class_docstr: Base class for segmentors.
class_docstr_tok: ["Base","class","for","segmentors","."]
docstr: The iteration step during validation.
  
  This method shares the same signature as :func:`train_step`, but used
  during val epochs. Note that the evaluation after training epochs is
  not implemented with this method, but an evaluation hook.
docstr_tok: ["The","iteration","step","during","validation",".","This","method","shares","the","same","signature","as",":","func",":","`","train_step","`",",","but","used","during","val","epochs",".","Note","that","the","evaluation","after","training","epochs","is","not","implemented","with","this","method",",","but","an","evaluation","hook","."]
code: def val_step(self, data_batch, **kwargs):
      """The iteration step during validation.
  
      This method shares the same signature as :func:`train_step`, but used
      during val epochs. Note that the evaluation after training epochs is
      not implemented with this method, but an evaluation hook.
      """
      output = self(**data_batch, **kwargs)
      return output
  
imports: import logging
  import warnings
  from abc import ABCMeta, abstractmethod
  from collections import OrderedDict
  import annotator.uniformer.mmcv
  import numpy
  import torch
  import torch.distributed
  import torch.nn
  from annotator.uniformer.mmcv.runner import auto_fp16
label_desc: Use image node_id 14 for calling the BaseSegmentor obj's underlying member method code with example usage: obj.val_step(data_batch) and returns: output