fce640ec46a05da265ce8d36066296277fc8061f,mnist_dcgan.py,DCGAN,save_imgs,#DCGAN#Any#,165
Before Change
gen_imgs = 0.5 * gen_imgs + 1
fig, axs = plt.subplots(r, c)
fig.suptitle("DCGAN: Generated digits", fontsize=12)
cnt = 0
for i in range(r):
for j in range(c):
axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap="gray")After Change
self.save_imgs(epoch)
def save_imgs(self, epoch):
r, c = 5 , 5
noise = np.random.normal(0, 1, (r * c, 100))
gen_imgs = self.generator.predict(noise)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 2
Instances Project Name: eriklindernoren/Keras-GAN
Commit Name: fce640ec46a05da265ce8d36066296277fc8061f
Time: 2017-07-11
Author: eriklindernoren@live.se
File Name: mnist_dcgan.py
Class Name: DCGAN
Method Name: save_imgs
Project Name: freelunchtheorem/Conditional_Density_Estimation
Commit Name: 75e5820670fa8fe7f06817b4e57feb847e77f24f
Time: 2019-07-01
Author: jonas.rothfuss@gmx.de
File Name: cde/evaluation/simulation_eval/plotting/question8_plots.py
Class Name:
Method Name:
Project Name: matplotlib/matplotlib
Commit Name: fa9c8b9ae1ec76d4bf60ad82352d40d5a3c8379e
Time: 2020-11-03
Author: 2836374+timhoffm@users.noreply.github.com
File Name: examples/event_handling/figure_axes_enter_leave.py
Class Name:
Method Name:
