}

void SetAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
             TF_Buffer* attr_value_proto, TF_Status* status) {
  TF_SetAttr(graph, op, attr_name, attr_value_proto, status);
}

void ClearAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
               TF_Status* status) {
  TF_ClearAttr(graph, op, attr_name, status);
}

void SetFullType(TF_Graph* graph, TF_Operation* op,

  return true;
}

bool GetI32VectorFromDenseI64CompositeAttr(
    const DictionaryAttr& composite_attrs, const std::string& attr_name,
    std::vector<int32_t>* out_vec) {
  DenseIntElementsAttr attr;
  if (!EnsureAttribute<DenseIntElementsAttr>(composite_attrs, attr_name,
                                             &attr)) {
    return false;
  }

  return DenseI64AttrToI32Vector(attr, out_vec);
}

TF_CAPI_EXPORT extern TF_Buffer* TF_OpKernelConstruction_GetAttrFunction(
    TF_OpKernelConstruction* ctx, const char* attr_name, TF_Status* status);

// Return true if the kernel construction has the attr_name
TF_CAPI_EXPORT extern bool TF_OpKernelConstruction_HasAttr(
    TF_OpKernelConstruction* ctx, const char* attr_name, TF_Status* status);

// Returns the unique operation name for this OpKernel.

  case DataTypeToEnum<type>::value: {                            \
    kernel_builder->cc_builder->TypeConstraint<type>(attr_name); \
    break;                                                       \
  }

void AddTypeConstraint(TF_KernelBuilder* kernel_builder, const char* attr_name,
                       const DataType dtype, TF_Status* status) {
  // This needs to be under tensorflow:: namespace so that

    }
    desc->node_builder.Attr(attr_name, v);
  }
}

void TF_SetAttrInt(TF_OperationDescription* desc, const char* attr_name,
                   int64_t value) {
  desc->node_builder.Attr(attr_name, static_cast<int64_t>(value));
}

void TF_SetAttrIntList(TF_OperationDescription* desc, const char* attr_name,
                       const int64_t* values, int num_values) {

TF_CAPI_EXPORT extern void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name,
                                            int64_t value);
TF_CAPI_EXPORT extern void TFE_OpSetAttrFloat(TFE_Op* op, const char* attr_name,
                                              float value);
TF_CAPI_EXPORT extern void TFE_OpSetAttrBool(TFE_Op* op, const char* attr_name,
                                             unsigned char value);

                                             const std::string& attr_name,
                                             int N) {
  ArrayAttr array_attr =
      mlir::dyn_cast_or_null<ArrayAttr>(attrs.get(attr_name));
  if (array_attr == nullptr || array_attr.size() != N) {
    return func->emitWarning()
           << "'" << attr_name << "' attribute for " << kMaxUnpooling
           << " must be set and has size of " << N;

  int64_t total_size;
} TF_AttrMetadata;

// Returns metadata about the value of the attribute `attr_name` of `oper`.
TF_CAPI_EXPORT extern TF_AttrMetadata TF_OperationGetAttrMetadata(
    TF_Operation* oper, const char* attr_name, TF_Status* status);

// Fills in `value` with the value of the attribute `attr_name`.  `value` must
// point to an array of length at least `max_length` (ideally set to

  if (!s.ok() && s.code() != error::NOT_FOUND) {
    return s;
  }

  n->ClearAttr(attr_name);
  attr_value.push_back(value);
  n->AddAttr(attr_name, attr_value);
  return absl::OkStatus();
}

// Replaces attribute value.
template <typename T>
void ReplaceAttr(Node* n, const string& attr_name, const T& value) {
  n->ClearAttr(attr_name);
  n->AddAttr(attr_name, value);
}

  for (auto& attr : func->getAttrs()) {
    StringRef attr_name = attr.getName().getValue();
    if (attr_name.starts_with("tf_saved_model.")) {
      func->removeAttr(attr_name);
    }
  }

  auto iface = cast<FunctionOpInterface>(func.getOperation());
  for (int i = 0; i < func.getNumArguments(); ++i) {
    for (auto& attr : iface.getArgAttrs(i)) {
      const StringAttr& attr_name = attr.getName();