Fix fused_batch_norm_v3 for eager mode.

src/TensorFlowNET.Core/Gradients/gradient_exclustions.cs

@@ -20,6 +20,7 @@ namespace Tensorflow.Gradients
         public static int[] OpGradientUnusedOutputIndices(string op_name)
             => op_name switch
             {
+                "FusedBatchNormV3" => new[] { 0, 1, 2 },
                 "ReadVariableOp" => new int[0],
                 "SoftmaxCrossEntropyWithLogits" => new[] { 0 },
                 "TensorArrayConcat" => new[] { 0 },

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

@@ -21,7 +21,7 @@ namespace Tensorflow.Keras.Engine
             _channels_first = args.DataFormat == "channels_first";
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             if (_channels_first)
             {

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

@@ -268,7 +268,7 @@ namespace Tensorflow.Keras.Engine
             nodes_in_decreasing_depth.Insert(nodes_in_decreasing_depth.Count, node);
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             return run_internal_graph(inputs, is_training);
         }
@@ -305,6 +305,7 @@ namespace Tensorflow.Keras.Engine
                     tensor_dict[node.FlatInputIds[0]] = new Tensor[0];
 
                     var outputs = node.Layer.Apply(layer_inputs, is_training: training);
+                    
                     // Update tensor_dict.
                     foreach (var (x_id, y) in zip(node.FlatOutputIds, outputs))
                         tensor_dict[x_id] = Enumerable.Range(0, tensor_usage_count[x_id]).Select(x => y).ToArray();

src/TensorFlowNET.Core/Keras/Engine/Layer.Apply.cs

@@ -46,7 +46,7 @@ namespace Tensorflow.Keras.Engine
                 if (!built)
                     MaybeBuild(inputs);
 
-                outputs = CallFn(inputs, state: state, is_training: is_training);
+                outputs = Call(inputs, state: state, is_training: is_training);
 
                 outputs = _set_connectivity_metadata_(inputs, outputs);
                 _handle_activity_regularization(inputs, outputs);

src/TensorFlowNET.Core/Keras/Engine/Layer.FunctionalConstructionCall.cs

@@ -42,7 +42,7 @@ namespace Tensorflow.Keras.Engine
                 if (!dynamic)
                     throw new NotImplementedException("");
 
-                outputs = CallFn(inputs);
+                outputs = Call(inputs);
 
                 outputs = _set_connectivity_metadata_(inputs, outputs);
                 _handle_activity_regularization(inputs, outputs);

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

@@ -162,7 +162,7 @@ namespace Tensorflow.Keras.Engine
         /// <param name="state"></param>
         /// <param name="is_training"></param>
         /// <returns></returns>
-        protected virtual Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected virtual Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             throw new NotImplementedException("");
         }

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

@@ -23,9 +23,9 @@ namespace Tensorflow.Keras.Engine
             built = true;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
-            return base.CallFn(inputs, state, is_training);
+            return base.Call(inputs, state, is_training);
         }
     }
 }

src/TensorFlowNET.Core/Keras/Layers/BatchNormalization.cs

@@ -119,7 +119,7 @@ namespace Tensorflow.Keras.Layers
             built = true;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             Tensor outputs = null;
 

src/TensorFlowNET.Core/Keras/Layers/Convolutional.cs

@@ -98,7 +98,7 @@ namespace Tensorflow.Keras.Layers
             built = true;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool training = false)
         {
             var outputs = _convolution_op.Apply(inputs, kernel);
             if (use_bias)

src/TensorFlowNET.Core/Keras/Layers/Dense.cs

@@ -65,7 +65,7 @@ namespace Tensorflow.Keras.Layers
             built = true;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool training = false)
         {
             Tensor outputs = null;
             var rank = inputs.rank;

src/TensorFlowNET.Core/Keras/Layers/Dropout.cs

@@ -18,7 +18,7 @@ namespace Tensorflow.Keras.Layers
             this.args = args;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             var output = tf_utils.smart_cond(is_training,
                 () => tf.nn.dropout(inputs,

