Use tensor.Id instead of GetHashCode.

src/TensorFlowNET.Core/Binding.cs

@@ -4,7 +4,7 @@ namespace Tensorflow
 {
     public static partial class Binding
     {
-        [DebuggerNonUserCode]
+        [DebuggerHidden]
         public static tensorflow tf { get; } = New<tensorflow>();
 
         /// <summary>

src/TensorFlowNET.Core/Eager/EagerTensor.Creation.cs

@@ -4,7 +4,7 @@ using static Tensorflow.Binding;
 
 namespace Tensorflow.Eager
 {
-    public partial class EagerTensor : Tensor
+    public partial class EagerTensor
     {
         public EagerTensor() : base(IntPtr.Zero)
         {
@@ -48,8 +48,8 @@ namespace Tensorflow.Eager
             if (_handle == IntPtr.Zero)
                 _handle = c_api.TFE_TensorHandleResolve(EagerTensorHandle, tf.Status.Handle);
 
-            //print($"new Tensor {Id} {_handle.ToString("x16")}");
-            //print($"new TensorHandle {Id} {EagerTensorHandle.ToString("x16")}");
+            // print($"New TensorHandle {Id} 0x{_handle.ToString("x16")}");
+            // print($"New EagerTensorHandle {Id} {EagerTensorHandle}");
 
             return this;
         }
@@ -96,14 +96,14 @@ namespace Tensorflow.Eager
         {
             base.DisposeManagedResources();
 
-            //print($"deleting DeleteTensorHandle {Id} {EagerTensorHandle.ToString("x16")}");
+            // print($"Delete EagerTensorHandle {Id} {EagerTensorHandle}");
             EagerTensorHandle.Dispose();
         }
 
         protected override void DisposeUnmanagedResources(IntPtr handle)
         {
             base.DisposeUnmanagedResources(handle);
-            //print($"deleting DeleteTensorHandle {Id} {_handle.ToString("x16")}");
+            // print($"Delete TensorHandle {Id} 0x{_handle.ToString("x16")}");
         }
     }
 }

src/TensorFlowNET.Keras/Engine/Functional.cs

@@ -23,8 +23,7 @@ namespace Tensorflow.Keras.Engine
         List<KerasHistory> _output_coordinates;
         public string[] NetworkNodes { get; set; }
 
-        Dictionary<int, int> tensor_usage_count;
-        public Dictionary<int, int> TensorUsageCount => tensor_usage_count;
+        Dictionary<long, int> tensor_usage_count;
 
         public Functional(Tensors inputs, Tensors outputs, string name = null)
             : base(new ModelArgs
@@ -38,7 +37,7 @@ namespace Tensorflow.Keras.Engine
             _output_layers = new List<ILayer>();
             _input_coordinates = new List<KerasHistory>();
             _output_coordinates = new List<KerasHistory>();
-            tensor_usage_count = new Dictionary<int, int>();
+            tensor_usage_count = new Dictionary<long, int>();
             if (this is Sequential)
                 return;
             _init_graph_network(inputs, outputs);
@@ -116,33 +115,33 @@ namespace Tensorflow.Keras.Engine
 
         void ComputeTensorUsageCount()
         {
-            var available_tensors = inputs.Select(x => x.GetHashCode()).ToList();
+            var available_tensors = inputs.Select(x => x.Id).ToList();
             var depth_keys = NodesByDepth.Keys.OrderBy(x => x).Reverse().Skip(1).ToArray();
             foreach (var depth in depth_keys)
             {
                 foreach (var node in NodesByDepth[depth])
                 {
-                    var input_tensors = node.KerasInputs.Select(x => x.GetHashCode()).ToArray();
+                    var input_tensors = node.KerasInputs.Select(x => x.Id).ToArray();
                     if (input_tensors.issubset(available_tensors))
                     {
                         foreach (var tensor in node.KerasInputs)
                         {
-                            if (!tensor_usage_count.ContainsKey(tensor.GetHashCode()))
-                                tensor_usage_count[tensor.GetHashCode()] = 0;
-                            tensor_usage_count[tensor.GetHashCode()] += 1;
+                            if (!tensor_usage_count.ContainsKey(tensor.Id))
+                                tensor_usage_count[tensor.Id] = 0;
+                            tensor_usage_count[tensor.Id] += 1;
                         }
 
