code: def make_data_batch(batch_size, in_dim, type):
      np.random.seed(1234)
      batch = []
      lo = 0
      hi = 1
      if np.issubdtype(type, np.integer):
          info = np.iinfo(type)
          # clip range to +/- 1000000 to prevent excessively large epsilons
          lo = max(info.min / 2, -1000000)
          hi = min(info.max / 2, 1000000)
  
      for i in range(batch_size):
          batch.append(
              (
                  np.random.rand(np.random.randint(0, 10000), in_dim)
                  * (hi - lo)
                  + lo
              ).astype(type)
          )
      return batch
  
file_path: DALI/dali/test/python/operator_1/test_coord_transform.py
imports: import random
  import numpy
  import nvidia.dali
  import nvidia.dali.fn
  from test_utils import check_batch, dali_type
  from sequences_test_utils import ArgData, ArgDesc, sequence_suite_helper, ArgCb
label_desc: Use image node_id 3 for calling a global function with example usage: make_data_batch(batch_size, in_dim, type) and returns: batch