#ifndef TENSORFLOW_COMPILER_MLIR_TF2XLA_INTERNAL_COMPILATION_TIMER_H_
#define TENSORFLOW_COMPILER_MLIR_TF2XLA_INTERNAL_COMPILATION_TIMER_H_

#include <chrono>  // NOLINT(build/c++11)

#include "tensorflow/core/platform/profile_utils/cpu_utils.h"

// Time the execution of kernels (in CPU cycles). Meant to be used as RAII.
struct CompilationTimer {
  uint64_t start_cycles =

#define TENSORFLOW_COMPILER_MLIR_TFRT_BACKEND_COMPILER_H_

#include "absl/status/status.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/DialectRegistry.h"  // from @llvm-project
#include "tensorflow/core/tfrt/runtime/runtime.h"

namespace tensorflow {

class BackendCompiler {
 public:
  virtual ~BackendCompiler();

  virtual void GetDependentDialects(mlir::DialectRegistry& registry) const {}

#ifndef TENSORFLOW_COMPILER_JIT_TF_TO_HLO_COMPILER_H_
#define TENSORFLOW_COMPILER_JIT_TF_TO_HLO_COMPILER_H_

#include <memory>
#include <vector>

#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {

class TfToHloCompiler {
 public:
  TfToHloCompiler() = default;
  virtual ~TfToHloCompiler() = default;

#ifndef TENSORFLOW_COMPILER_MLIR_TFR_INTEGRATION_NODE_EXPANSION_PASS_H_
#define TENSORFLOW_COMPILER_MLIR_TFR_INTEGRATION_NODE_EXPANSION_PASS_H_

#include "tensorflow/compiler/mlir/tfr/integration/tfr_decompose_ctx.h"
#include "tensorflow/core/common_runtime/eager/eager_op_rewrite_registry.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tfr {

// An optimization pass that decompose the composite ops in a module according

#include "mlir/IR/Types.h"  // from @llvm-project
#include "mlir/IR/Value.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "xla/statusor.h"
#include "tensorflow/core/framework/types.pb.h"

namespace mlir {
class Builder;
}  // namespace mlir

namespace tflite {
// Convert the MLIR type to the corresponding TFLite tensor.

#define TENSORFLOW_CC_SAVED_MODEL_IMAGE_FORMAT_INTERNAL_API_H_

#include <string>
#include <tuple>

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/cord.h"
#include "tensorflow/core/protobuf/saved_model.pb.h"

#define IS_OSS false

namespace tensorflow {
namespace image_format {

// Reads the SavedModel proto from {file_prefix}{.pb|.cpb}.

==============================================================================*/

#ifndef TENSORFLOW_COMPILER_JIT_DEADNESS_ANALYSIS_H_
#define TENSORFLOW_COMPILER_JIT_DEADNESS_ANALYSIS_H_

#include "tensorflow/core/graph/graph.h"

namespace tensorflow {

// This analyzes a TensorFlow graph to identify nodes which may have partially
// dead inputs (i.e. these nodes may have some dead inputs and some alive
// inputs).
//

#include "tensorflow/compiler/jit/pjrt_base_device.h"
#include "tensorflow/compiler/jit/xla_device.h"
#include "xla/stream_executor/integrations/tf_allocator_adapter.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {

// Holds some information about the platform on which an
// XlaLaunch/_XlaCompile/_XlaRun op must run on. Provides a common layer of

#include "absl/container/flat_hash_map.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/statusor.h"
#include "tensorflow/core/protobuf/saved_model.pb.h"
#include "tensorflow/core/protobuf/saved_object_graph.pb.h"
#include "tensorflow/core/protobuf/trackable_object_graph.pb.h"

#include <atomic>
#include <memory>
#include <unordered_set>
#include <vector>

#include "tensorflow/core/framework/cost_graph.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/protobuf/config.pb.h"
#include "tensorflow/core/protobuf/error_codes.pb.h"

namespace tensorflow {