src/TensorFlowNET.Core/Keras/Layers/Embedding.cs

@@ -62,7 +62,7 @@ namespace Tensorflow.Keras.Layers
             built = true;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             var dtype = inputs.dtype;
             if (dtype != tf.int32 && dtype != tf.int64)

src/TensorFlowNET.Core/Keras/Layers/LSTM.cs

@@ -29,9 +29,9 @@ namespace Tensorflow.Keras.Layers
                 .ToArray();
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
-            return base.CallFn(inputs, state: state, is_training: is_training);
+            return base.Call(inputs, state: state, is_training: is_training);
         }
     }
 }

src/TensorFlowNET.Core/Keras/Layers/Pooling2D.cs

@@ -36,7 +36,7 @@ namespace Tensorflow.Keras.Layers
             input_spec = new InputSpec(ndim: 4);
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             int[] pool_shape;
             int[] strides;

src/TensorFlowNET.Core/Keras/Layers/Rescaling.cs

@@ -20,7 +20,7 @@ namespace Tensorflow.Keras.Layers
             this.args = args;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             scale = math_ops.cast(args.Scale, args.DType);
             offset = math_ops.cast(args.Offset, args.DType);

src/TensorFlowNET.Core/Keras/Layers/ZeroPadding2D.cs

@@ -29,7 +29,7 @@ namespace Tensorflow.Keras.Layers
             this.input_spec = new InputSpec(ndim: 4);
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             return tf.keras.backend.spatial_2d_padding(inputs,
                 padding: padding,

src/TensorFlowNET.Core/Operations/NnOps/BasicLSTMCell.cs

@@ -74,7 +74,7 @@ namespace Tensorflow
         /// <param name="training"></param>
         /// <param name="state"></param>
         /// <returns></returns>
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             var one = constant_op.constant(1, dtype: dtypes.int32);
             // Parameters of gates are concatenated into one multiply for efficiency.

src/TensorFlowNET.Core/Operations/NnOps/BasicRNNCell.cs

@@ -67,7 +67,7 @@ namespace Tensorflow
             built = true;
         }
 
-        protected override Tensors CallFn(Tensors inputs, Tensor state = null, bool is_training = false)
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
         {
             // Most basic RNN: output = new_state = act(W * input + U * state + B).
             var concat = array_ops.concat(new Tensor[] { inputs, state }, 1);

src/TensorFlowNET.Core/Operations/NnOps/gen_nn_ops.cs

@@ -321,6 +321,23 @@ namespace Tensorflow.Operations
         bool is_training = true,
         string name = null)
         {
+            if (tf.executing_eagerly())
+            {
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "FusedBatchNormV3", name,
+                    null,
+                    x,
+                    scale,
+                    offset,
+                    mean,
+                    variance,
+                    "epsilon", epsilon,
+                    "data_format", data_format,
+                    "is_training", is_training);
+
+                return results;
+            }
+
             var _op = tf.OpDefLib._apply_op_helper("FusedBatchNormV3", name: name, args: new
             {
                 x,

src/TensorFlowNET.Core/Tensorflow.Binding.csproj

@@ -79,7 +79,7 @@ https://tensorflownet.readthedocs.io</Description>
 
   <ItemGroup>
     <PackageReference Include="Google.Protobuf" Version="3.11.4" />
-    <PackageReference Include="NumSharp.Lite" Version="0.1.8" />
+    <PackageReference Include="NumSharp.Lite" Version="0.1.9" />
     <PackageReference Include="Protobuf.Text" Version="0.4.0" />
   </ItemGroup>
 

src/TensorFlowNET.Core/Tensors/Tensor.Value.cs

@@ -158,6 +158,9 @@ namespace Tensorflow
             UnmanagedStorage storage;
             switch (dtype)
             {
+                case TF_DataType.TF_BOOL:
+                    storage = new UnmanagedStorage(NPTypeCode.Boolean);
+                    break;
                 case TF_DataType.TF_STRING:
                     return np.array(StringBytes()[0]);
                 case TF_DataType.TF_INT32: