Merge branch 'master' of https://github.com/SciSharp/TensorFlow.NET

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

@@ -31,7 +31,7 @@ namespace Tensorflow
             public Optimizer AdamOptimizer(float learning_rate, string name = "Adam") 
                 => new AdamOptimizer(learning_rate, name: name);
 
-            public object ExponentialMovingAverage(float decay)
+            public ExponentialMovingAverage ExponentialMovingAverage(float decay)
                 => new ExponentialMovingAverage(decay);
 
             public Saver Saver(VariableV1[] var_list = null) => new Saver(var_list: var_list);

src/TensorFlowNET.Core/Operations/Initializers/RandomNormal.cs

@@ -40,12 +40,20 @@ namespace Tensorflow.Operations.Initializers
 
         public Tensor call(TensorShape shape, TF_DataType dtype = TF_DataType.DtInvalid)
         {
-            throw new NotImplementedException();
+            if (dtype == TF_DataType.DtInvalid)
+                dtype = this.dtype;
+            return random_ops.random_normal(shape, mean, stddev, dtype, seed: seed);
         }
 
         public object get_config()
         {
-            throw new NotImplementedException();
+            return new
+            {
+                mean,
+                stddev,
+                seed,
+                dtype
+            };
         }
     }
 }

src/TensorFlowNET.Core/Operations/array_ops.py.cs

@@ -260,8 +260,7 @@ namespace Tensorflow
             return tf_with(ops.name_scope(name, "ones", new { dims }), scope =>
             {
                 name = scope;
-                var shape = ops.convert_to_tensor(dims, dtype: TF_DataType.TF_INT32);
-                var output = gen_array_ops.fill(shape, constant_op.constant(1.0f, dtype: dtype), name: name);
+                var output = _constant_if_small(1, dims, dtype, name);
                 return output;
             });
         }

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -141,7 +141,7 @@ namespace Tensorflow
         {
             var _op = _op_def_lib._apply_op_helper("Add", name, args: new { x, y });
 
-            return _op.outputs[0];
+            return _op.output;
         }
 
         public static Tensor atan(Tensor x, string name = null)

src/TensorFlowNET.Core/Operations/gen_random_ops.py.cs

@@ -40,7 +40,7 @@ namespace Tensorflow
                 name: name,
                 args: new { shape, dtype, seed, seed2 });
 
-            return _op.outputs[0];
+            return _op.output;
         }
 
         /// <summary>

src/TensorFlowNET.Core/Operations/random_ops.py.cs

@@ -39,9 +39,10 @@ namespace Tensorflow
         {
             return tf_with(ops.name_scope(name, "random_normal", new { shape, mean, stddev }), scope =>
             {
+                name = scope;
                 var shape_tensor = _ShapeTensor(shape);
                 var mean_tensor = ops.convert_to_tensor(mean, dtype: dtype, name: "mean");
-                var stddev_tensor = ops.convert_to_tensor(stddev, dtype: dtype, name = "stddev");
+                var stddev_tensor = ops.convert_to_tensor(stddev, dtype: dtype, name: "stddev");
                 var (seed1, seed2) = random_seed.get_seed(seed);
                 var rnd = gen_random_ops.random_standard_normal(shape_tensor, dtype: dtype, seed: seed1, seed2: seed2);
                 var mul = rnd * stddev_tensor;

src/TensorFlowNET.Core/Tensors/TensorShape.cs

@@ -143,6 +143,11 @@ namespace Tensorflow
             }
         }
 
+        public override string ToString()
+        {
+            return shape.ToString();
+        }
+
         public static implicit operator TensorShape(Shape shape) => new TensorShape((int[]) shape.Dimensions.Clone());
         public static implicit operator Shape(TensorShape shape) => new Shape((int[]) shape.dims.Clone());
         

src/TensorFlowNET.Core/Train/ExponentialMovingAverage.cs

@@ -1,6 +1,8 @@
 using System;
 using System.Collections.Generic;
+using System.Linq;
 using System.Text;
+using static Tensorflow.Binding;
 
 namespace Tensorflow.Train
 {
@@ -11,6 +13,7 @@ namespace Tensorflow.Train
         bool _zero_debias;
         string _name;
         public string name => _name;
+        List<VariableV1> _averages;
 
         public ExponentialMovingAverage(float decay, int? num_updates = null, bool zero_debias = false,
             string name = "ExponentialMovingAverage")
@@ -19,6 +22,7 @@ namespace Tensorflow.Train
             _num_updates = num_updates;
             _zero_debias = zero_debias;
             _name = name;
+            _averages = new List<VariableV1>();
         }
 
         /// <summary>
@@ -26,11 +30,23 @@ namespace Tensorflow.Train
         /// </summary>
         /// <param name="var_list"></param>
         /// <returns></returns>
-        public Operation apply(VariableV1[] var_list = null)
+        public Operation apply(RefVariable[] var_list = null)
         {
-            throw new NotImplementedException("");
-        }
+            if (var_list == null)
+                var_list = variables.trainable_variables() as RefVariable[];
 
