#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/client/global_data.h"
#include "xla/client/local_client.h"
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/device_base.h"
#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {

// The allocator used for Tensors assigned to the XLA device. The allocator

#ifndef TENSORFLOW_C_TF_BUFFER_INTERNAL_H_
#define TENSORFLOW_C_TF_BUFFER_INTERNAL_H_

#include <memory>

#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/core/platform/protobuf.h"  // IWYU pragma: keep
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

Status MessageToBuffer(const tensorflow::protobuf::MessageLite& in,
                       TF_Buffer* out);

#define TENSORFLOW_COMPILER_MLIR_LITE_PYTHON_GRAPHDEF_TO_TFL_FLATBUFFER_H_

#include <string>

#include "absl/status/status.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/lite/toco/model_flags.pb.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tensorflow {

#include "absl/base/attributes.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/Pass/PassManager.h"  // from @llvm-project
#include "tensorflow/core/lib/core/status.h"
#include "tsl/framework/device_type.h"

namespace tensorflow {
namespace tfrt_compiler {

// Given a MLIR module with tf_device.cluster ops, insert specific Runtime ops

#include "absl/strings/str_cat.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/lib/gtl/array_slice.h"

namespace tensorflow {

class Graph;
class GraphDef;
class NodeBuilder;
struct CompositeOpScopes;

/// @addtogroup core
/// @{

/// A `Scope` object represents a set of related TensorFlow ops that have the

#include "third_party/absl/strings/str_cat.h"
#Description:
# TensorFlow cc tools.

load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_test",
)
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:public"],
    licenses = ["notice"],
)

cc_library(
    name = "freeze_saved_model",

#include "tensorflow/compiler/tf2xla/xla_expression.h"
#include "xla/client/xla_builder.h"
#include "xla/client/xla_computation.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace mlir {
namespace mhlo {

class Tf2XlaRewriterTestPeer;

class Tf2XlaRewriter {
 public:
  static mlir::LogicalResult RewriteOp(mlir::Operation* op,

#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;