code: def test_deep_check():
      arr1, arr2 = np.random.rand(10), np.random.rand(10)
      tensor1, tensor2 = torch.rand([10]), torch.rand([10])
      s1, s2 = "string1", "string2"
      p1, p2 = Point(x=1, y=2), Point(x=2, y=1)
  
      assert not deep_check(arr1, arr2)
      assert not deep_check(tensor1, tensor2)
      assert not deep_check(s1, s2)
      assert not deep_check(p1, p2)
      assert not deep_check([arr1, tensor1], [arr2, tensor2])
      assert not deep_check([arr1, tensor1], (arr1, tensor1))
      assert not deep_check([arr1, tensor1], [tensor1, arr1])
      assert not deep_check(
          {"x": arr1, "y": tensor1}, {"x": arr2, "y": tensor2}
      )
      assert not deep_check(
          {"x": arr1, "y": tensor1}, {"x": tensor1, "y": arr1}
      )
  
      assert deep_check(arr1, arr1)
      assert deep_check(tensor1, tensor1)
      assert deep_check(s1, s1)
      assert deep_check(p1, p1)
      assert deep_check([arr1, tensor1], [arr1, tensor1])
      assert deep_check((arr1, tensor1), (arr1, tensor1))
      assert deep_check(
          {"x": arr1, "y": tensor1}, {"x": arr1, "y": tensor1}
      )
  
imports: from collections import namedtuple
  import numpy
  import torch
  from baal.utils.equality import deep_check
label_desc: Use image node_id 1 for calling a global function with example usage: test_deep_check() without return types