code: def test_pad(self):
      t = Tensor.rand(3, 2, 0).pad((None, None, (1, 1)), 1)
      assert t.shape == (3, 2, 2)
      np.testing.assert_equal(t.numpy(), np.ones((3, 2, 2)))
  
      if Device.DEFAULT != "TORCH":
          # torch does not support padding non-zero dim with 0-size. torch.nn.functional.pad(torch.zeros(3,2,0), [0,0,0,4,0,0])
          t = Tensor.rand(3, 2, 0).pad((None, (1, 1), None), 1)
          assert t.shape == (3, 4, 0)
          np.testing.assert_equal(t.numpy(), np.ones((3, 4, 0)))
  
          t = Tensor.rand(3, 2, 0).pad(((1, 1), None, None), 1)
          assert t.shape == (5, 2, 0)
          np.testing.assert_equal(t.numpy(), np.ones((5, 2, 0)))
  
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 6 for calling the TestZeroShapeTensor obj's underlying member method code with example usage: obj.test_pad() without return types