code: def test_while_loop(self, backend):
      class TestLayer(nn.Module):
          def __init__(self):
              super(TestLayer, self).__init__()
  
          def forward(self, x):
              x = 0.5 * x
              return x
  
      class TestNet(nn.Module):
          input_size = (1,)
  
          def __init__(self):
              super(TestNet, self).__init__()
              layer = TestLayer()
              self.layer = torch.jit.trace(
                  layer, torch.rand(self.input_size)
              )
  
          def forward(self, x):
              while x > 0.01:
                  x = self.layer(x)
              return x
  
      model = TestNet().eval()
      torch_model = torch.jit.script(model)
  
      run_compare_torch(model.input_size, torch_model, backend=backend)
  
imports: import sys
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.testing_reqs import *
  from .testing_utils import *
label_desc: Use image node_id 2 for calling the TestLoop obj's underlying member method code with example usage: obj.test_while_loop(backend) and returns: x, x