code: def setUp(self):
      self.feature_dim = 2
      self.hidden_layer_size = 10
      data_points = 10
  
      X = np.random.randn(data_points, self.feature_dim)
      y = (X[:, 0] > X[:, 1]).astype(np.float32)
  
      self.dataset = dc.data.NumpyDataset(X, y)
  
file_path: deepchem/deepchem/models/tests/test_pretrained_torch.py
imports: import unittest
  import pytest
  import deepchem
  import numpy
label_desc: Use image node_id 1 for calling the TestPretrainedTorch obj's underlying member method code with example usage: obj.setUp() without return types