train.py [306:318]:
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                orig_im = rescale_im(orig_im)
                try_im = rescale_im(try_im).squeeze()

                for i, (im, t_im, actual_im_i) in enumerate(
                        zip(orig_im[:20], try_im[:20], actual_im)):
                    shape = orig_im.shape[1:]
                    new_im = np.zeros((shape[0], shape[1] * 3, *shape[2:]))
                    size = shape[1]
                    new_im[:, :size] = im
                    new_im[:, size:2 * size] = t_im
                    new_im[:, 2 * size:] = actual_im_i

                    log_image(
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train.py [375:387]:
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                orig_im = rescale_im(orig_im)
                try_im = rescale_im(try_im).squeeze()

                for i, (im, t_im, actual_im_i) in enumerate(
                        zip(orig_im[:20], try_im[:20], actual_im)):

                    shape = orig_im.shape[1:]
                    new_im = np.zeros((shape[0], shape[1] * 3, *shape[2:]))
                    size = shape[1]
                    new_im[:, :size] = im
                    new_im[:, size:2 * size] = t_im
                    new_im[:, 2 * size:] = actual_im_i
                    log_image(
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