let constructor = "mlir::odml::CreateUniformQuantizedStableHloToTflPass()";
  let description = [{
    Converts StableHLO ops that accept or return uniform quantized types to
    equivalent ops in the TFLite dialect.
  }];
  let dependentDialects = [
    "stablehlo::StablehloDialect",
    "quant::QuantizationDialect",
    "mlir::TFL::TFLDialect",
  ];
}

// 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.

//RUN: tf_tfl_translate --enable-stablehlo-conversion --input-mlir %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s


module {
func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> {
  %1 = arith.constant dense<1> : tensor<1xi32>
  %2 = arith.constant dense<2.0> : tensor<1x1x2xf32>
  %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""}
    : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32>

#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"

namespace mlir {
namespace lite {

// Sparsify the `input_model` and write the result to a flatbuffer `builder`.
absl::Status SparsifyModel(const tflite::ModelT& input_model,
                           flatbuffers::FlatBufferBuilder* builder);
}  // namespace lite
}  // namespace mlir

  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) {

#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/custom_call.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/dot_general.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/reduce.h"

		for i, line := range b.Text {
			// Ignore final empty line (why is it even there?).
			if i == len(b.Text)-1 && len(line) == 0 {
				break
			}
			// var iline string
			// is := initialSpaces(line)
			// if is < 4 {
			// 	iline = "    " + line
			// } else {
			// 	iline = "\t" + line[4:]
			// }
			// Indent by 4 spaces.
			pre := s.prefix
			if i == 0 {
				pre = prefix1
			}

    ],
    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__",
    ],

// RUN: json_to_flatbuffer %p/test_schema.fbs %s | flatbuffer_translate --tflite-flatbuffer-to-mlir -o - | FileCheck %s

// This test is to test that if the flatbuffer omits the last optional input `bias` of tfl.conv_2d op, the flatbuffer_importer will automatically adds `none` value to tfl.conv_2d.

// CHECK: %[[CST:.*]] = "tfl.no_value"() <{value}> : () -> none