fix NodesByDepth order.

src/TensorFlowNET.Core/Keras/Engine/Functional.cs

@@ -88,7 +88,7 @@ namespace Tensorflow.Keras.Engine
         void ComputeTensorUsageCount()
         {
             var available_tensors = inputs.Select(x => x.GetHashCode()).ToList();
-            var depth_keys = NodesByDepth.Keys.Reverse().Skip(1).ToArray();
+            var depth_keys = NodesByDepth.Keys.OrderBy(x => x).Reverse().Skip(1).ToArray();
             foreach(var depth in depth_keys)
             {
                 foreach(var node in NodesByDepth[depth])
@@ -190,7 +190,7 @@ namespace Tensorflow.Keras.Engine
             }
 
             // Get sorted list of layer depths.
-            var depth_keys = layers_by_depth.Keys.Reverse();
+            var depth_keys = layers_by_depth.Keys.OrderBy(x => x).Reverse();
 
             // Set self.layers ordered by depth.
             var layers = new List<Layer>();
@@ -200,12 +200,12 @@ namespace Tensorflow.Keras.Engine
 
                 // Network.layers needs to have a deterministic order:
                 // here we order them by traversal order.
-                layers_for_depth.Reverse();
+                layers_for_depth = layers_for_depth.OrderBy(x => layer_indices[x]).ToList();
                 layers.AddRange(layers_for_depth);
             }
 
             // Get sorted list of node depths.
-            depth_keys = nodes_by_depth.Keys.Reverse();
+            depth_keys = nodes_by_depth.Keys.OrderBy(x => x).Reverse();
 
             return (network_nodes, nodes_by_depth, layers, layers_by_depth);
         }
@@ -290,7 +290,7 @@ namespace Tensorflow.Keras.Engine
                 tensor_dict[x_id] = Enumerable.Range(0, tensor_usage_count[x_id]).Select(x => y1).ToArray();
             }
 
-            var depth_keys = NodesByDepth.Keys.Reverse().ToArray();
+            var depth_keys = NodesByDepth.Keys.OrderBy(x => x).Reverse().ToArray();
 
             foreach(var depth in depth_keys)
             {

src/TensorFlowNET.Core/Keras/Engine/TensorFlowOpLayer.cs

@@ -2,6 +2,7 @@
 using System.Collections.Generic;
 using System.Text;
 using Tensorflow.Keras.ArgsDefinition;
+using static Tensorflow.Binding;
 
 namespace Tensorflow.Keras.Engine
 {
@@ -25,7 +26,13 @@ namespace Tensorflow.Keras.Engine
 
         protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
-            return base.Call(inputs, state, is_training);
+            return MakOp(inputs);
         }
+
+        // [AutoGraph]
+        Tensors MakOp(Tensors inputs)
+        {
+            return inputs;
+        } 
     }
 }

src/TensorFlowNET.Core/Operations/array_ops.cs

@@ -835,22 +835,24 @@ namespace Tensorflow
             }
 
             // Restore shape information where possible.
-            var paddings_constant = tensor_util.constant_value(
-                result.op.inputs[1], partial: true);
-            var input_shape = result.op.inputs[0].TensorShape;
-            if (input_shape.ndim > -1 &&
-                !result.TensorShape.is_fully_defined() &&
-                !(paddings_constant is null))
+            if (!tf.Context.executing_eagerly())
             {
-                var new_shape = new List<int>();
-                foreach((NDArray padding, int dim) in zip(paddings_constant.GetNDArrays(), np.array(input_shape.dims).GetNDArrays()))
+                var paddings_constant = tensor_util.constant_value(result.op.inputs[1], partial: true);
+                var input_shape = result.op.inputs[0].TensorShape;
+                if (input_shape.ndim > -1 &&
+                    !result.TensorShape.is_fully_defined() &&
+                    !(paddings_constant is null))
                 {
-                    if (padding is null || dim == -1 || padding.GetData<int>().Contains(-1))
-                        new_shape.Add(-1);
-                    else
-                        new_shape.Add(np.sum(padding) + dim);
+                    var new_shape = new List<int>();
+                    foreach ((NDArray padding, int dim) in zip(paddings_constant.GetNDArrays(), np.array(input_shape.dims).GetNDArrays()))
+                    {
+                        if (padding is null || dim == -1 || padding.GetData<int>().Contains(-1))
+                            new_shape.Add(-1);
+                        else
+                            new_shape.Add(np.sum(padding) + dim);
+                    }
+                    result.set_shape(new_shape.ToArray());
                 }
-                result.set_shape(new_shape.ToArray());
             }
 
             return result;

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -175,6 +175,15 @@ namespace Tensorflow
 
         public static Tensor pad(Tensor input, Tensor paddings, string name = null)
         {
+            if (tf.Context.executing_eagerly())
+            {
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "Pad", name,
+                    null,
+                    input, paddings);
+                return results[0];
+            }
+
             var _op = tf.OpDefLib._apply_op_helper("Pad", name: name, args: new { input, paddings });
 
             return _op.output;