class_docstr: Converts a PIL, numpy or CV image to a torch.float32 representation
class_docstr_tok: ["Converts","a","PIL",",","numpy","or","CV","image","to","a","torch.float32","representation"]
code: def __call__(self, img):
      if self.divisor is None:
          return th.from_numpy(np.array(img, dtype=np.float32))
      else:
          return th.from_numpy(
              np.array(img, dtype=np.float32) / self.divisor
          )
  
imports: import random
  import torch
  from torchvision.transforms.functional import to_tensor
  import numpy
  from ..utils import th_random_choice
label_desc: Use image node_id 2 for calling the MaskToFloatTensor obj's underlying member method code with example usage: obj.__call__(img) and returns: th, th