Hello @luisguiserrano! A very friendly introduction to GANs indeed :) I'm utilizing your code to carry out a class project to visualize a pandas df (50 x 300). So far, I've made alterations as shown to generate my dataframe:
def view_samples(samples, m, n): fig, axes = plt.subplots(figsize=(10, 10), nrows=m, ncols=n, sharey=True, sharex=True) for ax, img in zip(axes.flatten(), samples): ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) im = ax.imshow(1-img.reshape((50,300)), cmap='Greys_r') return fig, axes
Is the discriminator not training? Not sure if my error is zero or nothing is happening at all? Would you happen to know where the issue lies? Thank you!
Hello @luisguiserrano! A very friendly introduction to GANs indeed :) I'm utilizing your code to carry out a class project to visualize a pandas df (50 x 300). So far, I've made alterations as shown to generate my dataframe:
def view_samples(samples, m, n): fig, axes = plt.subplots(figsize=(10, 10), nrows=m, ncols=n, sharey=True, sharex=True) for ax, img in zip(axes.flatten(), samples): ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) im = ax.imshow(1-img.reshape((50,300)), cmap='Greys_r') return fig, axesIs the discriminator not training? Not sure if my error is zero or nothing is happening at all? Would you happen to know where the issue lies? Thank you!