namespace tensorflow {

// Replaces TF function calls marked with `_XlaCompiledKernel` with _XlaCompile
// and _XlaRun nodes (which compile and launch, respectively, the corresponding
// HLO module).
class BuildXlaOpsPass : public GraphOptimizationPass {
 public:
  // If enable_lazy_compilation is not nullopt then *enable_lazy_compilation
  // overrides --tf_xla_enable_lazy_compilation flag in deciding whether lazy

# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-graph-as-function -tf-control-output-arrays=assign_variable | tf-mlir-translate -mlir-tf-graph-to-hlo-text -tf-input-shapes=2:2 -tf-input-data-types=DT_FLOAT,DT_FLOAT -tf-xla-input-types=parameter,resource -tf-xla-emit-return-tuple | FileCheck %s

node {
  name: "arg0"
  op: "_Arg"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
  attr {

  let summary = "Verifies that all TF quant ops and types have been legalized.";

  let description = [{
    Ensures that all TF quant ops and types have been legalized to HLO
    and reports an error about which op failed to legalize. This pass
    does not transform any ops and is checking.}];

  let constructor = "mlir::quant::stablehlo::CreateVerifyQuantLegalizationPass()";

#include "tensorflow/core/platform/statusor.h"

namespace tensorflow {

class ProcessFunctionLibraryRuntime;
class Device;
class Tensor;
class TensorHandle;
class EagerContext;

enum class IrExportStage {
  HLO,
  HLO_NO_METADATA,
  HLO_SERIALIZED,
  OPTIMIZED_HLO,
  OPTIMIZED_HLO_SERIALIZED,
  OPTIMIZED_HLO_PROTO_SERIALIZED,
  OPTIMIZED_HLO_DOT
};

struct ArgShapeAndDType {
  TensorShape shape;

// RUN: tf-mlir-translate -mlir-tf-to-hlo-text %s -tf-input-shapes=10,19:19,10 -tf-xla-emit-use-tuple-args -tf-xla-emit-return-tuple | FileCheck %s

module attributes {tf.versions = {producer = 179 : i32}} {
  func.func @main(%arg0: tensor<10x19xf32>, %arg1: tensor<19x10xf32> {mhlo.is_same_data_across_replicas = true}) -> tensor<10x19xf32> {
    %0 = "tf.Shape"(%arg0) : (tensor<10x19xf32>) -> tensor<2xi64>

#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
absl::StatusOr<XlaCompilationResult> LegalizeTfToHlo(
    const tpu::MlirToHloArgs& computation,
    const tpu::TPUCompileMetadataProto& metadata, bool use_tuple_args,

// operations that can be represented by means of other TensorFlow operations.
// This pattern collection preserves those TensorFlow operations that will later
// be lowered to equivalent operations in CHLO or MHLO. This allows for
// HLO-specific lowerings.
void PopulateTFLoweringBeforeHLOPatterns(MLIRContext *context,
                                         RewritePatternSet *patterns);

// Populates TensorFlow lowering patterns to lower some of the TensorFlow

#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/client/xla_builder.h"
#include "xla/client/xla_computation.h"
#include "xla/hlo/ir/hlo_instruction.h"
#include "xla/hlo/ir/hlo_opcode.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"
#include "xla/service/hlo.pb.h"
#include "xla/translate/hlo_to_mhlo/hlo_function_importer.h"
#include "xla/translate/hlo_to_mhlo/hlo_to_mlir_hlo.h"

  // compilation. Returns an error if the results between the two do not match.
  Status ExecuteWithBatch(const GraphDef& graph, int batch);

  // Adds the suffix "_altered" to the HLO module names of all of the persistent
  // XLA compilation cache entries found at the specified directory. If none are
  // found, returns NOT_FOUND error.
  Status AlterPersistentCacheEntryHloModuleNames(

}

void RegisterConvertMlirToXlaHloPipelineWithDefaults() {
  static mlir::PassPipelineRegistration<> pipeline(
      "tf-to-hlo-pipeline",
      "Convert TF dialect to HLO dialect (used for compilation in bridge).",
      [](mlir::OpPassManager& pm) {
        tensorflow::CreateConvertMlirToXlaHloPipeline(