From fa4c747b7e9ef8deca9f806dd8e77315f805f2ca Mon Sep 17 00:00:00 2001 From: Junwei Pan Date: Tue, 28 Mar 2017 04:44:56 -0700 Subject: [PATCH] Typo Fix (#6017) --- examples/cifar10_cnn.py | 2 +- examples/mnist_acgan.py | 2 +- examples/mnist_net2net.py | 2 +- examples/mnist_swwae.py | 4 ++-- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/examples/cifar10_cnn.py b/examples/cifar10_cnn.py index 844f5c07b..110cedf94 100644 --- a/examples/cifar10_cnn.py +++ b/examples/cifar10_cnn.py @@ -91,7 +91,7 @@ else: horizontal_flip=True, # randomly flip images vertical_flip=False) # randomly flip images - # Compute quantities required for featurewise normalization + # Compute quantities required for feature-wise normalization # (std, mean, and principal components if ZCA whitening is applied). datagen.fit(x_train) diff --git a/examples/mnist_acgan.py b/examples/mnist_acgan.py index 16372d85e..cef6e0f47 100644 --- a/examples/mnist_acgan.py +++ b/examples/mnist_acgan.py @@ -222,7 +222,7 @@ if __name__ == '__main__': noise = np.random.uniform(-1, 1, (2 * batch_size, latent_size)) sampled_labels = np.random.randint(0, 10, 2 * batch_size) - # we want to train the genrator to trick the discriminator + # we want to train the generator to trick the discriminator # For the generator, we want all the {fake, not-fake} labels to say # not-fake trick = np.ones(2 * batch_size) diff --git a/examples/mnist_net2net.py b/examples/mnist_net2net.py index 7e51ba831..260f922f4 100644 --- a/examples/mnist_net2net.py +++ b/examples/mnist_net2net.py @@ -26,7 +26,7 @@ Notes Experiments - Teacher model: a basic CNN model trained on MNIST for 3 epochs. -- Net2WiderNet exepriment: +- Net2WiderNet experiment: + Student model has a wider Conv2D layer and a wider FC layer. + Comparison of 'random-padding' vs 'net2wider' weight initialization. + With both methods, student model should immediately perform as well as diff --git a/examples/mnist_swwae.py b/examples/mnist_swwae.py index 1619e25f3..80b34e216 100644 --- a/examples/mnist_swwae.py +++ b/examples/mnist_swwae.py @@ -35,12 +35,12 @@ applied as a bias because we know the MNIST digits are mapped to [0,1]. References: [3] 'Deep Residual Learning for Image Recognition' -Kaiming He, xiangyu Zhang, Shaoqing Ren, Jian Sun +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun https://arxiv.org/abs/1512.03385v1 [4] 'Identity Mappings in Deep Residual Networks' -Kaiming He, xiangyu Zhang, Shaoqing Ren, Jian Sun +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun https://arxiv.org/abs/1603.05027v3 '''