["tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], dense_shapes = [#tf_type.shape<>, #tf_type.shape<>], device = "", num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = [], resultSegmentSizes = array<i32: 2, 2, 2, 2, 0, 0>, sparse_types = ["tfdtype$DT_STRING", "tfdtype$DT_INT64"]} : (tensor<32x!tf_type.string>, tensor<0x!tf_type.string>, tensor<2x!tf_type.string>, tensor<2x!tf_type.string>, tensor<0x!tf_type.string>, tensor<0xf32>, tensor<0xf32>) -> (tensor<?x2xi64>, tensor<?x2xi64>, tensor<?x!tf_type.string>,...

y":"keep_alive_interval","value":"0s"},{"key":"reconnect_interval","value":"0s"},{"key":"queue_dir","value":""},{"key":"queue_limit","value":"0"}]},"notify_mysql":{"_":[{"key":"enable","value":"off"},{"key":"format","value":"namespace"},{"key":"dsn_string","value":""},{"key":"table","value":""},{"key":"queue_dir","value":""},{"key":"queue_limit","value":"0"},{"key":"max_open_connections","value":"2"}]},"notify_nats":{"_":[{"key":"enable","value":"off"},{"key":"address","value":""},{"key":"subjec...

			if err != nil {
				klog.ErrorS(err, "Error for parsing the resolv.conf file")
			} else {
				dnsString = dnsString + "search"
				for _, search := range hostSearch {
					dnsString = dnsString + fmt.Sprintf(" %s", search)
				}
				dnsString = dnsString + "\n"
			}
		}
	}
	if err := os.WriteFile(resolvePath, []byte(dnsString), 0600); err != nil {
		klog.ErrorS(err, "Could not write dns nameserver in the file", "path", resolvePath)

namespace tensorflow {
namespace {

Graph* BM_ScalarSummaryOp(TensorShape shape, std::string tag, float value) {
  Graph* g = new Graph(OpRegistry::Global());
  Tensor tags(DT_STRING, shape);
  Tensor values(DT_FLOAT, shape);
  for (int i = 0; i < tags.NumElements(); ++i) {
    tags.flat<tstring>()(i) = tag;
    values.flat<float>()(i) = value;
  }
  Node* ret;

    case tflite::TensorType_UINT32:
      return tensorflow::DT_UINT32;
    case tflite::TensorType_INT64:
      return tensorflow::DT_INT64;
    case tflite::TensorType_STRING:
      return tensorflow::DT_STRING;
    case tflite::TensorType_UINT8:
      return tensorflow::DT_UINT8;
    case tflite::TensorType_UINT16:
      return tensorflow::DT_UINT16;
    case tflite::TensorType_UINT64:
      return tensorflow::DT_UINT64;

  ExpectNodeEqual<double>(c.node(), {42.0, 42.0, 42.0, 42.0}, {2, 2});

  auto d = ops::Const(root, {"1", "2", "3", "4", "5", "6"}, {2, 3});
  TF_CHECK_OK(root.status());
  EXPECT_EQ(d.op().output_type(0), DT_STRING);
  ExpectNodeEqual<tstring>(d.node(), {"1", "2", "3", "4", "5", "6"}, {2, 3});
}

TEST(ConstOpTest, FromProto) {
  Scope root = Scope::NewRootScope();
  TensorProto proto;
  proto.set_dtype(DT_DOUBLE);

  EXPECT_FALSE(root.status().ok());
}

TEST(CCOpTest, InvalidFinalize) {
  Scope root = Scope::NewRootScope();
  auto read_up_to =
      ops::ReaderReadUpTo(root, Variable(root, {}, DT_STRING),
                          Variable(root, {}, DT_STRING), static_cast<int32>(2));
  EXPECT_FALSE(root.status().ok());
  auto err_msg = std::string(root.status().message());
  EXPECT_NE(err_msg.find("'num_records' passed int32 expected int64"),

    case DT_BFLOAT16:
    case DT_HALF:
    case DT_FLOAT8_E5M2:
    case DT_FLOAT8_E4M3FN:
      return ConvertTensorOfCustomFloatType(input_tensor, type);
    case DT_STRING:
      return ConvertStringTensor(input_tensor, type);
    default:
      // TODO(hinsu): Remove mangling now that there is a special attribute.
      return ElementsAttr(

  // Add a _Retval node to loop body.
  NodeDefBuilder ret_builder(
      absl::StrCat("recv_oc_while_body_ret_", while_node_name), "_Retval");
  ret_builder.Attr("T", DT_STRING);
  ret_builder.Attr("index", 0);
  ret_builder.Input(key_arg->name(), 0, DT_STRING);
  NodeDef ret_def;
  TF_RETURN_IF_ERROR(ret_builder.Finalize(&ret_def));
  TF_ASSIGN_OR_RETURN(Node * ret_node, body_graph->AddNode(ret_def));

                                      const std::string& s,
                                      ImmediateTensorHandlePtr* out) {
  int64_t flat_shape[] = {1};
  AbstractTensorPtr tensor(ctx->CreateTensor(DT_STRING, flat_shape));
  if (tensor.get() == nullptr) {
    return errors::Internal(
        "Failed to create vector string tensor for checkpoint restore");
  }
  // Use placement new to construct the string, since we don't have