+            foreach(var var in var_list)
+            {
+                if (!_averages.Contains(var))
+                {
+                    ops.init_scope();
+                    var slot = new SlotCreator();
+                    var.initialized_value();
+                    // var avg = slot.create_zeros_slot
+                }
+            }
 
+            throw new NotImplementedException("");
+        }
     }
 }

src/TensorFlowNET.Core/Variables/RefVariable.cs

@@ -308,5 +308,28 @@ namespace Tensorflow
         {
             throw new NotImplementedException();
         }
+
+        /// <summary>
+        /// Returns the value of this variable, read in the current context.
+        /// </summary>
+        /// <returns></returns>
+        private ITensorOrOperation read_value()
+        {
+            return array_ops.identity(_variable, name: "read");
+        }
+
+        public Tensor is_variable_initialized(RefVariable variable)
+        {
+            return state_ops.is_variable_initialized(variable);
+        }
+
+        public Tensor initialized_value()
+        {
+            ops.init_scope();
+            throw new NotImplementedException("");
+            /*return control_flow_ops.cond(is_variable_initialized(this),
+                                   read_value,
+                                   () => initial_value);*/
+        }
     }
 }

src/TensorFlowNET.Core/Variables/gen_state_ops.py.cs

@@ -14,6 +14,7 @@
    limitations under the License.
 ******************************************************************************/
 
+using System;
 using System.Collections.Generic;
 using Tensorflow.Eager;
 
@@ -145,5 +146,10 @@ namespace Tensorflow
             var _op = _op_def_lib._apply_op_helper("ScatterAdd", name: name, args: new { @ref, indices, updates, use_locking });
             return _op.outputs[0];
         }
+
+        public static Tensor is_variable_initialized(RefVariable @ref, string name = null)
+        {
+            throw new NotImplementedException("");
+        }
     }
 }

src/TensorFlowNET.Core/Variables/state_ops.cs

@@ -106,5 +106,13 @@ namespace Tensorflow
 
             throw new NotImplementedException("scatter_add");
         }
+
+        public static Tensor is_variable_initialized(RefVariable @ref, string name = null)
+        {
+            if (@ref.dtype.is_ref_dtype())
+                return gen_state_ops.is_variable_initialized(@ref: @ref, name: name);
+            throw new NotImplementedException("");
+            //return @ref.is_initialized(name: name);
+        }
     }
 }

test/TensorFlowNET.Examples/ImageProcessing/YOLO/Main.cs

@@ -94,6 +94,11 @@ namespace TensorFlowNET.Examples.ImageProcessing.YOLO
                 model = new YOLOv3(cfg, input_data, trainable);
             });
 
+            tf_with(tf.name_scope("define_weight_decay"), scope =>
+            {
+                var moving_ave = tf.train.ExponentialMovingAverage(moving_ave_decay).apply((RefVariable[])tf.trainable_variables());
+            });
+
             return graph;
         }
 

test/TensorFlowNET.Examples/ImageProcessing/YOLO/YOLOv3.cs

@@ -37,6 +37,21 @@ namespace TensorFlowNET.Examples.ImageProcessing.YOLO
             upsample_method = cfg.YOLO.UPSAMPLE_METHOD;
 
             (conv_lbbox, conv_mbbox, conv_sbbox) = __build_nework(input_data);
+
+            tf_with(tf.variable_scope("pred_sbbox"), scope =>
+            {
+                // pred_sbbox = decode(conv_sbbox, anchors[0], strides[0]);
+            });
+
+            tf_with(tf.variable_scope("pred_mbbox"), scope =>
+            {
+                // pred_sbbox = decode(conv_sbbox, anchors[0], strides[0]);
+            });
+
+            tf_with(tf.variable_scope("pred_lbbox"), scope =>
+            {
+                // pred_sbbox = decode(conv_sbbox, anchors[0], strides[0]);
+            });
         }
 
         private (Tensor, Tensor, Tensor) __build_nework(Tensor input_data)

test/TensorFlowNET.UnitTest/ImageTest.cs

@@ -8,6 +8,9 @@ using static Tensorflow.Binding;
 
 namespace TensorFlowNET.UnitTest
 {
+    /// <summary>
+    /// Find more examples in https://www.programcreek.com/python/example/90444/tensorflow.read_file
+    /// </summary>
     [TestClass]
     public class ImageTest
     {

test/TensorFlowNET.UnitTest/NameScopeTest.cs

@@ -69,9 +69,7 @@ namespace TensorFlowNET.UnitTest
                 Assert.AreEqual("scope1", g._name_stack);
                 var const3 = tf.constant(2.0);
                 Assert.AreEqual("scope1/Const_1:0", const3.name);
-            }
-
-            ;
+            };
 
             g.Dispose();