code: def id_list_batch(draw):
      batch_size = draw(st.integers(2, 2))
      values_dtype = np.float32
      inputs = []
      sample_size = draw(st.integers(5, 10))
      for _ in range(batch_size):
          values = draw(
              hnp.arrays(values_dtype, sample_size, st.integers(0, 1))
          )
          inputs += [values]
      return [np.array(inputs)]
  
file_path: pytorch/caffe2/python/operator_test/dense_vector_to_id_list_op_test.py
imports: from caffe2.python import core
  from hypothesis import given
  import caffe2.python.hypothesis_test_util
  import hypothesis.extra.numpy
  import hypothesis.strategies
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: id_list_batch(draw) and returns: list