bool prefer_tf2xla = false);

// Legalizes TF/XLA communication ops (TF dialect) to HLO dialect communication
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeTFCommunicationPass();

// Legalizes TF/XLA collective ops (TF dialect) to HLO dialect collective
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeTFCollectivePass();

// Verifies that the TF/XLA ops have all been lowered to MHLO.

#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/compile_only_client.h"
#include "tensorflow/core/tpu/kernels/tpu_compile_op_support.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

// Legalize the given MLIR module to XLA HLO using a combination of the MLIR
// Bridge and XlaBuilder

    std::vector<tpu::ShardingAndIndex>* arg_core_mapping,
    std::vector<std::vector<xla::Shape>>* per_core_arg_shapes,
    std::vector<std::unique_ptr<mlir::Pass>>& custom_legalization_passes,
    xla::CompileOnlyClient* client, XlaCompilationResult* compilation_result) {
  LOG_FIRST_N(INFO, 1) << "Compiling MLIR computation to XLA HLO using the "
                          "Combined MLIR Tf2Xla Bridge.";

    const std::vector<TensorShape>& arg_shapes,
    std::vector<tpu::ShardingAndIndex>* arg_core_mapping,
    std::vector<std::vector<xla::Shape>>* per_core_arg_shapes);

// Compiles a serialized MLIR module into XLA HLO, generates all accompanying
// metadata and stores them in CompilationResult.
absl::StatusOr<XlaCompilationResult> LegalizeWithMlirBridge(
    const tpu::MlirToHloArgs& computation,

#include "absl/container/flat_hash_map.h"
#include "absl/numeric/bits.h"
#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/status_macros.h"
#include "xla/statusor.h"
#include "tensorflow/core/framework/types.h"

namespace tensorflow {
namespace jit {
class DeviceInfoCache;
class DeviceSet;

#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 {

#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/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"