBALTENSORSPASS
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_savedmodel_passes.h.inc"

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
#include "tensorflow/compiler/mlir/tensorflow/translate/import_model.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace mlir::quant {
namespace {

using ::mlir::tf_saved_model::AssetOp;
using ::mlir::tf_saved_model::kTfSavedModelIndexPathAttr;
using ::mlir::tf_saved_model::LookupBoundInputOfType;
using ::tensorflow::AssetFileDef;

//   2) The `tf_saved_model` dialect requires that the arguments with
//   `tf_saved_model.index_path` attributes should precede those with
//   `tf_saved_model.bound_input` attributes. The init function of type
//   `kTfSavedModelInitializerRestoreType` usually has an argument with
//   `tf_saved_model.index_path`, whereas the init function of type
//   `kTfSavedModelInitializerInitType` may have arguments with

  pm.addPass(mlir::tf_saved_model::CreateLowerVariableOpsToMlProgramPass());
  pm.addPass(mlir::tf_saved_model::CreateLowerGlobalsToMlProgramPass());
  pm.addPass(mlir::TF::CreateLocalizeVarHandlesPass());
  pm.addPass(mlir::tf_saved_model::CreateAddFunctionsForExportedNamesPass());
  pm.addPass(mlir::tf_saved_model::CreateStripSavedModuleMetadataPass());

# CHECK-SAME: tf.versions
# CHECK-SAME: bad_consumers
# CHECK-SAME: min_consumer
# CHECK-SAME: producer

# CHECK: "tf_saved_model.global_tensor"()
# CHECK: "tf_saved_model.session_initializer"() <{initializers = [@[[init:.*]]]}> : () -> ()

# CHECK:      func @[[init]]
# CHECK-SAME: tf_saved_model.initializer_type = "init_op"
# CHECK-NEXT: [[R6:%.*]] = "tf.Const"()
# CHECK-NEXT: [[R5:%.*]] = "tf.Const"() <{value = dense<[1, 2,

module attributes {tf_saved_model.semantics, tf_saved_model.under_construction} {

  func.func @serving_default(%arg0: tensor<!tf_type.resource<tensor<100x50xf32>>> {tf.resource_name = "dense/kernel"}, %arg1: tensor<!tf_type.resource<tensor<50xf32>>> {tf.resource_name = "dense/bias"}) -> (tensor<100x50xf32> {tf_saved_model.index_path = ["dense_2"]})

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"

namespace mlir {
namespace tf_saved_model {

namespace {

std::string GetVariableName(Operation* op) {
  if (auto handle = dyn_cast<TF::VarHandleOp>(op)) {

// RUN: tf-tfrt-opt -tf-to-tfrt %s | FileCheck %s --dump-input=fail

// CHECK-LABEL: func @device_test
func.func @device_test(
    %arg0: tensor<3x1xf32> {tf_saved_model.index_path = [0]},
    %arg1: tensor<1x3xf32> {tf_saved_model.index_path = [0]})
      -> (tensor<3x3xf32> {tf_saved_model.index_path = []}) {
  // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0"