code: def sample_data():
      X = np.asarray(
          [
              np.random.uniform(0.0, 1.0, size=(3, 8, 8)).astype(
                  np.float32
              )
              for _ in range(4)
          ]
      )
      Y = np.asarray(
          [
              np.random.uniform(0.0, 1.0, size=(4, 6, 6)).astype(
                  np.float32
              )
              for _ in range(4)
          ]
      )
      X, Y = torch.tensor(X), torch.tensor(Y)
      return X, Y
  
imports: import copy
  from collections import OrderedDict
  import numpy
  import pytest
  import torch
  from coremltools.optimize.torch.pruning import MagnitudePruner, MagnitudePrunerConfig, ModuleMagnitudePrunerConfig
  from coremltools.optimize.torch.pruning._utils import n_m_mask
label_desc: Use image node_id 7 for calling a global function with example usage: sample_data() and returns: X,  Y