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add tf.convert_to_tensor
1 parent cc0b994 commit dc8a8cf

9 files changed

Lines changed: 55 additions & 31 deletions

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‎TensorFlow.NET.sln‎

Lines changed: 0 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -9,8 +9,6 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Examples", "t
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Core", "src\TensorFlowNET.Core\TensorFlowNET.Core.csproj", "{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}"
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "NumSharp.Core", "..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj", "{DE97EAD7-B92C-4112-9690-91C40A97179E}"
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EndProject
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Global
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
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Debug|Any CPU = Debug|Any CPU
@@ -29,10 +27,6 @@ Global
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{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|Any CPU.Build.0 = Release|Any CPU
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{DE97EAD7-B92C-4112-9690-91C40A97179E}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{DE97EAD7-B92C-4112-9690-91C40A97179E}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{DE97EAD7-B92C-4112-9690-91C40A97179E}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{DE97EAD7-B92C-4112-9690-91C40A97179E}.Release|Any CPU.Build.0 = Release|Any CPU
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EndGlobalSection
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GlobalSection(SolutionProperties) = preSolution
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HideSolutionNode = FALSE

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

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,13 @@
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using NumSharp;
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using System;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow
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{
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public static partial class tf
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{
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public static Tensor convert_to_tensor(object value,
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string name = null) => ops.convert_to_tensor(value, name: name);
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}
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}

‎src/TensorFlowNET.Core/Python.cs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -29,7 +29,7 @@ protected IEnumerable<int> range(int end)
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protected IEnumerable<int> range(int start, int end)
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{
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return Enumerable.Range(start, end);
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return Enumerable.Range(start, end - start);
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}
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public static T New<T>(object args) where T : IPyClass

‎src/TensorFlowNET.Core/TensorFlowNET.Core.csproj‎

Lines changed: 3 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -4,10 +4,10 @@
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<TargetFramework>netstandard2.0</TargetFramework>
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<AssemblyName>TensorFlow.NET</AssemblyName>
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<RootNamespace>Tensorflow</RootNamespace>
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<Version>0.6.1-alpha</Version>
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<Version>0.6.1</Version>
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<Authors>Haiping Chen</Authors>
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<Company>SciSharp STACK</Company>
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<GeneratePackageOnBuild>true</GeneratePackageOnBuild>
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<GeneratePackageOnBuild>false</GeneratePackageOnBuild>
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<Copyright>Apache 2.0</Copyright>
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<RepositoryUrl>https://github.com/SciSharp/TensorFlow.NET</RepositoryUrl>
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<RepositoryType>git</RepositoryType>
@@ -44,7 +44,7 @@ More math/ linalg APIs.</PackageReleaseNotes>
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<ItemGroup>
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<PackageReference Include="Google.Protobuf" Version="3.7.0" />
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<PackageReference Include="NumSharp" Version="0.9.0" />
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<PackageReference Include="NumSharp" Version="0.10.0-alpha" />
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</ItemGroup>
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<ItemGroup>
@@ -57,8 +57,4 @@ More math/ linalg APIs.</PackageReleaseNotes>
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<Folder Include="Keras\Initializers\" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
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</ItemGroup>
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</Project>

