Gradient function for Conv2D

src/TensorFlowNET.Core/Gradients/nn_grad.cs

@@ -97,6 +97,50 @@ namespace Tensorflow.Gradients
             };
         }
 
+        /// <summary>
+        /// Gradient function for Conv2D.
+        /// </summary>
+        /// <param name="op"></param>
+        /// <param name="grads"></param>
+        /// <returns></returns>
+        [RegisterGradient("Conv2D")]
+        public static Tensor[] _Conv2DGrad(Operation op, Tensor[] grads)
+        {
+            var dilations = op.get_attr("dilations");
+            var strides = op.get_attr("strides");
+            var padding = op.get_attr("padding");
+            var explicit_paddings = op.get_attr("explicit_paddings");
+            var use_cudnn_on_gpu = op.get_attr("use_cudnn_on_gpu");
+            var data_format = op.get_attr("data_format");
+            var shape = gen_array_ops.shape_n(new Tensor[] { op.inputs[0], op.inputs[1] });
+            
+            return new Tensor[]
+            {
+                gen_nn_ops.conv2d_backprop_input(new Conv2dParams
+                {
+                    InputSizes = shape[0],
+                    Filter = op.inputs[1],
+                    Dilations = dilations == null ? null : dilations as int[],
+                    Strides = strides == null ? null : strides as int[],
+                    Padding = padding.ToString(),
+                    ExplicitPaddings = explicit_paddings == null ? null : explicit_paddings as int[],
+                    UseCudnnOnGpu = (bool)use_cudnn_on_gpu,
+                    DataFormat = data_format.ToString()
+                }),
+                gen_nn_ops.conv2d_backprop_filter(new Conv2dParams
+                {
+                    Input = op.inputs[0],
+                    FilterSizes = shape[1],
+                    Dilations = dilations == null ? null : dilations as int[],
+                    Strides = strides == null ? null : strides as int[],
+                    Padding = padding.ToString(),
+                    ExplicitPaddings = explicit_paddings == null ? null : explicit_paddings as int[],
+                    UseCudnnOnGpu = (bool)use_cudnn_on_gpu,
+                    DataFormat = data_format.ToString()
+                })
+            };
+        }
+
         private static bool IsZero(Tensor g)
         {
             if (new string[] { "ZerosLike", "Zeros" }.Contains(g.op.type))

src/TensorFlowNET.Core/Operations/NnOps/Conv2dParams.cs

@@ -22,11 +22,27 @@ namespace Tensorflow.Operations
         /// </summary>
         public Tensor Input { get; set; }
 
+        /// <summary>
+        /// An integer vector representing the shape of `input`
+        /// </summary>
+        public Tensor InputSizes { get; set; }
+
         /// <summary>
         /// A 4-D tensor of shape
         /// </summary>
         public Tensor Filter { get; set; }
 
+        /// <summary>
+        /// An integer vector representing the tensor shape of `filter`
+        /// </summary>
+        public Tensor FilterSizes { get; set; }
+
+        /// <summary>
+        /// A `Tensor`. Must have the same type as `filter`.
+        /// 4-D with shape `[batch, out_height, out_width, out_channels]`.
+        /// </summary>
+        public Tensor OutBackProp { get; set; }
+
         /// <summary>
         /// The stride of the sliding window for each
         /// dimension of `input`. The dimension order is determined by the value of

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

@@ -43,6 +43,52 @@ namespace Tensorflow.Operations
             });
 
             return _op.outputs[0];
+        }
+
+        /// <summary>
+        /// Computes the gradients of convolution with respect to the filter.
+        /// </summary>
+        /// <param name="parameters"></param>
+        /// <returns></returns>
+        public static Tensor conv2d_backprop_filter(Conv2dParams parameters)
+        {
+            var _op = _op_def_lib._apply_op_helper("Conv2DBackpropFilter", name: parameters.Name, args: new
+            {
+                input = parameters.Input,
+                filter_sizes = parameters.FilterSizes,
+                out_backprop = parameters.OutBackProp,
+                strides = parameters.Strides,
+                padding = parameters.Padding,
+                use_cudnn_on_gpu = parameters.UseCudnnOnGpu,
+                explicit_paddings = parameters.ExplicitPaddings,
+                data_format = parameters.DataFormat,
+                dilations = parameters.Dilations
+            });
+
+            return _op.outputs[0];
+        }
+
+        /// <summary>
+        /// Computes the gradients of convolution with respect to the input.
+        /// </summary>
+        /// <param name="parameters"></param>
+        /// <returns></returns>
+        public static Tensor conv2d_backprop_input(Conv2dParams parameters)
+        {
+            var _op = _op_def_lib._apply_op_helper("Conv2DBackpropInput", name: parameters.Name, args: new
+            {
+                input_sizes = parameters.InputSizes,
+                filter = parameters.Filter,
+                out_backprop = parameters.OutBackProp,
+                strides = parameters.Strides,
+                padding = parameters.Padding,
+                use_cudnn_on_gpu = parameters.UseCudnnOnGpu,
+                explicit_paddings = parameters.ExplicitPaddings,
+                data_format = parameters.DataFormat,
+                dilations = parameters.Dilations
+            });
+
+            return _op.outputs[0];
         }
 
         public static Tensor bias_add(Tensor value,

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -252,6 +252,19 @@ namespace Tensorflow
             return _op.outputs[0];
         }
 
+        /// <summary>
+        /// Returns shape of tensors.
+        /// </summary>
+        /// <param name="input"></param>
+        /// <param name="out_type"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public static Tensor[] shape_n(Tensor[] input, TF_DataType out_type = TF_DataType.TF_INT32, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("ShapeN", name, new { input, out_type });
+            return _op.outputs;
+        }
+
         public static Tensor size(Tensor input, TF_DataType out_type = TF_DataType.TF_INT32, string name = null)
         {
             var _op = _op_def_lib._apply_op_helper("Size", name, new { input, out_type });

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -20,8 +20,9 @@ Docs: https://tensorflownet.readthedocs.io</Description>
     <AssemblyVersion>0.8.1.0</AssemblyVersion>
     <PackageReleaseNotes>Changes since v0.8:
 
-1. Removed global static graph instance.
-2. Provide custom gradient function.</PackageReleaseNotes>
+1. Remove global static graph instance.
+2. Provide custom gradient function.
+3. Add gradient function for Conv2D.</PackageReleaseNotes>
     <LangVersion>7.2</LangVersion>
     <FileVersion>0.8.1.0</FileVersion>
   </PropertyGroup>