(self, n)
| 216 | return current_img_summary, imgs |
| 217 | |
| 218 | def visualization(self, n): |
| 219 | fake_sum_train, superimage_train = \ |
| 220 | self.visualize_one_superimage(self.fake_images[:n * n], |
| 221 | self.images[:n * n], |
| 222 | n, "train") |
| 223 | fake_sum_test, superimage_test = \ |
| 224 | self.visualize_one_superimage(self.fake_images[n * n:2 * n * n], |
| 225 | self.images[n * n:2 * n * n], |
| 226 | n, "test") |
| 227 | self.superimages = tf.concat(0, [superimage_train, superimage_test]) |
| 228 | self.image_summary = tf.merge_summary([fake_sum_train, fake_sum_test]) |
| 229 | |
| 230 | def preprocess(self, x, n): |
| 231 | # make sure every row with n column have the same embeddings |
no test coverage detected