code: def find_inf(
      self,
      sizea,
      sizeb,
      applier,
      repeat_tensors,
      in_type,
      out_type,
      t,
      ind,
      val,
      inplace=False,
  ):
      self.overflow_buf.zero_()
      a = torch.cuda.FloatTensor(sizea).fill_(self.scale)
      b = torch.cuda.FloatTensor(sizeb).fill_(self.scale)
  
      out_list = []
      for i in range(repeat_tensors):
          out_list += [a.clone().to(out_type), b.clone().to(out_type)]
  
      if inplace:
          in_list = out_list
      else:
          in_list = [out.clone().to(in_type) for out in out_list]
  
      applier(
          multi_tensor_scale,
          self.overflow_buf,
          [in_list, out_list],
          1.0 / self.scale,
      )
  
      self.overflow_buf.zero_()
      in_list[t][ind] = val
      applier(
          multi_tensor_scale,
          self.overflow_buf,
          [in_list, out_list],
          1.0 / self.scale,
      )
      self.assertTrue(self.overflow_buf.item())
  
file_path: apex/tests/L0/run_amp/test_multi_tensor_scale.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 TestMultiTensorScale obj's underlying member method code with example usage: obj.find_inf(sizea, sizeb, applier, repeat_tensors, in_type, out_type, t, ind, val, inplace) without return types