code: def perturbate_input_(input_, n_elements=200):
      N, C, H, W = input_.shape
      if N != 1:
          raise AssertionError
      c_ = np.random.random_integers(0, C - 1, n_elements)
      h_ = np.random.random_integers(0, H - 1, n_elements)
      w_ = np.random.random_integers(0, W - 1, n_elements)
      for c_idx in c_:
          for h_idx in h_:
              for w_idx in w_:
                  input_[0, c_idx, h_idx, w_idx] = 1
      return input_
  
file_path: pywick/pywick/models/segmentation/testnets/gscnn/my_functionals/DualTaskLoss.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import numpy
  from .custom_functional import compute_grad_mag
label_desc: Use image node_id 1 for calling a global function with example usage: perturbate_input_(input_, n_elements) and returns: input_