#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "absl/status/status.h"
#include "tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.h"
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/xla_computation.h"
#include "xla/service/hlo.pb.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/lib/monitoring/counter.h"
#include "tsl/platform/statusor.h"

namespace {

// RUN: stablehlo-quant-opt %s -split-input-file -tf-xla-call-module-serialization -stablehlo-convert-xla-call-module-op-to-bfloat16 -tf-xla-call-module-deserialization | FileCheck %s

// ConvertXlaCallModuleOpToBfloat16Pass works on XlaCallModuleOps with
// serialized modules. Which makes verification difficult. Therefore we add
// (de)serialization passes so that the input and output are deserializated
// StableHLO functions.

// CHECK-LABEL: module
module {

#include "tensorflow/c/experimental/stream_executor/stream_executor.h"
#include "tensorflow/c/tf_status_helper.h"
#include "xla/stream_executor/executor_cache.h"
#include "xla/stream_executor/platform.h"
#include "xla/stream_executor/stream_common.h"
#include "xla/stream_executor/stream_executor.h"
#include "tsl/platform/statusor.h"

namespace stream_executor {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"
#include "xla/mlir_hlo/mhlo/IR/register.h"
#include "xla/mlir_hlo/mhlo/transforms/passes.h"
#include "tensorflow/core/ir/types/dialect.h"

int main(int argc, char** argv) {
  tensorflow::InitMlir y(&argc, &argv);

  mlir::registerAllPasses();

#include "tensorflow/compiler/jit/tests/device_compiler_test_helper.h"

#include <string>

#include "absl/strings/match.h"
#include "tensorflow/compiler/jit/xla_compilation_cache.pb.h"
#include "xla/service/hlo.pb.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/public/session.h"

namespace tensorflow {
namespace {

#include "tensorflow/compiler/mlir/tensorflow/utils/mlprogram_util.h"
#include "tensorflow/compiler/mlir/tools/kernel_gen/ir/tf_framework_ops.h"
#include "xla/mlir/framework/ir/xla_framework.h"
#include "xla/mlir_hlo/mhlo/IR/register.h"

namespace mlir {

void RegisterCommonToolingDialects(mlir::DialectRegistry& registry) {
  mlir::RegisterAllTensorFlowDialects(registry);

#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tf2xla/internal/test_matchers.h"
#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/shape.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_TF_STATUS_INTERNAL_H_
#define TENSORFLOW_C_TF_STATUS_INTERNAL_H_

#include "xla/tsl/c/tsl_status_internal.h"

typedef struct TSL_Status TF_Status;

enum OpSet {
  OP_SET_UNSPECIFIED = 0;  // go/do-include-enum-unspecified
  // Uses TF ops that mimic quantization behavior. Used when the corresponding
  // integer op is not yet present.
  TF = 1;
  // Uses TF XLA ops
  XLA = 2;
  // Uses TF Uniform Quantized ops
  UNIFORM_QUANTIZED = 3;
  // Uses the StableHLO Quantizer. StableHLO Quantizer will be available as
  // an option in the TF Quantizer in StableHLO Quantizer v1.

#include "tensorflow/compiler/mlir/tosa/tf_tfl_passes.h"
#include "tensorflow/compiler/mlir/tosa/tfl_passes.h"
#include "tensorflow/compiler/mlir/tosa/transforms/passes.h"
#include "xla/mlir/framework/transforms/passes.h"
#include "xla/mlir_hlo/mhlo/transforms/passes.h"

int main(int argc, char **argv) {
  tensorflow::InitMlir y(&argc, &argv);

  mlir::registerAllPasses();
  mlir::registerTransformsPasses();