code: def run_all(logdir):
      w = tf.summary.create_file_writer(logdir)
      tf.random.set_seed(0)
      with w.as_default():
          for x in range(5):
              image1 = tf.random.uniform(shape=[8, 8, 1])
              image2 = tf.random.uniform(shape=[8, 8, 1])
              tf.summary.image(
                  "grayscale_noise", [image1, image2], step=x
              )
              # Convert the original dtype=int32 `Tensor` into `dtype=float64`.
              rgb_image_float = (
                  tf.constant(
                      [
                          [
                              [1000 - 100 * x, 0, 0],
                              [0, 500, 1000 - 100 * x],
                          ],
                      ]
                  )
                  / 1000
              )
              tf.summary.image("picture", [rgb_image_float], step=x)
  
imports: from absl import app
  from absl import logging
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: run_all(logdir) without return types