From 9a02bd419c89c79c4c890d52b3ae77d771ec8cdd Mon Sep 17 00:00:00 2001 From: wangyang59 Date: Thu, 17 Nov 2016 16:59:45 -0800 Subject: [PATCH] fixed a small bug in demo/gan/README.md and testMatrix.py --- demo/gan/README.md | 2 +- paddle/api/test/testMatrix.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/demo/gan/README.md b/demo/gan/README.md index 51faba1919..f347f15e2d 100644 --- a/demo/gan/README.md +++ b/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/ \ No newline at end of file diff --git a/paddle/api/test/testMatrix.py b/paddle/api/test/testMatrix.py index 0432345edd..8b0da62692 100644 --- a/paddle/api/test/testMatrix.py +++ b/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) -- GitLab