? 1
          : 0;

  Type element_ty = lhs_type.getElementType();
  Attribute identity_attr;
  if (auto ty = mlir::dyn_cast<FloatType>(element_ty)) {
    identity_attr = FloatAttr::get(ty, static_cast<double>(identity));
  } else if (auto ty = mlir::dyn_cast<IntegerType>(element_ty)) {
    identity_attr = IntegerAttr::get(ty, static_cast<int64_t>(identity));
  } else {
    return {};
  }

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.h"

namespace mlir {
namespace quant {

template <class TFFakeQuantOp>
struct FetchMinMaxAttrs {
  using AttrType = FloatAttr;
  bool operator()(TFFakeQuantOp tf_op, AttrType &min_value,
                  AttrType &max_value) const {
    min_value = tf_op.getMinAttr();
    max_value = tf_op.getMaxAttr();

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.h"

namespace mlir {
namespace TFL {

template <class TFFakeQuantOp>
struct FetchMinMaxAttrs {
  using AttrType = FloatAttr;
  bool operator()(TFFakeQuantOp tf_op, AttrType &min_value,
                  AttrType &max_value) const {
    min_value = tf_op.getMinAttr();
    max_value = tf_op.getMaxAttr();

  for (const auto& kv : hardware_map) {
    auto cost_attr = device_costs_attr.getNamed(kv.first);
    if (!cost_attr.has_value()) return std::nullopt;
    float cost = mlir::dyn_cast_or_null<mlir::FloatAttr>(cost_attr->getValue())
                     .getValueAsDouble();
    device_costs[kv.second] = cost;
  }
  return device_costs;
}

flatbuffers::Offset<SubgraphMetadata> CreateSubgraphMetadata(