1aff940e60d7d62bd82ddf7469e666197832e212,src/classifiers/cnn_unittest.py,TestCNNModel,test_mnist,#TestCNNModel#,55

Before Change


        X_train, Y_train, X_test, Y_test = X_train[:NB_TRAIN], Y_train[:NB_TRAIN], X_test[:NB_TEST], Y_test[:NB_TEST]

        // convert class vectors to binary class matrices
        Y_train = np_utils.to_categorical(Y_train,NB_CLASSES)
        Y_test = np_utils.to_categorical(Y_test,NB_CLASSES)

        im_shape = X_train[0].shape

After Change



        scores = model.evaluate(X_test,Y_test)

        print("\naccuracy: %.2f%%" % (scores[1] * 100))

if __name__ == "__main__":
    unittest.main()
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: IBM/adversarial-robustness-toolbox
Commit Name: 1aff940e60d7d62bd82ddf7469e666197832e212
Time: 2017-05-11
Author: valentina.zantedeschi@ibm.com
File Name: src/classifiers/cnn_unittest.py
Class Name: TestCNNModel
Method Name: test_mnist


Project Name: IBM/adversarial-robustness-toolbox
Commit Name: 1aff940e60d7d62bd82ddf7469e666197832e212
Time: 2017-05-11
Author: valentina.zantedeschi@ibm.com
File Name: src/classifiers/cnn_unittest.py
Class Name: TestCNNModel
Method Name: test_cifar


Project Name: osmr/imgclsmob
Commit Name: 09e4a76102ff4a06a835180237ea171eb475985c
Time: 2018-09-19
Author: osemery@gmail.com
File Name: keras_/models/mobilenet.py
Class Name:
Method Name: _test