tf.nn.moments

TensorFlow.NET.sln

@@ -15,6 +15,8 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Visualization
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "KerasNET.Core", "..\Keras.NET\src\KerasNET.Core\KerasNET.Core.csproj", "{E2F0C39C-D706-4CF5-AE00-81FB447F949D}"
 EndProject
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "NumSharp.Core", "..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj", "{62360571-D1F7-473C-B81F-F03CA59E37DD}"
+EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -45,6 +47,10 @@ Global
 		{E2F0C39C-D706-4CF5-AE00-81FB447F949D}.Debug|Any CPU.Build.0 = Debug|Any CPU
 		{E2F0C39C-D706-4CF5-AE00-81FB447F949D}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{E2F0C39C-D706-4CF5-AE00-81FB447F949D}.Release|Any CPU.Build.0 = Release|Any CPU
+		{62360571-D1F7-473C-B81F-F03CA59E37DD}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{62360571-D1F7-473C-B81F-F03CA59E37DD}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{62360571-D1F7-473C-B81F-F03CA59E37DD}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{62360571-D1F7-473C-B81F-F03CA59E37DD}.Release|Any CPU.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

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

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    public static partial class tf
+    {
+        public static nn_impl nn => new nn_impl();
+    }
+}

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

@@ -23,6 +23,17 @@ namespace Tensorflow
                 return x;
             });
         }
+        /// <summary>
+        /// 
+        /// </summary>
+        /// <param name="input_tensor"></param>
+        /// <param name="axes"></param>
+        /// <param name="keepdims"></param>
+        /// <param name="name"></param>
+        public static void reduce_mean(Tensor input_tensor, int[] axes = null, bool keepdims = false, string name = null)
+        {
+
+        }
 
         /// <summary>
         /// Helper function for reduction ops.

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

@@ -0,0 +1,32 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    public class nn_impl : Python
+    {
+        /// <summary>
+        /// Calculate the mean and variance of `x`
+        /// </summary>
+        /// <param name="x"></param>
+        /// <param name="axes"></param>
+        /// <param name="name"></param>
+        /// <param name="keep_dims"></param>
+        /// <returns></returns>
+        public (Tensor, Tensor) moments(Tensor x, 
+            int[] axes,
+            string name = null,
+            bool keep_dims = false)
+        {
+            with<ops.name_scope>(new ops.name_scope(name, "moments", new { x, axes }), scope =>
+            {
+                var y = math_ops.cast(x, TF_DataType.TF_FLOAT);
+                // mean = math_ops.reduce_mean(y, axes, keepdims = True, name = "mean")
+
+            });
+
+            throw new NotImplementedException("");
+        }
+    }
+}

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -55,4 +55,8 @@ Docs: https://tensorflownet.readthedocs.io</Description>
     <Folder Include="APIs\Keras\" />
   </ItemGroup>
 
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
+  </ItemGroup>
+
 </Project>

test/TensorFlowNET.Examples/NaiveBayesClassifier.cs

@@ -2,6 +2,8 @@
 using System.Collections.Generic;
 using System.Text;
 using Tensorflow;
+using NumSharp.Core;
+using System.Linq;
 
 namespace TensorFlowNET.Examples
 {
@@ -9,10 +11,28 @@ namespace TensorFlowNET.Examples
     /// https://github.com/nicolov/naive_bayes_tensorflow
     /// </summary>
     public class NaiveBayesClassifier : Python, IExample
-    {
+    { 
         public void Run()
         {
-            throw new NotImplementedException();
+           // t/f.nn.moments()
+        }
+
+        public void fit(NDArray X, NDArray y)
+        {
+            // separate training points by class
+            // shape : nb_class * nb_samples * nb_features
+            NDArray unique_y = y.unique<long>();
+            NDArray points_by_class = np.array(y.Data<long>().Where(ys => unique_y.Data<long>().Contains(ys)));
+
+            foreach (long cls in unique_y)
+            {
+
+            }
+
+
+            // estimate mean and variance for each class / feature
+            // shape : nb_classes * nb_features
+            
         }
     }
 }

test/TensorFlowNET.Examples/TensorFlowNET.Examples.csproj

@@ -12,6 +12,7 @@
 
   <ItemGroup>
     <ProjectReference Include="..\..\..\Keras.NET\src\KerasNET.Core\KerasNET.Core.csproj" />
+    <ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
     <ProjectReference Include="..\..\src\TensorFlowNET.Core\TensorFlowNET.Core.csproj" />
     <ProjectReference Include="..\..\src\TensorFlowNET.Utility\TensorFlowNET.Utility.csproj" />
   </ItemGroup>