diff --git a/src/TensorFlowNET.Core/Binding.Util.cs b/src/TensorFlowNET.Core/Binding.Util.cs
index 254f4ded..d8732224 100644
--- a/src/TensorFlowNET.Core/Binding.Util.cs
+++ b/src/TensorFlowNET.Core/Binding.Util.cs
@@ -424,6 +424,9 @@ namespace Tensorflow
             return true;
         }
 
+        public static bool empty<T>(this Queue<T> queue)
+            => queue.Count == 0;
+
         public static TValue SetDefault<TKey, TValue>(this Dictionary<TKey, TValue> dic, TKey key, TValue value)
         {
             if (dic.ContainsKey(key))
diff --git a/src/TensorFlowNET.Core/Keras/Engine/Layer.Layers.cs b/src/TensorFlowNET.Core/Keras/Engine/Layer.Layers.cs
index 1cddc769..cccb605b 100644
--- a/src/TensorFlowNET.Core/Keras/Engine/Layer.Layers.cs
+++ b/src/TensorFlowNET.Core/Keras/Engine/Layer.Layers.cs
@@ -11,6 +11,7 @@ namespace Tensorflow.Keras.Engine
     public partial class Layer
     {
         protected List<Layer> _layers = new List<Layer>();
+        public List<Layer> Layers => _layers;
 
         protected Layer Dense(int units,
             Activation activation = null,
diff --git a/src/TensorFlowNET.Core/Keras/Engine/Layer.cs b/src/TensorFlowNET.Core/Keras/Engine/Layer.cs
index f15e2edf..00cd858d 100644
--- a/src/TensorFlowNET.Core/Keras/Engine/Layer.cs
+++ b/src/TensorFlowNET.Core/Keras/Engine/Layer.cs
@@ -61,7 +61,6 @@ namespace Tensorflow.Keras.Engine
         protected List<IVariableV1> trainable_weights;
 
         public virtual List<IVariableV1> trainable_variables => trainable_weights;
-         
 
         protected List<IVariableV1> non_trainable_weights;
         public List<IVariableV1> non_trainable_variables => non_trainable_weights;
@@ -83,7 +82,8 @@ namespace Tensorflow.Keras.Engine
         ThreadLocal<CallContext> callContext;
         public CallContext CallContext => callContext.Value;
         public Tensor[] input => inboundNodes[0].input_tensors;
-
+        public Dictionary<int, List<Node>> NodesByDepth { get; set; }
+        public TensorShape output_shape => inboundNodes[0].Outputs.shape;
         public Layer(LayerArgs args)
         {
             this.args = args;
@@ -224,5 +224,23 @@ namespace Tensorflow.Keras.Engine
                 this.name = base_layer_utils.unique_layer_name(base_name, zero_based: zero_based);
             }
         }
+
+        public int count_params()
+        {
+            if (Trainable)
+                return layer_utils.count_params(this, weights);
+            return 0;
+        }
+
+        public List<IVariableV1> weights
+        {
+            get
+            {
+                var weights = new List<IVariableV1>();
+                weights.AddRange(trainable_weights);
+                weights.AddRange(non_trainable_weights);
+                return weights;
+            }
+        }
     }
 }
diff --git a/src/TensorFlowNET.Core/Operations/gen_array_ops.cs b/src/TensorFlowNET.Core/Operations/gen_array_ops.cs
index 7f1f9be0..c35ff349 100644
--- a/src/TensorFlowNET.Core/Operations/gen_array_ops.cs
+++ b/src/TensorFlowNET.Core/Operations/gen_array_ops.cs
@@ -388,19 +388,19 @@ namespace Tensorflow
             return _op.outputs[0];
         }
 
-        public static Tensor select<Tx, Ty>(Tensor condition, Tx t, Ty e, string name = null)
+        public static Tensor select<Tx, Ty>(Tensor condition, Tx x, Ty y, string name = null)
         {
             if (tf.Context.executing_eagerly())
             {
                 var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
-                    "SelectV2", name,
+                    "Select", name,
                     null,
-                    condition, t, e);
+                    condition, x, y);
 
                 return results[0];
             }
 
-            var _op = tf.OpDefLib._apply_op_helper("Select", name, new { condition, t, e });
+            var _op = tf.OpDefLib._apply_op_helper("Select", name, new { condition, t = x, e = y });
             return _op.outputs[0];
         }
 
@@ -580,26 +580,33 @@ namespace Tensorflow
         /// <param name="shrink_axis_mask">An optional `int`. Defaults to `0`.</param>
         /// <param name="name">A name for the operation (optional).</param>
         /// <returns>A `Tensor`. Has the same type as `dy`.</returns>
-        public static Tensor strided_slice_grad(Tensor shape, Tensor begin, Tensor end, Tensor strides, Tensor dy, 
+        public static Tensor strided_slice_grad(Tensor shape, Tensor begin, Tensor end, Tensor strides, Tensor dy,
             int begin_mask = 0, int end_mask = 0, int ellipsis_mask = 0, int new_axis_mask = 0,
             int shrink_axis_mask = 0, string name = null)
-        {
-            var op = tf.OpDefLib._apply_op_helper("StridedSliceGrad", name: name, args: new
-            {
-                shape,
-                begin,
-                end,
-                strides,
-                dy,
-                begin_mask,
-                end_mask,
-                ellipsis_mask,
-                new_axis_mask,
-                shrink_axis_mask
-            });
-
-            return op.output;
-        }
+            => tf.Context.RunInAutoMode(()
+                => tf.OpDefLib._apply_op_helper("StridedSliceGrad", name, new
+                {
+                    shape,
+                    begin,
+                    end,
+                    strides,
+                    dy,
+                    begin_mask,
+                    end_mask,
+                    ellipsis_mask,
+                    new_axis_mask,
+                    shrink_axis_mask
+                }).output, ()
+                => tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "StridedSliceGrad", name,
+                    null,
+                    shape, begin, end, strides, dy,
+                    "begin_mask", begin_mask,
+                    "end_mask", end_mask,
+                    "ellipsis_mask", ellipsis_mask,
+                    "new_axis_mask", new_axis_mask,
+                    "shrink_axis_mask", shrink_axis_mask).FirstOrDefault(),
+                shape, begin, end, strides, dy);
 
         public static Tensor slice<Tb, Ts>(Tensor input, Tb begin, Ts size, string name = null)
         {