class_docstr: Segmentation Eval Module
class_docstr_tok: ["Segmentation","Eval","Module"]
code: def __call__(self, *inputs, **kwargs):
      if self.use_predict:
          return self.module.predict(*inputs, **kwargs)
      else:
          return self.module.evaluate(*inputs, **kwargs)
  
imports: import math
  import warnings
  import numpy
  import mxnet
  from mxnet.ndarray import NDArray
  from mxnet.gluon.nn import HybridBlock
  from ..utils.parallel import parallel_apply
  from .resnetv1b import resnet18_v1b, resnet34_v1b, resnet50_v1s, resnet101_v1s, resnet152_v1s
  from .resnest import resnest50, resnest101, resnest200, resnest269
  from ..utils.parallel import tuple_map
label_desc: Use image node_id 2 for calling the SegEvalModel obj's underlying member method code with example usage: obj.__call__() and returns: self, self