#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSLATE_EXPORT_GRAPHDEF_H_

#include "absl/base/attributes.h"
#include "absl/container/flat_hash_set.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 "mlir/IR/MLIRContext.h"  // from @llvm-project

#ifndef TENSORFLOW_COMPILER_MLIR_TF2XLA_API_V2_TF_EXECUTOR_TO_GRAPH_H_
#define TENSORFLOW_COMPILER_MLIR_TF2XLA_API_V2_TF_EXECUTOR_TO_GRAPH_H_

#include "absl/container/flat_hash_set.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 "mlir/IR/MLIRContext.h"  // from @llvm-project

limitations under the License.
==============================================================================*/
#include <cmath>
#include <cstdlib>
#include <memory>
#include <string>
#include <utility>

#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Support/Casting.h"
#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

                             std::vector<int32_t>* out_vec);

// Gets boolean from composite attrs if it exists.
std::optional<bool> GetBoolFromCompositeAttr(
    const DictionaryAttr& composite_attrs, llvm::StringRef attr_name);

// Given a DictionaryAttr, checks if it has a DenseIntElementsAttr attribute
// with the name attr_name. If so, extracts its values and stores as a vector
// of int32_t elements.

  absl::Status status = absl::OkStatus();
  module_op.walk([&py_function_library, &calibration_options, &status,
                  &statistics_map](mlir::TF::CustomAggregatorOp aggregator_op) {
    mlir::StringRef id = aggregator_op.getId();
    auto iter = statistics_map.find(id);
    if (iter == statistics_map.end()) {
      status = absl::InternalError(
          absl::StrFormat("Calibrated data does not exist. Cannot find "

  if (failed(GetOp(region, &send_op))) return failure();

  // No TPU embedding ops.
  if (!recv_op && !send_op) return success();

  Location loc = recv_op ? recv_op.getLoc() : send_op.getLoc();
  StringRef config = recv_op ? recv_op.getConfig() : send_op.getConfig();

  // Create XlaRecvTPUEmbeddingDeduplicationData op.
  OpBuilder builder(region);
  auto output_ty =

absl::StatusOr<tensorflow::XlaCompilationResult> LegalizeMlirToHlo(
    const std::variant<tpu::MlirToHloArgs, tpu::FunctionToHloArgs>& computation,
    const tpu::TPUCompileMetadataProto& metadata, bool use_tuple_args,
    llvm::StringRef device_type,
    std::vector<std::unique_ptr<mlir::Pass>>& custom_legalization_passes,
    XlaShapeLayoutHelpers::ShapeDeterminationFns shape_determination_fns,
    const std::vector<tensorflow::TensorShape>& arg_shapes,

                                      llvm::cl::init("-"));

namespace mlir {
namespace {
std::optional<std::unique_ptr<tflite::ModelT>> InjectStatsToFullyConnected(
    llvm::StringRef buffer) {
  auto model_ptr = tflite::FlatBufferModel::VerifyAndBuildFromBuffer(
      buffer.data(), buffer.size());
  if (nullptr == model_ptr) {
    return std::nullopt;
  }

limitations under the License.
==============================================================================*/

#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/StringSet.h"
#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

    return std::nullopt;

  if (!HasValidHardwareTarget(op)) return std::nullopt;

  auto device = op->getAttrOfType<mlir::StringAttr>(mlir::TFL::tac::kDevice);
  if (device == nullptr) return std::nullopt;

  llvm::StringRef device_name_str = device.getValue();
  return device_name_str.str();
}

std::optional<std::vector<float>> GetPerDeviceCosts(
    const std::map<std::string, uint8_t>& hardware_map, mlir::Operation* op) {