7e5287713d58f17f7a4279df18825c05d7d066e3,jaxnerf/train.py,,main,#,102

Before Change

      t_loop_start = time.time()
      rays_per_sec = FLAGS.batch_size * steps_per_sec
      summary_writer.scalar("steps_per_sec", steps_per_sec, step)
      summary_writer.scalar("rays_per_sec", rays_per_sec, step)
      precision = int(np.ceil(np.log10(FLAGS.max_steps))) + 1
      print(("{:" + "{:d}".format(precision) + "d}").format(step) +
            f"/{FLAGS.max_steps:d}: " + f"i_loss={stats.loss[0]:0.5f}, " +
            f"avg_loss={avg_loss:0.5f}, " +

After Change

        eval_time = time.time() - t_eval_start
        num_rays = jnp.prod(jnp.array(test_case["rays"].directions.shape[:-1]))
        rays_per_sec = num_rays / eval_time
        summary_writer.scalar("test_rays_per_sec", rays_per_sec, step)
        print(f"Eval {step}: {eval_time:0.3f}s., {rays_per_sec:0.0f} rays/sec")
        summary_writer.scalar("test_psnr", psnr, step)
        summary_writer.scalar("test_ssim", ssim, step)
        summary_writer.image("test_pred_color", pred_color, step)

Instances