class_docstr: Calculates the learnability of a set of features.
  mini-batch version w/ "left" and "right" multiplies
class_docstr_tok: ["Calculates","the","learnability","of","a","set","of","features",".","mini-batch","version","w\/","``","left","''","and","``","right","''","multiplies"]
docstr: Get the return value based on z.
docstr_tok: ["Get","the","return","value","based","on","z","."]
code: def ret_val(self, z):
      """
      Get the return value based on z.
      """
  
      if not self.binary:
          return 1 - z
  
      else:
          return 0.5 * (1 - safesqrt.apply(ramp.apply(z)))
  
imports: import time
  import numpy
  import scipy.special
  import torch
  import torch.nn
  from .None import constants
  from .None import syssettings
  from .fginitialize import ChunkDataLoader
label_desc: Use image node_id 2 for calling the LearnabilityMB obj's underlying member method code with example usage: obj.ret_val(z) and returns: unknown, unknown