code: def test_cat(self):
      s = Tensor.rand(3, 2, 2)
      t = Tensor.rand(3, 2, 0).cat(s, dim=2)
      assert t.shape == (3, 2, 2)
      np.testing.assert_equal(t.numpy(), s.numpy())
  
      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])
          s = Tensor.rand(3, 4, 0)
          t = Tensor.rand(3, 2, 0).cat(s, dim=1)
          assert t.shape == (3, 6, 0)
          np.testing.assert_equal(t.numpy(), np.zeros((3, 6, 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 8 for calling the TestZeroShapeTensor obj's underlying member method code with example usage: obj.test_cat() without return types