code: def check_input_shape(input_shape, factor):
      if input_shape is None:
          raise ValueError(
              "Input shape should be a tuple of 3 integers, not None!"
          )
  
      h, w = (
          input_shape[:2]
          if backend.image_data_format() == "channels_last"
          else input_shape[1:]
      )
      min_size = factor * 6
  
      is_wrong_shape = (
          h % min_size != 0
          or w % min_size != 0
          or h < min_size
          or w < min_size
      )
  
      if is_wrong_shape:
          raise ValueError(
              "Wrong shape {}, input H and W should ".format(
                  input_shape
              )
              + "be divisible by `{}`".format(min_size)
          )
  
file_path: segmentation_models/segmentation_models/models/pspnet.py
imports: from keras_applications import get_submodules_from_kwargs
  from ._common_blocks import Conv2dBn
  from ._utils import freeze_model, filter_keras_submodules
  from ..backbones.backbones_factory import Backbones
label_desc: Use image node_id 2 for calling a global function with example usage: check_input_shape(input_shape, factor) without return types