def METHOD_NAME(self):
    input_size_pairs = (
        ((7, 77, 7, 77), (5, 55, 5, 55)),
        ((1, 1, 777, 1), (1, 1, 555, 1)),
        ((5, 47, 5, 55), (1, 1, 1, 2048*32 + 1)),
        ((1, 1, 1, 2048*32 + 1), (55, 47, 5, 55)),
        ((555, 1, 1, 1), (32, 8, 32, 8)),
        ((32, 8, 32, 8), (55, 47, 5, 55)),
        ((1, 1, 33333, 1), (55, 47, 55, 5)),
        ((55, 47, 55, 5), (1, 1, 33333, 1)))
    appliers = (
        MultiTensorApply(2048*32),
        MultiTensorApply(333),
        MultiTensorApply(33333))
    repeat_tensors = (
        1,
        55)
    for sizea, sizeb in input_size_pairs:
      for applier in appliers:
        for repeat in repeat_tensors:
          for x_type in (torch.float32, torch.float16):
            for y_type in (torch.float32, torch.float16):
              for out_type in (torch.float32, torch.float16):
                for inplace in (True, False):
                  if inplace is True and (y_type is not out_type):
                    continue
                  else:
                    self.axpby(sizea, sizeb, applier, repeat,
                               x_type, y_type, out_type, inplace=inplace, nhwc=True)
                  # self.find_inf(sizea, sizeb, applier, repeat, in_type, out_type,
                  #               0, 0, float('nan'), inplace=inplace)
                  # self.find_inf(sizea, sizeb, applier, repeat, in_type, out_type,
                  #               2*repeat-1, sizeb-1, float('inf'), inplace=inplace)
                  # self.find_inf(sizea, sizeb, applier, repeat, in_type, out_type,
                  #              2*(repeat//2), sizea//2, float('inf'), inplace=inplace)