8ff81bf47b897cb714839245301c207c1d13c24c,src/generate_class_specific_samples.py,ClassSpecificImageGeneration,generate,#ClassSpecificImageGeneration#,32

Before Change

            // Target specific class
            class_loss = -output[0, self.target_class]

            if i in np.linspace(0, iterations, 10, dtype=int):
                print("Iteration:", str(i), "Loss",
                      "{0:.2f}".format(class_loss.data.numpy()))
            // Zero grads

After Change

            self.created_image = recreate_image(self.processed_image)
            if i % 10 == 0 or i == iterations-1:
                // Save image
                im_path = "../generated/class_"+str(self.target_class)+"/c_"+str(self.target_class)+"_"+"iter_"+str(i)+".png"
                save_image(self.created_image, im_path)

        return self.processed_image

Instances