#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/client/local_client.h"
#include "xla/pjrt/pjrt_client.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {

// An OpKernel that compiles an op to an XLA computation and runs it. Unlike

#include "mlir/IR/Operation.h"  // from @llvm-project
#include "mlir/IR/Types.h"  // from @llvm-project
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/lib/core/status.h"

namespace mlir {
class ShapedType;
}  // namespace mlir

namespace tensorflow {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
#include "xla/xla.pb.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

namespace mlir {
namespace TFTPU {

// Populates a TPUCompileMetadataProto from attributes of a

    // functions, as it may sometimes remove arguments and results.
    enable_grappler = false;
  }

  // If true, use ServingCoreSelector to pick TPU core. Otherwise, obtain core
  // location from assigned device name.
  // Currently we don't use core_selector for training use cases.
  bool tpu_use_core_selector = false;

#include <string>

#include "absl/base/attributes.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "tensorflow/core/lib/core/status.h"

namespace mlir {
namespace TF {

inline constexpr char kStandardPipelineBefore[] = "standard_pipeline_before";
inline constexpr char kStandardPipelineAfter[] = "standard_pipeline_after";

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/tstring.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value);

#include "tensorflow/c/experimental/ops/gen/cpp/renderers/renderer.h"
#include "tensorflow/c/experimental/ops/gen/cpp/renderers/renderer_context.h"
#include "tensorflow/c/experimental/ops/gen/cpp/views/op_view.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

class OpRenderer : public Renderer {
 public:
  explicit OpRenderer(RendererContext context, OpView op);
  void Render();

#ifndef TENSORFLOW_CC_SAVED_MODEL_FINGERPRINTING_H_
#define TENSORFLOW_CC_SAVED_MODEL_FINGERPRINTING_H_

#include <string>

#include "absl/status/statusor.h"
#include "absl/strings/string_view.h"
#include "tensorflow/core/protobuf/fingerprint.pb.h"

namespace tensorflow::saved_model::fingerprinting {

// Creates a FingerprintDef proto from a SavedModel (regular or chunked) and the
// checkpoint meta file (.index) in `export_dir`.

#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace mlir::quant {

// Converts arguments of the @main function that are bound to
// `tf_saved_model::AssetOp`s into regular tensor args. Returns `AsestFileDef`s

#include <string>
#include <vector>

#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/core/platform/statusor.h"

namespace tensorflow {

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

enum class IrExportStage {
  HLO,