#include "absl/status/status.h"
#include "absl/types/variant.h"
#include "xla/client/compile_only_client.h"
#include "xla/pjrt/compile_options.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/tpu/kernels/tpu_compile.pb.h"
#include "tensorflow/core/tpu/kernels/tpu_compile_op_support.h"

namespace tensorflow {
namespace tf2xla {
namespace v1 {

#include "mlir/IR/Builders.h"  // from @llvm-project
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"

namespace mlir {
namespace TFL {

bool IsQuantized(const tflite::TensorT& tensor);

absl::StatusOr<mlir::quant::QuantizedType> GetQuantizedType(

#define TENSORFLOW_C_EXPERIMENTAL_NEXT_PLUGGABLE_DEVICE_TENSOR_PJRT_BUFFER_UTIL_H_

#include "xla/pjrt/c/pjrt_c_api.h"
#include "xla/pjrt/pjrt_c_api_client.h"
#include "tensorflow/core/framework/tensor.h"

namespace tensorflow {

absl::StatusOr<PJRT_Buffer*> GetPjRtCBufferFromTensor(const Tensor* tensor);

absl::Status SetPjRtCBufferToTensor(PJRT_Buffer* c_buffer,

#include "absl/strings/string_view.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/Pass/PassManager.h"  // from @llvm-project
#include "tensorflow/core/public/session.h"

namespace tensorflow {
namespace quantization {

// Default MLIR dump file prefix for TensorFlow quantization passes.
inline constexpr absl::string_view kDefaultTfQuantMlirDumpFilePrefix =

#ifndef TENSORFLOW_COMPILER_AOT_EMBEDDED_PROTOCOL_BUFFERS_H_
#define TENSORFLOW_COMPILER_AOT_EMBEDDED_PROTOCOL_BUFFERS_H_

#include "absl/types/span.h"
#include "xla/statusor.h"
#include "tensorflow/core/platform/protobuf.h"

namespace tensorflow {
namespace tfcompile {
using absl::StatusOr;

// Represents a set of protocol buffers embedded into an object file and
// describes how to access them at runtime.

namespace tflite {

// Convert a model represented in `input_contents`. `model_flags_proto`
// describes model parameters. `flags_proto` describes conversion
// parameters (see relevant .protos for more information). Returns a string
// representing the contents of the converted model. When extended_return
// flag is set to true returns a dictionary that contains string representation

#include "tensorflow/compiler/mlir/tensorflow/translate/mlir_roundtrip_flags.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/graph/graph.h"

namespace tensorflow {

inline constexpr absl::string_view kImportModelDefaultGraphFuncName = "main";

#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_UTILS_CONVERT_ATTR_H_

#include "mlir/IR/Attributes.h"  // from @llvm-project
#include "mlir/IR/Builders.h"  // from @llvm-project
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {

using tsl::StatusOr;

// Converts non func AttrValue proto into an MLIR attribute. Func attribute is

#include "llvm/ADT/StringRef.h"
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/compile_only_client.h"
#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

#include <string>
#include <vector>

#include "llvm/ADT/StringRef.h"
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "tensorflow/core/tpu/kernels/tpu_compile_op_support.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

// Compiles a serialized MLIR module and returns a serialized MLIR module of the