code: def test_fuzz(self):
      input_size_pairs = (
          (7777 * 77, 555 * 555),
          (777, 555),
          (555, 2048 * 32 + 1),
          (2048 * 32 + 1, 555),
          (555, 2048 * 32),
          (2048 * 32, 555),
          (33333, 555),
          (555, 33333),
      )
      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 in_type in (torch.float32, torch.float16):
                      for per_tensor in (False, True):
                          self.l2norm(
                              sizea,
                              sizeb,
                              applier,
                              repeat,
                              in_type,
                              per_tensor,
                          )
  
file_path: apex/tests/L0/run_amp/test_multi_tensor_l2norm.py
imports: import unittest
  import functools
  import itertools
  from apex import amp
  import torch
  from torch import nn
  import torch.nn.functional
  from utils import common_init, HALF, FLOAT, ALWAYS_HALF, ALWAYS_FLOAT, MATCH_INPUT
label_desc: Use image node_id 4 for calling the TestMultiTensorL2Norm obj's underlying member method code with example usage: obj.test_fuzz() without return types