def eval_custom_lines32(self, ops, n_interpolations=256, n_images_per_interpolation=16):
image = self.make_sample_grid_and_save(
ops, 64, 0, n_images_per_interpolation, n_interpolations,
save_to_disk=False)[1]
image = image.reshape([n_interpolations, 32, n_images_per_interpolation, 32, 1])
batch2d = image.transpose(0, 2, 1, 3, 4)
mean_distance, mean_smoothness = eval.line_eval(batch2d)
tf.logging.info('kimg=%d mean_distance=%.4f mean_smoothness=%.4f' %
(self.cur_nimg >> 10, mean_distance, mean_smoothness))
return mean_distance, mean_smoothness
def eval_custom_lines32(self, ops, n_interpolations=256,
n_images_per_interpolation=16):
image = self.make_sample_grid_and_save(
ops, 64, 0, n_images_per_interpolation, n_interpolations,
save_to_disk=False)[1]
image = image.reshape([n_interpolations, 32,
n_images_per_interpolation, 32, 1])
batch2d = image.transpose(0, 2, 1, 3, 4)
mean_distance, mean_smoothness = eval.line_eval(batch2d)
tf.logging.info('kimg=%d mean_distance=%.4f mean_smoothness=%.4f' %
(self.cur_nimg >> 10, mean_distance, mean_smoothness))
return mean_distance, mean_smoothness
