llvm::dyn_cast_or_null<mlir::TF::TensorListReserveOp>(op)) {
    tflite::TensorType tflite_type =
        tflite::ConvertTypeToTensorType(reserve.getElementDtype());

    return CreateListReserveOptions(context, tflite_type);
  }
  if (auto empty = llvm::dyn_cast_or_null<mlir::TF::EmptyTensorListOp>(op)) {
    tflite::TensorType tflite_type =
        tflite::ConvertTypeToTensorType(empty.getElementDtype());

#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/compiler/mlir/lite/quantization/quantization_passes.h"
#include "tensorflow/compiler/mlir/lite/quantization/tensorflow/passes.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_tf_xla_call_module_to_stablehlo_pass.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h"

  let options = [
    Option<"default_min_", "default-min", "double", "-1.0",
               "Default minimum value for TFLite quantization">,
    Option<"default_max_", "default-max", "double", "1.0",
               "Default maximum value for TFLite quantization">,
    Option<"is_signed_", "is-signed", "bool", "false",
               "Is the corresponding integer signed">,
  ];
}

// There are four parts: a boolean negative flag, a form byte with three possible states
// (finite=0, infinite=1, NaN=2), a base-2 big-endian integer
// coefficient (also known as a significand) as a []byte, and an int32 exponent.
// These are composed into a final value as "decimal = (neg) (form=finite) coefficient * 10 ^ exponent".
// A zero length coefficient is a zero value.

  private enum TimeoutsToUse {
    ANY(Timeout.values()),
    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {

    ],
    deps = [
        ":common",
        ":runtime_metadata_fbs",
        "//tensorflow/compiler/mlir/lite:tensorflow_lite",
        "//tensorflow/compiler/mlir/lite/experimental/tac/hardwares:target_hardware",
        "//tensorflow/compiler/mlir/lite/quantization/ir:QuantOps",
        "//tensorflow/compiler/mlir/tensorflow",
        "@flatbuffers",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:ArithDialect",

    "get_compatible_with_portable",
)

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = [
        # For TFLite Converter integration.
        "//tensorflow/compiler/mlir/lite:__subpackages__",
        "//tensorflow/compiler/mlir/quantization:__subpackages__",
        "//tensorflow/compiler/mlir/tensorflow_to_stablehlo:__subpackages__",
    ],

#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/targets.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/utils.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/utils/attribute_utils.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

//             Flatbuffers. Has backward compatibility with version 3, 3a and
//             3b.

namespace tflite;

// This corresponds to the version.
file_identifier "TFL3";
// File extension of any written files.
file_extension "tflite";

// IMPORTANT: All new members of tables, enums and unions must be added at the
// end to ensure backwards compatibility.

    } catch (UnsupportedOperationException expected) {
    }
  }

  /**
   * Verifies that an Iterator is unmodifiable.
   *
   * <p>This test only works with iterators that iterate over a finite set.
   */
  public static void assertIteratorIsUnmodifiable(Iterator<?> iterator) {
    while (iterator.hasNext()) {
      iterator.next();
      try {
        iterator.remove();