final int length = attrs.getLength();
        for (int i = 0; i < length; ++i) {
            final Attr attr = (Attr) attrs.item(i);
            buf.append(' ');
            appendAttr(attr, buf);
        }
    }

    /**
     * {@link Attr}の文字列表現を追加します。
     *
     * @param attr
     *            属性。{@literal null}であってはいけません
     * @param buf
     *            文字列バッファ。{@literal null}であってはいけません

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

ldap.attr.postalAddress=postalAddress
ldap.attr.city=l
ldap.attr.teletexTerminalIdentifier=teletexTerminalIdentifier
ldap.attr.x121Address=x121Address
ldap.attr.businessCategory=businessCategory
ldap.attr.registeredAddress=registeredAddress
ldap.attr.displayName=displayName
ldap.attr.preferredLanguage=preferredLanguage
ldap.attr.departmentNumber=departmentNumber
ldap.attr.uidNumber=uidNumber
ldap.attr.gidNumber=gidNumber

  }
}

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);

    return;
  }

  (*(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()) {

    from pydantic.fields import (  # type: ignore[no-redef,attr-defined]
        Required as Required,  # noqa: F401
    )
    from pydantic.fields import (  # type: ignore[no-redef,attr-defined]
        Undefined as Undefined,
    )
    from pydantic.fields import (  # type: ignore[no-redef, attr-defined]
        UndefinedType as UndefinedType,  # noqa: F401
    )
    from pydantic.schema import (
        field_schema,

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) {

	return nil
}

// Config - object lock configuration specified in
// https://docs.aws.amazon.com/AmazonS3/latest/API/Type_API_ObjectLockConfiguration.html
type Config struct {
	XMLNS             string   `xml:"xmlns,attr,omitempty"`
	XMLName           xml.Name `xml:"ObjectLockConfiguration"`
	ObjectLockEnabled string   `xml:"ObjectLockEnabled"`
	Rule              *struct {
		DefaultRetention DefaultRetention `xml:"DefaultRetention"`

@org_tensorflow//tensorflow
@com_google_absl//
@pybind11_abseil//pybind11_abseil
//external
@local
@com_github_googlecloudplatform_google_cloud_cpp//
@embedded_jdk//
^//$
@ruy//
EOF

  license_query "attr('licenses', 'notice', deps($BUILD_TARGET))" > $BATS_TEST_TMPDIR/expected_licenses
  license_query "deps($LICENSES_TARGET)" > $BATS_TEST_TMPDIR/actual_licenses

        # TODO: remove when deprecating Pydantic v1
        encoders: Dict[Any, Any] = {}
        if not PYDANTIC_V2:
            encoders = getattr(obj.__config__, "json_encoders", {})  # type: ignore[attr-defined]
            if custom_encoder:
                encoders.update(custom_encoder)
        obj_dict = _model_dump(
            obj,
            mode="json",
            include=include,