class_docstr: An object representing a range of sizes for an image feature inside a
  neural network. Valid ranges for height and width are > 0. A "-1"
  upper bound value for either width or height represents an unbounded size
  for that dimension.
class_docstr_tok: ["An","object","representing","a","range","of","sizes","for","an","image","feature","inside","a","neural","network",".","Valid","ranges","for","height","and","width","are",">","0",".","A","``","-1","''","upper","bound","value","for","either","width","or","height","represents","an","unbounded","size","for","that","dimension","."]
code: def get_width_range(self):
      return self._width_range
  
imports: from ..utils import _get_feature, _get_nn_layers, _get_input_names
  from ...None import _MINIMUM_FLEXIBLE_SHAPES_SPEC_VERSION
  from ...None import _MINIMUM_NDARRAY_SPEC_VERSION
label_desc: Use image node_id 4 for calling the NeuralNetworkImageSizeRange obj's underlying member method code with example usage: obj.get_width_range() and returns: self