|
|
@@ -213,18 +213,8 @@ class Exercise:
|
|
|
# Test this dataset with every given test-function.
|
|
|
# The results are printed out and stored to the results dictionary.
|
|
|
if gan.canPredict and "GAN" not in self.testFunctions.keys():
|
|
|
- #self.debug(f"-> retrain GAN for predict")
|
|
|
- #trainData = np.concatenate((dataSlice.train.data0, dataSlice.train.data1))
|
|
|
- #trainLabels = np.concatenate((np.zeros(len(dataSlice.train.data0)), np.zeros(len(dataSlice.train.data1)) + 1))
|
|
|
- #indices = shuffle(np.array(range(len(trainData))))
|
|
|
- #trainData = trainData[indices]
|
|
|
- #trainLabels = trainLabels[indices]
|
|
|
- #indices = None
|
|
|
- #gan.retrainDiscriminitor(trainData, trainLabels)
|
|
|
- #trainData = None
|
|
|
- #trainLabels = None
|
|
|
self.debug(f"-> test with 'GAN'")
|
|
|
- testResult = runTester(dataSlice, gan, f"{imageFileName}-GAN.json")
|
|
|
+ testResult = runTester(dataSlice, gan, "GAN", f"{imageFileName}-GAN.json")
|
|
|
self.debug(str(testResult))
|
|
|
self.results["GAN"].append(testResult)
|
|
|
|