generatorLossesArray.append(0)
discriminatorLossesAveragesArray.append(
sum(discriminatorLossesArray) / len(discriminatorLossesArray))
generatorLossesAveragesArray.append(
sum(generatorLossesArray) / len(generatorLossesArray))
if (epoch % epochsPerPrint == 0):
save(generator.state_dict(), './generator.pth')
save(discriminator.state_dict(), './discriminator.pth')
print("Epoch: ", epoch)
plotter.plotImage(generatedImage)
plotter.plotImage(image)
plotter.multiGraph([
discriminatorLossesAveragesArray, generatorLossesAveragesArray
], ['r', 'w'], epochsPerPrint)
else:
noise = noiseGenerator.generate(batchSize, channels,
(noiseHeight, noiseWidth))
generatedImage = generator(noise)
plotter.plotImage(generatedImage)
#%%
if (training_mode):
save(generator.state_dict(), './generator.pth')
save(discriminator.state_dict(), './discriminator.pth')
