fix import_meta_graph without VariableV1 bug. #453

src/TensorFlowNET.Core/Framework/meta_graph.cs

@@ -268,6 +268,22 @@ namespace Tensorflow
 
             switch (graph.get_collection(key))
             {
+                case List<VariableV1> collection_list:
+                    col_def.BytesList = new Types.BytesList();
+                    foreach (var x in collection_list)
+                    {
+                        if(x is RefVariable x_ref_var)
+                        {
+                            var proto = x_ref_var.to_proto(export_scope);
+                            col_def.BytesList.Value.Add(proto.ToByteString());
+                        }
+                        else
+                        {
+                            Console.WriteLine($"Can't find to_proto method for type {x.GetType().Name}");
+                        }
+                    }
+
+                    break;
                 case List<RefVariable> collection_list:
                     col_def.BytesList = new Types.BytesList();
                     foreach (var x in collection_list)

src/TensorFlowNET.Core/Operations/Operation.Control.cs

@@ -52,10 +52,6 @@ namespace Tensorflow
 
         public void _set_control_flow_context(ControlFlowContext ctx)
         {
-            if (name.Contains("gradients/rnn/while/basic_rnn_cell/Tanh_grad/TanhGrad/f_acc"))
-            {
-
-            }
             _control_flow_context = ctx;
         }
 

src/TensorFlowNET.Core/Training/Saving/Saver.cs

@@ -14,6 +14,7 @@
    limitations under the License.
 ******************************************************************************/
 
+using NumSharp;
 using System;
 using System.Collections.Generic;
 using System.IO;
@@ -170,7 +171,7 @@ namespace Tensorflow
         {
             if (string.IsNullOrEmpty(latest_filename))
                 latest_filename = "checkpoint";
-            object model_checkpoint_path = "";
+            NDArray[] model_checkpoint_path = null;
             string checkpoint_file = "";
 
             if (global_step > 0)
@@ -183,15 +184,14 @@ namespace Tensorflow
             if (!_is_empty)
             {
                 model_checkpoint_path = sess.run(_saver_def.SaveTensorName,
-                    new FeedItem(_saver_def.FilenameTensorName, checkpoint_file)
-                );
+                    (_saver_def.FilenameTensorName, checkpoint_file));
 
                 if (write_state)
                 {
-                    _RecordLastCheckpoint(model_checkpoint_path.ToString());
+                    _RecordLastCheckpoint(model_checkpoint_path[0].ToString());
                     checkpoint_management.update_checkpoint_state_internal(
                         save_dir: save_path_parent,
-                        model_checkpoint_path: model_checkpoint_path.ToString(),
+                        model_checkpoint_path: model_checkpoint_path[0].ToString(),
                         all_model_checkpoint_paths: _last_checkpoints.Keys.Select(x => x).ToList(),
                         latest_filename: latest_filename,
                         save_relative_paths: _save_relative_paths);

src/TensorFlowNET.Core/Training/Saving/checkpoint_management.py.cs

@@ -44,8 +44,7 @@ namespace Tensorflow
             float? last_preserved_timestamp = null
             )
         {
-            CheckpointState ckpt = null;
-
+            CheckpointState ckpt = null; 
             // Writes the "checkpoint" file for the coordinator for later restoration.
             string coord_checkpoint_filename = _GetCheckpointFilename(save_dir, latest_filename);
             if (save_relative_paths)
@@ -65,7 +64,12 @@ namespace Tensorflow
                 throw new RuntimeError($"Save path '{model_checkpoint_path}' conflicts with path used for " +
                     "checkpoint state.  Please use a different save path.");
 
-            File.WriteAllText(coord_checkpoint_filename, ckpt.ToString());
+            // File.WriteAllText(coord_checkpoint_filename, ckpt.ToString());
+            File.WriteAllLines(coord_checkpoint_filename, new[] 
+            {
+                $"model_checkpoint_path: \"{ckpt.ModelCheckpointPath}\"",
+                $"all_model_checkpoint_paths: \"{ckpt.AllModelCheckpointPaths[0]}\"",
+            });
         }
 
         /// <summary>
@@ -98,7 +102,14 @@ namespace Tensorflow
                 all_model_checkpoint_paths.Add(model_checkpoint_path);
 
             // Relative paths need to be rewritten to be relative to the "save_dir"
-            // if model_checkpoint_path already contains "save_dir".
+            if (model_checkpoint_path.StartsWith(save_dir))
+            {
+                model_checkpoint_path = model_checkpoint_path.Substring(save_dir.Length + 1);
+                all_model_checkpoint_paths = all_model_checkpoint_paths
+                    .Select(x => x.Substring(save_dir.Length + 1))
+                    .ToList();
+            }
+                
 
             var coord_checkpoint_proto = new CheckpointState()
             {

src/TensorFlowNET.Core/Training/Saving/saver.py.cs

@@ -29,14 +29,12 @@ namespace Tensorflow
         {
             var meta_graph_def = meta_graph.read_meta_graph_file(meta_graph_or_file);
 
-            var meta = meta_graph.import_scoped_meta_graph_with_return_elements(
+            var (imported_vars, imported_return_elements) = meta_graph.import_scoped_meta_graph_with_return_elements(
                         meta_graph_def,
                         clear_devices: clear_devices,
                         import_scope: import_scope,
                         return_elements: return_elements);
 
-            var (imported_vars, imported_return_elements) = meta;
-
             var saver = _create_saver_from_imported_meta_graph(
                 meta_graph_def, import_scope, imported_vars);