code: def get_network_numpool(
      patch_size, maxpool_cap=999, min_feature_map_size=4
  ):
      network_numpool_per_axis = np.floor(
          [
              np.log(i / min_feature_map_size) / np.log(2)
              for i in patch_size
          ]
      ).astype(int)
      network_numpool_per_axis = [
          min(i, maxpool_cap) for i in network_numpool_per_axis
      ]
      return network_numpool_per_axis
  
file_path: PaddleSeg/contrib/MedicalSeg/tools/preprocess_utils/experiment_utils.py
imports: import numpy
  from copy import deepcopy
label_desc: Use image node_id 3 for calling a global function with example usage: get_network_numpool(patch_size, maxpool_cap, min_feature_map_size) and returns: network_numpool_per_axis