code: def test_randn_isnt_inf_on_zero(self):
      # simulate failure case of rand handing a zero to randn
      original_rand, Tensor.rand = Tensor.rand, Tensor.zeros
      try:
          self.assertNotIn(np.inf, Tensor.randn(16).numpy())
      except:
          raise
      finally:
          Tensor.rand = original_rand
  
imports: import numpy
  import torch
  import unittest, copy
  import mmap
  from tinygrad import Tensor, Device, dtypes
  from tinygrad.helpers import temp
  from extra.gradcheck import numerical_jacobian, jacobian, gradcheck
label_desc: Use image node_id 10 for calling the TestTinygrad obj's underlying member method code with example usage: obj.test_randn_isnt_inf_on_zero() without return types