#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/client/local_client.h"
#include "tensorflow/core/framework/metrics.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/lib/core/threadpool.h"
#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/platform/thread_annotations.h"

namespace tensorflow {

#include <memory>
#include <unordered_set>

#include "absl/status/statusor.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saved_model.pb.h"

namespace tensorflow {
Status ReadSavedModel(absl::string_view export_dir,

#include <vector>

#include "tensorflow/core/framework/api_def.pb.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/attr_value_util.h"
#include "tensorflow/core/framework/op_def_util.h"
#include "tensorflow/core/framework/op_gen_lib.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

#ifndef TENSORFLOW_COMPILER_MLIR_LITE_PYTHON_JAX_TO_TFL_FLATBUFFER_H_
#define TENSORFLOW_COMPILER_MLIR_LITE_PYTHON_JAX_TO_TFL_FLATBUFFER_H_

#include <string>

#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/lite/toco/model_flags.pb.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tensorflow {

#include "tensorflow/compiler/mlir/tensorflow/utils/export_utils.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op_def_builder.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

#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/c/tensor_interface.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/framework/numeric_types.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/platform.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/tstring.h"

#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;