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Oceania2018Oceania2018
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Merge pull request SciSharp#201 from PppBr/master
NB classifier running
2 parents 3593978 + c15a1ea commit c9e58d8

9 files changed

Lines changed: 31 additions & 13 deletions

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‎TensorFlow.NET.sln‎

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@@ -11,6 +11,8 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Core", "src\T
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Visualization", "src\TensorFlowNET.Visualization\TensorFlowNET.Visualization.csproj", "{0254BFF9-453C-4FE0-9609-3644559A79CE}"
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "NumSharp.Core", "..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj", "{647E7590-9B50-48D9-B9E2-47743E9EAA56}"
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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
@@ -33,6 +35,10 @@ Global
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{0254BFF9-453C-4FE0-9609-3644559A79CE}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{0254BFF9-453C-4FE0-9609-3644559A79CE}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{0254BFF9-453C-4FE0-9609-3644559A79CE}.Release|Any CPU.Build.0 = Release|Any CPU
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{647E7590-9B50-48D9-B9E2-47743E9EAA56}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{647E7590-9B50-48D9-B9E2-47743E9EAA56}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{647E7590-9B50-48D9-B9E2-47743E9EAA56}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{647E7590-9B50-48D9-B9E2-47743E9EAA56}.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.math.cs‎

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@@ -252,6 +252,11 @@ public static Tensor reduce_sum(Tensor input, int? axis = null, int? reduction_i
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return math_ops.reduce_sum(input);
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}
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public static Tensor reduce_sum(Tensor input, int axis, int? reduction_indices = null)
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{
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return math_ops.reduce_sum(input, axis);
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}
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public static Tensor reduce_mean(Tensor input_tensor, int[] axis = null, bool keepdims = false, string name = null, int? reduction_indices = null)
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=> math_ops.reduce_mean(input_tensor, axis: axis, keepdims: keepdims, name: name, reduction_indices: reduction_indices);
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‎src/TensorFlowNET.Core/Operations/Distributions/normal.py.cs‎

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@@ -83,7 +83,7 @@ protected override Tensor _log_prob(Tensor x)
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{
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var log_prob = _log_unnormalized_prob(_z(x));
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var log_norm = _log_normalization();
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return log_prob - log_norm;
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return tf.sub(log_prob, log_norm);
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}
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private Tensor _log_unnormalized_prob (Tensor x)

‎src/TensorFlowNET.Core/Operations/math_ops.cs‎

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@@ -211,14 +211,14 @@ public static Tensor reduce_all(Tensor input_tensor, int[] axis = null, bool kee
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/// <returns> The reduced tensor.</returns>
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public static Tensor reduce_logsumexp(Tensor input_tensor, int[] axis = null, bool keepdims = false, string name = null)
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{
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with(ops.name_scope(name, "ReduceLogSumExp", new { input_tensor }), scope =>
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return with(ops.name_scope(name, "ReduceLogSumExp", new { input_tensor }), scope =>
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{
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var raw_max = reduce_max(input_tensor, axis, true);
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var my_max = array_ops.stop_gradient(array_ops.where(gen_math_ops.is_finite(raw_max), raw_max, array_ops.zeros_like(raw_max)));
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var result = gen_math_ops.log(
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reduce_sum(
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gen_math_ops.exp(gen_math_ops.sub(input_tensor, my_max)),
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new Tensor(axis),
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axis[0],
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keepdims));
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if (!keepdims)
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{
@@ -227,7 +227,6 @@ public static Tensor reduce_logsumexp(Tensor input_tensor, int[] axis = null, bo
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result = gen_math_ops.add(result, my_max);
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return _may_reduce_to_scalar(keepdims, axis, result);
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});
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return null;
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}
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public static Tensor reduce_max(Tensor input_tensor, int[] axis = null, bool keepdims = false, string name = null)
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if (!common_shapes.has_fully_defined_shape(output) &&
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!keepdims &&
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axis == null)
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// We want set_shape to be reflected in the C API graph for when we run it.
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output.shape = new long[0];
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return output;
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}
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private static Tensor _may_reduce_to_scalar(bool keepdims, int[] axis, Tensor output)
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{
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output.shape = new long[0];
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if (!common_shapes.has_fully_defined_shape(output) &&
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!keepdims &&
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axis == null)
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output.shape = new long[0];
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return output;
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}
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if (axis != null)
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{
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// should return axis. or check before.
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return null;
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return ops.convert_to_tensor(axis, TF_DataType.TF_INT32);
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}
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else
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{

‎src/TensorFlowNET.Core/TensorFlowNET.Core.csproj‎

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@@ -58,4 +58,8 @@ Bug memory leak issue when allocating Tensor.</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/ImageRecognition.cs‎

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@@ -12,7 +12,7 @@ namespace TensorFlowNET.Examples
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{
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public class ImageRecognition : Python, IExample
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{
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public int Priority => 6;
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public int Priority => 7;
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public bool Enabled => true;
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public string Name => "Image Recognition";
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‎test/TensorFlowNET.Examples/KMeansClustering.cs‎

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@@ -15,8 +15,8 @@ namespace TensorFlowNET.Examples
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/// </summary>
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public class KMeansClustering : Python, IExample
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{
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public int Priority => 7;
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public bool Enabled => true;
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public int Priority => 8;
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public bool Enabled => false;
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public string Name => "K-means Clustering";
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Datasets mnist;

‎test/TensorFlowNET.Examples/NaiveBayesClassifier.cs‎

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@@ -12,7 +12,7 @@ namespace TensorFlowNET.Examples
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/// </summary>
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public class NaiveBayesClassifier : Python, IExample
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{
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public int Priority => 100;
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public int Priority => 6;
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public bool Enabled => true;
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public string Name => "Naive Bayes Classifier";
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@@ -88,7 +88,7 @@ public bool Run()
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var s = tf.Session();
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if (xx.dtype == typeof(float))
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{
91-
var samples = np.vstack <float>(xx.ravel(), yy.ravel());
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var samples = np.hstack<float>(xx.ravel().reshape(-1,1), yy.ravel().reshape(-1,1));
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var Z = s.run(predict(samples));
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}
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@@ -179,7 +179,7 @@ public Tensor predict (NDArray X)
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var joint_likelihood = tf.add(ops.convert_to_tensor(priors, TF_DataType.TF_FLOAT), cond_probs);
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// normalize to get (log)-probabilities
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var norm_factor = tf.reduce_logsumexp(joint_likelihood, new int[] { 1 }, true);
182+
var norm_factor = tf.reduce_logsumexp(joint_likelihood, new int[] { 1 }, keepdims: true);
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var log_prob = joint_likelihood - norm_factor;
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// exp to get the actual probabilities
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return tf.exp(log_prob);

‎test/TensorFlowNET.Examples/TextClassification/TextClassificationWithMovieReviews.cs‎

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@@ -11,7 +11,7 @@ namespace TensorFlowNET.Examples
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{
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public class TextClassificationWithMovieReviews : Python, IExample
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{
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public int Priority => 7;
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public int Priority => 9;
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public bool Enabled => false;
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public string Name => "Movie Reviews";
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