                         foreach (var output_tensor in node.Outputs)
-                            available_tensors.Add(output_tensor.GetHashCode());
+                            available_tensors.Add(output_tensor.Id);
                     }
                 }
             }
 
             foreach (var tensor in outputs)
             {
-                if (!tensor_usage_count.ContainsKey(tensor.GetHashCode()))
-                    tensor_usage_count[tensor.GetHashCode()] = 0;
-                tensor_usage_count[tensor.GetHashCode()] += 1;
+                if (!tensor_usage_count.ContainsKey(tensor.Id))
+                    tensor_usage_count[tensor.Id] = 0;
+                tensor_usage_count[tensor.Id] += 1;
             }
         }
 
@@ -316,12 +315,11 @@ namespace Tensorflow.Keras.Engine
                     input_t.KerasMask = masks[i];
             }
 
-            var tensor_dict = new Dictionary<int, Queue<Tensor>>();
+            var tensor_dict = new Dictionary<long, Queue<Tensor>>();
             foreach (var (x, y) in zip(this.inputs, inputs))
             {
                 var y1 = conform_to_reference_input(y, x);
-                var x_id = x.GetHashCode();
-                tensor_dict[x_id] = new Queue<Tensor>(Enumerable.Range(0, tensor_usage_count[x_id]).Select(x => y1));
+                tensor_dict[x.Id] = new Queue<Tensor>(Enumerable.Range(0, tensor_usage_count[x.Id]).Select(x => y1));
             }
 
             var depth_keys = NodesByDepth.Keys.OrderBy(x => x).Reverse().ToArray();
@@ -347,13 +345,10 @@ namespace Tensorflow.Keras.Engine
                 }
             }
 
-            var output_tensors = new List<Tensor>();
+            var output_tensors = new Tensors();
 
             foreach (var x in outputs)
-            {
-                var x_id = x.GetHashCode();
-                output_tensors.append(tensor_dict[x_id].Dequeue());
-            }
+                output_tensors.Add(tensor_dict[x.Id].Dequeue());
 
             return output_tensors;
         }

src/TensorFlowNET.Keras/Engine/Node.cs

@@ -42,10 +42,10 @@ namespace Tensorflow.Keras.Engine
         public List<Tensor> KerasInputs { get; set; } = new List<Tensor>();
         public ILayer Layer { get; set; }
         public bool is_input => args.InputTensors == null;
-        public int[] FlatInputIds { get; set; }
-        public int[] FlatOutputIds { get; set; }
+        public long[] FlatInputIds { get; set; }
+        public long[] FlatOutputIds { get; set; }
         bool _single_positional_tensor_passed => KerasInputs.Count() == 1;
-        Dictionary<int, int> _keras_inputs_ids_and_indices = new Dictionary<int, int>();
+        Dictionary<int, long> _keras_inputs_ids_and_indices = new Dictionary<int, long>();
         public INode[] ParentNodes
         {
             get
@@ -70,7 +70,7 @@ namespace Tensorflow.Keras.Engine
                 KerasInputs.AddRange(args.InputTensors);
 
             foreach (var (i, ele) in enumerate(KerasInputs))
-                _keras_inputs_ids_and_indices[i] = ele.GetHashCode();
+                _keras_inputs_ids_and_indices[i] = ele.Id;
 
             // Wire up Node to Layers.
             layer.InboundNodes.Add(this);
@@ -89,8 +89,8 @@ namespace Tensorflow.Keras.Engine
                 tensor.KerasHistory = new KerasHistory(layer, node_index, i, tensor);
 
             // Cached for performance.
-            FlatInputIds = KerasInputs.Select(x => x.GetHashCode()).ToArray();
-            FlatOutputIds = Outputs.Select(x => x.GetHashCode()).ToArray();
+            FlatInputIds = KerasInputs.Select(x => x.Id).ToArray();
+            FlatOutputIds = Outputs.Select(x => x.Id).ToArray();
         }
 
         /// <summary>
@@ -98,7 +98,7 @@ namespace Tensorflow.Keras.Engine
         /// </summary>
         /// <param name="tensor_dict"></param>
         /// <returns></returns>
-        public Tensors MapArguments(Dictionary<int, Queue<Tensor>> tensor_dict)
+        public Tensors MapArguments(Dictionary<long, Queue<Tensor>> tensor_dict)
         {
             if (_single_positional_tensor_passed)
             {