class_docstr: Create mock images for inference on CPU based on the specifics of the original torch test dataset.
  Uses yield so as to avoid storing everything in the memory.
  Args:
      image_size (List[int]): Size of input image
      total_count (int): Total images in the test dataset
class_docstr_tok: ["Create","mock","images","for","inference","on","CPU","based","on","the","specifics","of","the","original","torch","test","dataset",".","Uses","yield","so","as","to","avoid","storing","everything","in","the","memory",".","Args",":","image_size","(","List","[","int","]",")",":","Size","of","input","image","total_count","(","int",")",":","Total","images","in","the","test","dataset"]
docstr: Yield batch of generated images.
  Args:
      idx (int): Unused
docstr_tok: ["Yield","batch","of","generated","images",".","Args",":","idx","(","int",")",":","Unused"]
code: def __call__(self) -> Iterable[np.ndarray]:
      """Yield batch of generated images.
      Args:
          idx (int): Unused
      """
      for _ in range(self.total_count):
          yield self.image
  
imports: from typing import Iterable, List
  import numpy
label_desc: Use image node_id 3 for calling the MockImageLoader obj's underlying member method code with example usage: obj.__call__() without return types