code: def test_cat2_scalar(shape):
      tensor = torch.randn(shape)
      for dim in range(-len(shape), 0):
          expected_shape = list(shape)
          expected_shape[dim] += 1
          expected_shape = torch.Size(expected_shape)
          assert cat2(tensor, 0, dim=dim).shape == expected_shape
          assert cat2(0, tensor, dim=dim).shape == expected_shape
          assert (cat2(tensor, 0, dim=dim).unbind(dim)[-1] == 0).all()
          assert (cat2(0, tensor, dim=dim).unbind(dim)[0] == 0).all()
  
imports: import pytest
  import torch
  from pyro.contrib.epidemiology.util import cat2, clamp
  from tests.common import assert_equal
label_desc: Use image node_id 2 for calling a global function with example usage: test_cat2_scalar(shape) without return types