minor change in TextClassificationTrain

src/TensorFlowNET.Core/Graphs/Graph.cs

@@ -160,7 +160,14 @@ namespace Tensorflow
                 }
                 else if (!name.Contains(":") & !allow_operation)
                 {
-                    throw new NotImplementedException("_as_graph_element_locked");
+                    // Looks like an Operation name but can't be an Operation.
+                    if (_nodes_by_name.ContainsKey(name))
+                        // Yep, it's an Operation name
+                        throw new ValueError($"The name {name} refers to an Operation, not a {types_str}.");
+                    else
+                        throw new ValueError(
+                            $"The name {name} looks like an (invalid) Operation name, not a {types_str}" +
+                            " Tensor names must be of the form \"<op_name>:<output_index>\".");
                 }
             }
 

test/TensorFlowNET.Examples/TextProcess/TextClassificationTrain.cs

@@ -79,13 +79,13 @@ namespace TensorFlowNET.Examples.CnnTextClassification
             var num_batches_per_epoch = (len(train_x) - 1) / BATCH_SIZE + 1;
             double max_accuracy = 0;
 
-            Tensor is_training = graph.get_operation_by_name("is_training");
-            Tensor model_x = graph.get_operation_by_name("x");
-            Tensor model_y = graph.get_operation_by_name("y");
-            Tensor loss = graph.get_operation_by_name("loss/value");
-            Tensor optimizer = graph.get_operation_by_name("loss/optimizer");
-            Tensor global_step = graph.get_operation_by_name("global_step");
-            Tensor accuracy = graph.get_operation_by_name("accuracy/value");
+            Tensor is_training = graph.get_tensor_by_name("is_training:0");
+            Tensor model_x = graph.get_tensor_by_name("x:0");
+            Tensor model_y = graph.get_tensor_by_name("y:0");
+            Tensor loss = graph.get_tensor_by_name("loss/value:0");
+            Tensor optimizer = graph.get_tensor_by_name("loss/optimizer:0");
+            Tensor global_step = graph.get_tensor_by_name("global_step:0");
+            Tensor accuracy = graph.get_tensor_by_name("accuracy/value:0");
             stopwatch = Stopwatch.StartNew();
             int i = 0;
             foreach (var (x_batch, y_batch, total) in train_batches)