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henonhenon
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minor changes in examples
1 parent 1ff31db commit ecc4923

4 files changed

Lines changed: 21 additions & 19 deletions

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‎test/TensorFlowNET.Examples/KMeansClustering.cs‎

Lines changed: 6 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -18,14 +18,15 @@ public class KMeansClustering : Python, IExample
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public int Priority => 8;
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public bool Enabled { get; set; } = true;
2020
public string Name => "K-means Clustering";
21-
public int DataSize = 5000;
22-
public int TestSize = 5000;
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public int BatchSize = 100;
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22+
public int? train_size = null;
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public int validation_size = 5000;
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public int? test_size = null;
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public int batch_size = 1024; // The number of samples per batch
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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 batch_size = 1024; // The number of samples per batch
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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
@@ -48,7 +49,7 @@ public bool Run()
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public void PrepareData()
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{
51-
mnist = MnistDataSet.read_data_sets("mnist", one_hot: true, validation_size: DataSize, test_size:TestSize);
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mnist = MnistDataSet.read_data_sets("mnist", one_hot: true, train_size: train_size, validation_size:validation_size, test_size:test_size);
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full_data_x = mnist.train.images;
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}
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}

‎test/TensorFlowNET.Examples/LinearRegression.cs‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -16,13 +16,13 @@ public class LinearRegression : Python, IExample
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public bool Enabled { get; set; } = true;
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public string Name => "Linear Regression";
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NumPyRandom rng = np.random;
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public int training_epochs = 1000;
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// Parameters
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float learning_rate = 0.01f;
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public int TrainingEpochs = 1000;
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int display_step = 50;
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25+
NumPyRandom rng = np.random;
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NDArray train_X, train_Y;
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int n_samples;
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@@ -62,7 +62,7 @@ public bool Run()
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sess.run(init);
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// Fit all training data
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for (int epoch = 0; epoch < TrainingEpochs; epoch++)
65+
for (int epoch = 0; epoch < training_epochs; epoch++)
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{
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foreach (var (x, y) in zip<float>(train_X, train_Y))
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{

‎test/TensorFlowNET.Examples/LogisticRegression.cs‎

Lines changed: 10 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -20,12 +20,13 @@ public class LogisticRegression : Python, IExample
2020
public bool Enabled { get; set; } = true;
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public string Name => "Logistic Regression";
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23+
public int training_epochs = 10;
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public int? train_size = null;
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public int validation_size = 5000;
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public int? test_size = null;
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public int batch_size = 100;
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private float learning_rate = 0.01f;
24-
public int TrainingEpochs = 10;
25-
public int? TrainSize = null;
26-
public int ValidationSize = 5000;
27-
public int? TestSize = null;
28-
public int BatchSize = 100;
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private int display_step = 1;
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3132
Datasets mnist;
@@ -60,14 +61,14 @@ public bool Run()
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sess.run(init);
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// Training cycle
63-
foreach (var epoch in range(TrainingEpochs))
64+
foreach (var epoch in range(training_epochs))
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{
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var avg_cost = 0.0f;
66-
var total_batch = mnist.train.num_examples / BatchSize;
67+
var total_batch = mnist.train.num_examples / batch_size;
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// Loop over all batches
6869
foreach (var i in range(total_batch))
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{
70-
var (batch_xs, batch_ys) = mnist.train.next_batch(BatchSize);
71+
var (batch_xs, batch_ys) = mnist.train.next_batch(batch_size);
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// Run optimization op (backprop) and cost op (to get loss value)
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var result = sess.run(new object[] { optimizer, cost },
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new FeedItem(x, batch_xs),
@@ -99,7 +100,7 @@ public bool Run()
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100101
public void PrepareData()
101102
{
102-
mnist = MnistDataSet.read_data_sets("mnist", one_hot: true, train_size: TrainSize, validation_size: ValidationSize, test_size: TestSize);
103+
mnist = MnistDataSet.read_data_sets("mnist", one_hot: true, train_size: train_size, validation_size: validation_size, test_size: test_size);
103104
}
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105106
public void SaveModel(Session sess)

‎test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -39,7 +39,7 @@ public void InceptionArchGoogLeNet()
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[TestMethod]
4040
public void KMeansClustering()
4141
{
42-
new KMeansClustering() { Enabled = true }.Run();
42+
new KMeansClustering() { Enabled = true, train_size = 500, validation_size = 100, test_size = 100, batch_size =100 }.Run();
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}
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4545
[TestMethod]
@@ -51,7 +51,7 @@ public void LinearRegression()
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[TestMethod]
5252
public void LogisticRegression()
5353
{
54-
new LogisticRegression() { Enabled = true, TrainingEpochs=10, TrainSize = 500, ValidationSize = 100, TestSize = 100 }.Run();
54+
new LogisticRegression() { Enabled = true, training_epochs=10, train_size = 500, validation_size = 100, test_size = 100 }.Run();
5555
}
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5757
[Ignore]

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