fix dictionary access when modified.

Oceania2018 · Oceania2018 · commit cb82dafcf7db · 2019-07-11T20:05:43.000-05:00
diff --git a/src/TensorFlowNET.Core/Variables/_VariableScopeStore.cs b/src/TensorFlowNET.Core/Variables/_VariableScopeStore.cs
@@ -41,7 +41,11 @@ public void open_variable_scope(string scope_name)
 
         public void close_variable_subscopes(string scope_name)
         {
+            var variable_scopes_count_tmp = new Dictionary<string, int>();
             foreach (var k in variable_scopes_count.Keys)
+                variable_scopes_count_tmp.Add(k, variable_scopes_count[k]);
+
+            foreach (var k in variable_scopes_count_tmp.Keys)
                 if (scope_name == null || k.StartsWith(scope_name + "/"))
                     variable_scopes_count[k] = 0;
         }
diff --git a/test/TensorFlowNET.Examples/ImageProcess/DigitRecognitionCNN.cs b/test/TensorFlowNET.Examples/ImageProcess/DigitRecognitionCNN.cs
@@ -73,6 +73,8 @@ public class DigitRecognitionCNN : IExample
         float accuracy_test = 0f;
         float loss_test = 1f;
 
+        NDArray x_train;
+
         public bool Run()
         {
             PrepareData();
@@ -241,11 +243,19 @@ private Tensor fc_layer(Tensor x, int num_units, string name, bool use_relu = tr
         public void PrepareData()
         {
             mnist = MNIST.read_data_sets("mnist", one_hot: true);
+            x_train = Reformat(mnist.train.data, mnist.train.labels);
             print("Size of:");
             print($"- Training-set:\t\t{len(mnist.train.data)}");
             print($"- Validation-set:\t{len(mnist.validation.data)}");
         }
 
+        private NDArray Reformat(NDArray x, NDArray y)
+        {
+            var (img_size, num_ch, num_class) = (np.sqrt(x.shape[1]), 1, np.unique<int>(np.argmax(y, 1)));
+
+            return x;
+        }
+
         public void Train(Session sess)
         {
             // Number of training iterations in each epoch
diff --git a/test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs b/test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs
@@ -39,6 +39,7 @@ public void InceptionArchGoogLeNet()
             new InceptionArchGoogLeNet() { Enabled = true }.Run();
         }
 
+        [Ignore]
         [TestMethod]
         public void KMeansClustering()
         {
@@ -83,10 +84,12 @@ public void NearestNeighbor()
             new NearestNeighbor() { Enabled = true, TrainSize = 500, ValidationSize = 100, TestSize = 100 }.Run();
         }
 
+        [Ignore]
         [TestMethod]
         public void WordCnnTextClassification()
             => new CnnTextClassification { Enabled = true, ModelName = "word_cnn", DataLimit =100 }.Run();
 
+        [Ignore]
         [TestMethod]
         public void CharCnnTextClassification()
             => new CnnTextClassification { Enabled = true, ModelName = "char_cnn", DataLimit = 100 }.Run();

Original file line number	Diff line number	Diff line change
`@@ -41,7 +41,11 @@ public void open_variable_scope(string scope_name)`
`41`	`41`
`42`	`42`	`public void close_variable_subscopes(string scope_name)`
`43`	`43`	`{`
	`44`	`+ var variable_scopes_count_tmp = new Dictionary<string, int>();`
`44`	`45`	`foreach (var k in variable_scopes_count.Keys)`
	`46`	`+ variable_scopes_count_tmp.Add(k, variable_scopes_count[k]);`
	`47`	`+`
	`48`	`+ foreach (var k in variable_scopes_count_tmp.Keys)`
`45`	`49`	`if (scope_name == null \|\| k.StartsWith(scope_name + "/"))`
`46`	`50`	`variable_scopes_count[k] = 0;`
`47`	`51`	`}`
Original file line number	Diff line number	Diff line change
`@@ -39,6 +39,7 @@ public void InceptionArchGoogLeNet()`
`39`	`39`	`new InceptionArchGoogLeNet() { Enabled = true }.Run();`
`40`	`40`	`}`
`41`	`41`
	`42`	`+ [Ignore]`
`42`	`43`	`[TestMethod]`
`43`	`44`	`public void KMeansClustering()`
`44`	`45`	`{`
`@@ -83,10 +84,12 @@ public void NearestNeighbor()`
`83`	`84`	`new NearestNeighbor() { Enabled = true, TrainSize = 500, ValidationSize = 100, TestSize = 100 }.Run();`
`84`	`85`	`}`
`85`	`86`
	`87`	`+ [Ignore]`
`86`	`88`	`[TestMethod]`
`87`	`89`	`public void WordCnnTextClassification()`
`88`	`90`	`=> new CnnTextClassification { Enabled = true, ModelName = "word_cnn", DataLimit =100 }.Run();`
`89`	`91`
	`92`	`+ [Ignore]`
`90`	`93`	`[TestMethod]`
`91`	`94`	`public void CharCnnTextClassification()`
`92`	`95`	`=> new CnnTextClassification { Enabled = true, ModelName = "char_cnn", DataLimit = 100 }.Run();`