‎test/TensorFlowNET.Examples/KMeansClustering.cs‎

Lines changed: 31 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,8 @@
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using NumSharp;
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using System;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Linq;
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using System.Text;
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using Tensorflow;
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using Tensorflow.Clustering;
@@ -26,7 +28,7 @@ public class KMeansClustering : Python, IExample
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Datasets mnist;
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NDArray full_data_x;
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int num_steps = 50; // Total steps to train
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int num_steps = 10; // Total steps to train
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int k = 25; // The number of clusters
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int num_classes = 10; // The 10 digits
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int num_features = 784; // Each image is 28x28 pixels
@@ -63,22 +65,43 @@ public bool Run()
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// Training
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NDArray result = null;
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foreach(var i in range(1, num_steps + 1))
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var sw = new Stopwatch();
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foreach (var i in range(1, num_steps + 1))
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{
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sw.Start();
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result = sess.run(new ITensorOrOperation[] { train_op, avg_distance, cluster_idx }, new FeedItem(X, full_data_x));
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if (i % 2 == 0 || i == 1)
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print($"Step {i}, Avg Distance: {result[1]}");
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sw.Stop();
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if (i % 5 == 0 || i == 1)
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print($"Step {i}, Avg Distance: {result[1]} Elapse: {sw.ElapsedMilliseconds}ms");
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sw.Reset();
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}
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var idx = result[2];
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var idx = result[2].Data<int>();
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// Assign a label to each centroid
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// Count total number of labels per centroid, using the label of each training
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// sample to their closest centroid (given by 'idx')
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var counts = np.zeros(k, num_classes);
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foreach (var i in range(idx.len))
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counts[idx[i]] += mnist.train.labels[i];
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var counts = np.zeros((k, num_classes), np.float32);
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sw.Start();
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foreach (var i in range(idx.Length))
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{
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var x = mnist.train.labels[i];
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counts[idx[i]] += x;
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}
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sw.Stop();
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print($"Assign a label to each centroid took {sw.ElapsedMilliseconds}ms");
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// Assign the most frequent label to the centroid
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var labels_map_array = np.argmax(counts, 1);
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var labels_map = tf.convert_to_tensor(labels_map_array);
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// Evaluation ops
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// Lookup: centroid_id -> label
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});
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return false;

‎test/TensorFlowNET.Examples/LogisticRegression.cs‎

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@@ -88,7 +88,7 @@ public bool Run()
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// Display logs per epoch step
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if ((epoch + 1) % display_step == 0)
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print($"Epoch: {(epoch + 1).ToString("D4")} cost= {avg_cost.ToString("G9")} elapse= {sw.ElapsedMilliseconds}ms");
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print($"Epoch: {(epoch + 1).ToString("D4")} Cost: {avg_cost.ToString("G9")} Elapse: {sw.ElapsedMilliseconds}ms");
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sw.Reset();
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}

‎test/TensorFlowNET.Examples/NearestNeighbor.cs‎

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@@ -51,9 +51,9 @@ public bool Run()
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long nn_index = sess.run(pred, new FeedItem(xtr, Xtr), new FeedItem(xte, Xte[i]));
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// Get nearest neighbor class label and compare it to its true label
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int index = (int)nn_index;
54-
print($"Test {i} Prediction: {np.argmax(Ytr[(NDArray)index])} True Class: {np.argmax(Yte[i] as NDArray)}");
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print($"Test {i} Prediction: {np.argmax(Ytr[index])} True Class: {np.argmax(Yte[i])}");
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// Calculate accuracy
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if (np.argmax(Ytr[(NDArray)index]) == np.argmax(Yte[i] as NDArray))
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if ((int)np.argmax(Ytr[index]) == (int)np.argmax(Yte[i]))
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accuracy += 1f/ Xte.shape[0];
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}
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‎test/TensorFlowNET.Examples/TensorFlowNET.Examples.csproj‎

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@@ -2,19 +2,18 @@
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFramework>netcoreapp2.1</TargetFramework>
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<TargetFramework>netcoreapp2.2</TargetFramework>
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<GeneratePackageOnBuild>false</GeneratePackageOnBuild>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Colorful.Console" Version="1.2.9" />
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<PackageReference Include="Newtonsoft.Json" Version="12.0.1" />
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<PackageReference Include="Newtonsoft.Json" Version="12.0.2" />
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<PackageReference Include="SharpZipLib" Version="1.1.0" />
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<PackageReference Include="System.Drawing.Common" Version="4.5.1" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
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<ProjectReference Include="..\..\src\TensorFlowNET.Core\TensorFlowNET.Core.csproj" />
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</ItemGroup>
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‎test/TensorFlowNET.UnitTest/TensorFlowNET.UnitTest.csproj‎

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<Project Sdk="Microsoft.NET.Sdk">
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFramework>netcoreapp2.1</TargetFramework>
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<TargetFramework>netcoreapp2.2</TargetFramework>
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<IsPackable>false</IsPackable>
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</PropertyGroup>
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
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<ProjectReference Include="..\..\src\TensorFlowNET.Core\TensorFlowNET.Core.csproj" />
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<ProjectReference Include="..\TensorFlowNET.Examples\TensorFlowNET.Examples.csproj" />
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</ItemGroup>

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