fixed a small bug in demo/gan/README.md and testMatrix.py

demo/gan/README.md

@@ -7,6 +7,6 @@ The general training procedures are implemented in gan_trainer.py. The neural ne
 In order to run the model, first download the corresponding data by running the shell script in ./data.
 Then you can run the command below. The flag -d specifies the training data (cifar, mnist or uniform) and flag --useGpu specifies whether to use gpu for training (0 is cpu, 1 is gpu).  
 
-$python gan_trainer_image.py -d cifar --useGpu 1
+$python gan_trainer.py -d cifar --useGpu 1
 
 The generated images will be stored in ./cifar_samples/

paddle/api/test/testMatrix.py

@@ -68,7 +68,7 @@ class TestMatrix(unittest.TestCase):
 
     def test_numpyCpu(self):
         numpy_mat = np.matrix([[1, 2], [3, 4], [5, 6]], dtype="float32")
-        m = swig_paddle.Matrix.createCpuDenseFromNumpy(numpy_mat)
+        m = swig_paddle.Matrix.createCpuDenseFromNumpy(numpy_mat, copy=False)
         self.assertEqual((int(m.getHeight()), int(m.getWidth())),
                          numpy_mat.shape)