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"

    // Pass an invalid session argument, which is a nullptr.
    if (failed(tf_saved_model::LiftVariables(module, /*session=*/nullptr)))
      signalPassFailure();
  }
};

}  // namespace
}  // namespace tf_saved_model

namespace tf_test {

std::unique_ptr<OperationPass<ModuleOp>> CreateLiftVariablesTestPass() {
  return std::make_unique<tf_saved_model::LiftVariablesTestPass>();
}

std::unique_ptr<OperationPass<ModuleOp>>

#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;

#include "tensorflow/core/public/session.h"

namespace mlir {
namespace tf_saved_model {

// Creates a pass that optimizes tf_saved_model.global_tensor ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateOptimizeGlobalTensorsPass();

// Creates a pass that freezes tf_saved_model.global_tensor ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateFreezeGlobalTensorsPass(

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"}) -> (tensor<100x50xf32> {tf_saved_model.index_path = ["dense_2"]})
  attributes {tf.entry_function = {control_outputs = "", inputs = "", outputs = "dense_2/Add:0"}, tf_saved_model.exported_names = ["serving_default"]} {

//   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"]})