class_docstr: Helper transform wrapper to make the given transform deterministic
class_docstr_tok: ["Helper","transform","wrapper","to","make","the","given","transform","deterministic"]
code: def forward(self, input: torch.Tensor):
      torch.random.manual_seed(self.seed)
      return self.transform(input)
  
imports: import unittest
  from typing import List
  import torch
  import torchaudio.transforms
  from parameterized import parameterized
  from torch.autograd import gradcheck, gradgradcheck
  from torchaudio_unittest.common_utils import get_spectrogram, get_whitenoise, nested_params, rnnt_utils, TestBaseMixin
label_desc: Use image node_id 2 for calling the _DeterministicWrapper obj's underlying member method code with example usage: obj.forward(input) and returns: self