}
}

void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name, int64_t value) {
  auto s = tensorflow::unwrap(op)->SetAttrInt(attr_name, value);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrFloat(TFE_Op* op, const char* attr_name, float value) {
  auto s = tensorflow::unwrap(op)->SetAttrFloat(attr_name, value);
  if (!s.ok()) {

  absl::Status SetAttrFloat(const char* attr_name, float value) override {
    op_->node_builder.Attr(attr_name, value);
    return absl::OkStatus();
  }
  absl::Status SetAttrBool(const char* attr_name, bool value) override {
    op_->node_builder.Attr(attr_name, value);
    return absl::OkStatus();
  }
  absl::Status SetAttrType(const char* const attr_name,
                           DataType value) override {
    if (!op_) {

absl::Status SetAttrString(AbstractOperation*, const char* attr_name,
                           const char* data, size_t length, ForwardOperation*);
absl::Status SetAttrInt(AbstractOperation*, const char* attr_name,
                        int64_t value, ForwardOperation*);
absl::Status SetAttrFloat(AbstractOperation*, const char* attr_name,
                          float value, ForwardOperation*);

  virtual bool GetFloat(absl::string_view attr_name, float* result) const = 0;
  virtual bool GetBool(absl::string_view attr_name, bool* result) const = 0;
  virtual bool GetType(absl::string_view attr_name, DataType* result) const = 0;
  virtual absl::Status GetTypeList(
      absl::string_view attr_name,
      absl::InlinedVector<DataType, 4>* type_list) const = 0;

 private:

    }
    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) {

  }

  (*(fdef_or.value()->mutable_attr()))[string(attr_name)] = attr_value;

  status->status = absl::OkStatus();
}

void TF_FunctionGetAttrValueProto(TF_Function* func, const char* attr_name,
                                  TF_Buffer* output_attr_value,
                                  TF_Status* status) {
  const auto& it = func->record->fdef().attr().find(attr_name);
  if (it == func->record->fdef().attr().end()) {

void TF_AttrBuilderSetType(TF_AttrBuilder* builder, const char* attr_name,
                           TF_DataType value) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, static_cast<tensorflow::DataType>(value));
}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {

// `op_name` must outlive `op`.
void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,
                            TF_Status* s);
// `attr_name` must outlive `op`.
void TF_AbstractOpSetAttrType(TF_AbstractOp* op, const char* const attr_name,
                              TF_DataType value, TF_Status* s);

void TF_DeleteAbstractTensor(TF_AbstractTensor*);

            assert isinstance(link_open_tag, str)

            attributes: list[HTMLLinkAttribute] = []
            for attr_name, attr_quote, attr_value in re.findall(
                HTML_ATTR_RE, link_open_tag
            ):
                assert isinstance(attr_name, str)
                assert isinstance(attr_quote, str)
                assert isinstance(attr_value, str)
                attributes.append(

  }
  tsl::Set_TF_Status_from_Status(s, tracing_op->SetOpName(op_name));
}

void TF_AbstractOpSetAttrType(TF_AbstractOp* op, const char* const attr_name,
                              TF_DataType value, TF_Status* s) {
  Status status =
      unwrap(op)->SetAttrType(attr_name, static_cast<DataType>(value));
  TF_SetStatus(s, static_cast<TF_Code>(status.code()),
               absl::StatusMessageAsCStr(status));
}