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

Author: PppBr

README.md

@@ -150,6 +150,8 @@ Example runner will download all the required files like training data and model
 * [Named Entity Recognition](test/TensorFlowNET.Examples/TextProcess/NER)
 * [Transfer Learning for Image Classification in InceptionV3](test/TensorFlowNET.Examples/ImageProcess/RetrainImageClassifier.cs)
 
+More troubleshooting of running example refer [here](tensorflowlib/README.md).
+
 ### Contribute:
 
 Feel like contributing to one of the hottest projects in the Machine Learning field? Want to know how Tensorflow magically creates the computational graph? We appreciate every contribution however small. There are tasks for novices to experts alike, if everyone tackles only a small task the sum of contributions will be huge.

docs/_config.yml

@@ -0,0 +1 @@
+theme: jekyll-theme-cayman

graph/InceptionV3.meta

@@ -36,6 +36,16 @@ public static Tensor concat(IList<Tensor> values, int axis, string name = "conca
         public static Tensor expand_dims(Tensor input, int axis = -1, string name = null, int dim = -1)
             => array_ops.expand_dims(input, axis, name, dim);
 
+        /// <summary>
+        /// Creates a tensor filled with a scalar value.
+        /// </summary>
+        /// <param name="dims"></param>
+        /// <param name="value"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public static Tensor fill<T>(Tensor dims, T value, string name = null)
+            => gen_array_ops.fill(dims, value, name: name);
+
         /// <summary>
         /// Return the elements, either from `x` or `y`, depending on the `condition`.
         /// </summary>

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

@@ -6,7 +6,7 @@ namespace Tensorflow
 {
     public static partial class tf
     {
-        public static object gradients(Tensor[] ys,
+        public static Tensor[] gradients(Tensor[] ys,
             Tensor[] xs,
             Tensor[] grad_ys = null,
             string name = "gradients",
@@ -15,7 +15,7 @@ public static object gradients(Tensor[] ys,
             int? aggregation_method = null,
             Tensor[] stop_gradients = null)
         {
-            return gradients_impl._GradientsHelper(ys, 
+            return gradients_util._GradientsHelper(ys, 
                 xs, 
                 grad_ys, 
                 name, 
@@ -33,13 +33,31 @@ public static Tensor[] gradients(Tensor ys,
             int? aggregation_method = null,
             Tensor[] stop_gradients = null)
         {
-            return gradients_impl._GradientsHelper(new Tensor[] { ys },
+            return gradients_util._GradientsHelper(new Tensor[] { ys },
                 xs,
                 grad_ys,
                 name,
                 colocate_gradients_with_ops,
                 gate_gradients,
                 stop_gradients: stop_gradients);
         }
+
+        public static Tensor[] gradients(Tensor ys,
+            Tensor xs,
+            Tensor[] grad_ys = null,
+            string name = "gradients",
+            bool colocate_gradients_with_ops = false,
+            bool gate_gradients = false,
+            int? aggregation_method = null,
+            Tensor[] stop_gradients = null)
+        {
+            return gradients_util._GradientsHelper(new Tensor[] { ys },
+                new Tensor[] { xs },
+                grad_ys,
+                name,
+                colocate_gradients_with_ops,
+                gate_gradients,
+                stop_gradients: stop_gradients);
+        }
     }
 }

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

@@ -142,6 +142,7 @@ public static Tensor dense(Tensor inputs,
 
                 var layer = new Dense(units, activation, 
                     use_bias: use_bias,
+                    bias_initializer: bias_initializer,
                     kernel_initializer: kernel_initializer);
 
                 return layer.apply(inputs);

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

@@ -257,6 +257,16 @@ public static Tensor multiply<Tx, Ty>(Tx x, Ty y)
         public static Tensor negative(Tensor x, string name = null)
             => gen_math_ops.neg(x, name);
 
+        /// <summary>
+        /// Divides x / y elementwise (using Python 2 division operator semantics).
+        /// </summary>
+        /// <param name="x"></param>
+        /// <param name="y"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public static Tensor div(Tensor x, Tensor y, string name = null)
+            => math_ops.div(x, y, name: name);
+
         public static Tensor divide<T>(Tensor x, T[] y, string name = null) where T : struct
             => x / ops.convert_to_tensor(y, dtype: x.dtype.as_base_dtype(), name: "y");
 

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

@@ -23,6 +23,8 @@ public static RefVariable get_variable(string name,
             TF_DataType dtype = TF_DataType.DtInvalid,
             object initializer = null, // IInitializer or Tensor
             bool? trainable = null,
+            bool? use_resource = null,
+            bool validate_shape = true,
             VariableSynchronization synchronization = VariableSynchronization.Auto,
             VariableAggregation aggregation = VariableAggregation.None)
         {
@@ -32,6 +34,8 @@ public static RefVariable get_variable(string name,
                 name, 
                 shape: shape, 
                 dtype: dtype,
+                use_resource: use_resource,
+                validate_shape: validate_shape,
                 initializer: initializer,
                 trainable: trainable);
         }

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

@@ -0,0 +1,13 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Framework
+{
+    /// <summary>
+    /// Abstract base class for Tensor-like objects that are composed from Tensors.
+    /// </summary>
+    public abstract class CompositeTensor
+    {
+    }
+}

src/TensorFlowNET.Core/Framework/CompositeTensor.cs

@@ -0,0 +1,48 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Framework
+{
+    /// <summary>
+    /// A sparse representation of a set of tensor slices at given indices.
+    /// </summary>
+    public class IndexedSlices : CompositeTensor
+    {
+        Tensor _values;
+        public Tensor values => _values;
+        Tensor _indices;
+        public Tensor indices => _indices;
+        Tensor _dense_shape;
+        public Tensor dense_shape => _dense_shape;
+
+        public string name => _values.name;
+
+        public string device => _values.Device;
+
+        public Operation op => _values.op;
+
+        public TF_DataType dtype => _values.dtype;
+
+        public Graph graph => _values.graph;
+
+        public IndexedSlices(Tensor values, Tensor indices, Tensor dense_shape = null)
+        {
+            _values = values;
+            _indices = indices;
+            _dense_shape = dense_shape;
+
+            _values.Tag = this;
+        }
+
+        public static implicit operator Tensor(IndexedSlices indexedSlices)
+        {
+            return indexedSlices.values;
+        }
+
+        public static implicit operator IndexedSlices(Tensor tensor)
+        {
+            return tensor.Tag as IndexedSlices;
+        }
+    }
+}