BatchNormalization return tuple for call

Author: Oceania2018

src/TensorFlowNET.Core/APIs/tf.layers.cs

@@ -63,7 +63,7 @@ public Tensor conv2d(Tensor inputs,
                     trainable: trainable,
                     name: name);
 
-                return layer.apply(inputs);
+                return layer.apply(inputs).Item1;
             }
 
             /// <summary>
@@ -117,7 +117,7 @@ public Tensor batch_normalization(Tensor inputs,
                     trainable: trainable,
                     name: name);
 
-                return layer.apply(inputs, training: training);
+                return layer.apply(inputs, training: training).Item1;
             }
 
             /// <summary>
@@ -143,7 +143,7 @@ public Tensor max_pooling2d(Tensor inputs,
                     data_format: data_format,
                     name: name);
 
-                return layer.apply(inputs);
+                return layer.apply(inputs).Item1;
             }
 
             /// <summary>
@@ -179,7 +179,7 @@ public Tensor dense(Tensor inputs,
                     kernel_initializer: kernel_initializer, 
                     trainable: trainable);
 
-                return layer.apply(inputs);
+                return layer.apply(inputs).Item1;
             }
 
             /// <summary>

src/TensorFlowNET.Core/APIs/tf.nn.cs

@@ -76,7 +76,7 @@ public Tensor dropout(Tensor x, Tensor keep_prob = null, Tensor noise_shape = nu
             /// <param name="swap_memory"></param>
             /// <param name="time_major"></param>
             /// <returns>A pair (outputs, state)</returns>
-            public (Tensor, Tensor) dynamic_rnn(RNNCell cell, Tensor inputs,
+            public (Tensor, Tensor) dynamic_rnn(RnnCell cell, Tensor inputs,
                 Tensor sequence_length = null, TF_DataType dtype = TF_DataType.DtInvalid,
                 int? parallel_iterations = null, bool swap_memory = false, bool time_major = false)
                 => rnn.dynamic_rnn(cell, inputs, sequence_length: sequence_length, dtype: dtype,

src/TensorFlowNET.Core/Graphs/Graph.Control.cs

@@ -18,6 +18,7 @@ limitations under the License.
 using System.Diagnostics.CodeAnalysis;
 using System.Linq;
 using Tensorflow.Operations;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Graphs/Graph.cs

@@ -262,15 +262,11 @@ public Operation create_op(string op_type, Tensor[] inputs, TF_DataType[] dtypes
 
             if (string.IsNullOrEmpty(name))
                 name = op_type;
+
             // If a names ends with a '/' it is a "name scope" and we use it as-is,
             // after removing the trailing '/'.
             name = name.EndsWith("/") ? ops.name_from_scope_name(name) : unique_name(name);
             var node_def = ops._NodeDef(op_type, name, device: "", attrs: attrs);
-
-            if (name.Contains("define_loss/bigger_box_loss/mul_13"))
-            {
-
-            }
 
             var input_ops = inputs.Select(x => x.op).ToArray();
             var control_inputs = _control_dependencies_for_inputs(input_ops);
@@ -377,7 +373,11 @@ public string name_scope(string name)
         /// <returns>A string to be passed to `create_op()` that will be used
         /// to name the operation being created.</returns>
         public string unique_name(string name, bool mark_as_used = true)
-        {
+        {
+            if (name.EndsWith("basic_r_n_n_cell"))
+            {
+
+            }
             if (!String.IsNullOrEmpty(_name_stack))
                 name = _name_stack + "/" + name;
             // For the sake of checking for names in use, we treat names as case
@@ -405,7 +405,7 @@ public string unique_name(string name, bool mark_as_used = true)
 
                 // Return the new name with the original capitalization of the given name.
                 name = $"{name}_{i-1}";
-            }
+            }
             return name;
         }
 

src/TensorFlowNET.Core/Graphs/_ControlDependenciesController.cs

@@ -16,6 +16,7 @@ limitations under the License.
 
 using System.Collections.Generic;
 using Tensorflow.Operations;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {

src/TensorFlowNET.Core/Interfaces/IPackable.cs

@@ -4,8 +4,8 @@
 
 namespace Tensorflow
 {
-    public interface IPackable
+    public interface IPackable<T>
     {
-        void Pack(object[] sequences);
+        T Pack(object[] sequences);
     }
 }

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

@@ -139,14 +139,14 @@ protected override void build(TensorShape input_shape)
             built = true;
         }
 
-        protected override Tensor call(Tensor inputs, Tensor training = null)
+        protected override (Tensor, Tensor) call(Tensor inputs, Tensor training = null)
         {
             Tensor outputs = null;
 
             if (fused)
             {
                 outputs = _fused_batch_norm(inputs, training: training);
-                return outputs;
+                return (outputs, outputs);
             }
 
             throw new NotImplementedException("BatchNormalization call");

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

@@ -108,7 +108,7 @@ protected override void build(TensorShape input_shape)
             built = true;
         }
 
-        protected override Tensor call(Tensor inputs, Tensor training = null)
+        protected override (Tensor, Tensor) call(Tensor inputs, Tensor training = null)
         {
             var outputs = _convolution_op.__call__(inputs, kernel);
             if (use_bias)
@@ -124,9 +124,9 @@ protected override Tensor call(Tensor inputs, Tensor training = null)
             }
 
             if (activation != null)
-                return activation.Activate(outputs);
+                outputs = activation.Activate(outputs);
 
-            return outputs;
+            return (outputs, outputs);
         }
     }
 }

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

@@ -72,7 +72,7 @@ protected override void build(TensorShape input_shape)
             built = true;
         }
 
-        protected override Tensor call(Tensor inputs, Tensor training = null)
+        protected override (Tensor, Tensor) call(Tensor inputs, Tensor training = null)
         {
             Tensor outputs = null;
             var rank = inputs.rank;
@@ -88,9 +88,9 @@ protected override Tensor call(Tensor inputs, Tensor training = null)
             if (use_bias)
                 outputs = tf.nn.bias_add(outputs, bias);
             if (activation != null)
-                return activation.Activate(outputs);
+                outputs = activation.Activate(outputs);
 
-            return outputs;
+            return (outputs, outputs);
         }
     }
 }

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

@@ -50,14 +50,14 @@ protected override void build(TensorShape input_shape)
             built = true;
         }
 
-        protected override Tensor call(Tensor inputs, Tensor training = null)
+        protected override (Tensor, Tensor) call(Tensor inputs, Tensor training = null)
         {
             var dtype = inputs.dtype;
             if (dtype != tf.int32 && dtype != tf.int64)
                 inputs = math_ops.cast(inputs, tf.int32);
 
             var @out = embedding_ops.embedding_lookup(embeddings, inputs);
-            return @out;
+            return (@out, @out);
         }
     }
 }