code: def gen_tf_with_dali_external_source(test_run):
      for dtype in [np.uint8, np.int32, np.float32]:
          for (
              get_callback,
              is_batched,
              cycle,
              batch_info,
          ) in es_configurations:
              for dense in get_dense_options(is_batched):
                  for dev, es_dev in [
                      ("cpu", "cpu"),
                      ("gpu", "cpu"),
                      ("gpu", "gpu"),
                  ]:
                      for iter_limit in [3, 9, 10, 11, 100]:
                          bs = 12 if is_batched else None
                          es_args = {
                              "source": get_callback(
                                  dtype, iter_limit, bs, dense
                              ),
                              "batch": is_batched,
                              "cycle": cycle,
                              "batch_info": batch_info,
                          }
                          yield test_run, dev, es_args, es_dev, tf.dtypes.as_dtype(
                              dtype
                          ), iter_limit, dense
  
imports: import copy
  import numpy
  import nvidia.dali.plugin.tf
  import tensorflow
  from nvidia.dali import Pipeline, fn
  from test_utils import RandomlyShapedDataIterator
label_desc: Use image node_id 10 for calling a global function with example usage: gen_tf_with_dali_external_source(test_run) without return types