//   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

  func.func @serving_default(%arg0: tensor<1x4xf32> {tf_saved_model.index_path = ["x"]}) -> (tensor<1x3xf32> {tf_saved_model.index_path = ["output"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_x:0", outputs = "PartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

      return %2 : tensor<1x3xf32>
    }
  }
)mlir";

constexpr absl::string_view kModuleXlaCallModule = R"mlir(
  module {
    func.func @main(%arg0: tensor<?x2xf32> {tf_saved_model.index_path = ["input_tensor"]}) -> (tensor<?x2xf32>) {
      %0 = stablehlo.constant dense<[-0.211145893, -0.708605706]> : tensor<2xf32>

  EXPECT_TRUE(MessageDifferencer::Equals(method, Method::default_instance()));
}
constexpr absl::string_view kModuleDotWeightOnlyPtq = R"mlir(
  module {
    func.func @main(%arg0: tensor<?x2xf32> {tf_saved_model.index_path = ["input_tensor"]}) -> (tensor<?x2xf32>) {
      %0 = stablehlo.constant dense<[-0.211145893, -0.708605706]> : tensor<2xf32>

// RUN: stablehlo-quant-opt %s -split-input-file -stablehlo-quantize -verify-each=false | FileCheck %s

module attributes {tf_saved_model.semantics} {
  // CHECK-LABEL: same_scale_after_composite
  // CHECK-SAME: %[[ARG0:.*]]: tensor<1x2xf32>
  // CHECK-SAME: %[[ARG1:.*]]: tensor<2x3xf32>
  func.func private @same_scale_after_composite(%arg0: tensor<1x2xf32>, %arg1: tensor<2x3xf32>) -> tensor<3x1xf32> {

    tbl_outs = [
        (
            ["-gen-op-decls"],
            "ir/tf_saved_model.h.inc",
        ),
        (
            ["-gen-op-defs"],
            "ir/tf_saved_model.cc.inc",
        ),
        (
            ["-gen-dialect-doc"],
            "g3doc/tf_saved_model.md",
        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",

    // constant ops.
    pass_manager->addPass(mlir::tf_saved_model::CreateFreezeGlobalTensorsPass(
        /*allow_mutable_tensors=*/pass_config.enable_tflite_variables));
  }

  if (!saved_model_dir.empty()) {
    // This pass 'freezes' tf saved model asset ops and inlines as string values
    // in a format of the tf constant op.
    pass_manager->addPass(
        mlir::tf_saved_model::CreateFreezeAssetsPass(saved_model_dir.str()));
  }

// to the save function and returns the file_prefix argument (typed
// `tensor<!tf_type.string>`). The file_prefix argument, which can be identified
// if the "tf_saved_model.index_path" attribute has "__tf_file_prefix", will be
// reused if it already exist in @main. Otherwise a new file prefix argument
// will be created. @tf_quant__save function will be erased.
//

    StaticRangePtqPreset static_range_ptq_preset = 1;
    WeightOnlyPtqPreset weight_only_ptq_preset = 7;
  }

  // TF SavedModel specific information for the input model.
  TfSavedModelConfig tf_saved_model = 2;

  // Configures the graph transformation pipeline for quantization.
  PipelineConfig pipeline_config = 3;

  QuantizationSpecs specs = 4;

  // Configures the quantization debugger.