#include "xla/mlir_hlo/mhlo/IR/register.h"
#include "xla/shape.h"
#include "xla/translate/mhlo_to_hlo/type_to_shape.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tsl/platform/errors.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {
namespace {

constexpr char kEntryFuncName[] = "main";

absl::Status SetupArguments(mlir::ModuleOp module,

#include "tensorflow/compiler/mlir/lite/transforms/passes.h"
#include "tensorflow/compiler/mlir/lite/utils/convert_type.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/error_util.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/lite/tools/optimize/reduced_precision_support.h"

namespace mlir {
namespace lite {

absl::Status SparsifyModel(const tflite::ModelT& input_model,

#include "tensorflow/core/lib/monitoring/test_utils.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/protobuf/config.pb.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tensorflow/core/tpu/kernels/tpu_compile_op_support.h"
#include "tensorflow/core/util/debug_data_dumper.h"
#include "tsl/lib/core/status_test_util.h"

#include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_config.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/error_util.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/lite/c/c_api_types.h"

namespace mlir {
namespace lite {

std::string TfLiteToMlir(const absl::string_view tflite_op_name) {

#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/graph_to_functiondef.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/framework/versions.pb.h"
#include "tensorflow/core/graph/algorithm.h"

#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tsl/platform/protobuf.h"

namespace mlir {
using tsl::Status;
using tsl::StatusOr;

static constexpr char kMlirToGraphCompilationCheckName[] =
    "mlir-to-graph-compilation-check";

#include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_config.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/error_util.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/lite/c/c_api_types.h"

namespace mlir {
namespace lite {

namespace {

using llvm::StringRef;

// Convert op represented in TFLite builtin_code to its corresponding MLIR

#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/common_runtime/optimization_registry.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/public/session_options.h"
#include "tsl/platform/statusor.h"

#include "xla/status_macros.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/versions.pb.h"
#include "tensorflow/core/lib/monitoring/counter.h"
#include "tensorflow/core/lib/monitoring/sampler.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/profile_utils/cpu_utils.h"

#include "tensorflow/compiler/mlir/utils/string_container_utils.h"
#include "xla/array4d.h"
#include "xla/service/computation_placer.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/protobuf/tpu/topology.pb.h"
#include "tensorflow/core/util/device_name_utils.h"
#include "tsl/platform/errors.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {