code: def test_gluon_domain_map():
      class TestDomainMap(HybridBlock):
          def __init__(self, constraint_type, bijective):
              super(TestDomainMap, self).__init__()
              self._constraint_type = getattr(
                  mgp.constraint, constraint_type
              )
  
          def forward(self, *params):
              value = params[0]
              constraint_param = params[1:]
              if len(constraint_param) == 0:
                  constraint = self._constraint_type()
              else:
                  constraint = self._constraint_type(*constraint_param)
              if bijective:
                  bijector = mgp.biject_to(constraint)
                  value = bijector(value)
              else:
                  transformation = mgp.transform_to(constraint)
                  value = transformation(value)
              return (value, constraint.check(value))
  
      constraints_zoo = [
          # (constraint_type, constraint_param)
          ("Positive", ()),
          ("GreaterThan", [np.random.randn(2, 2)]),
          ("GreaterThanEq", [np.random.randn(2, 2)]),
          ("LessThan", [np.random.randn(2, 2)]),
          (
              "Interval",
              [
                  np.random.uniform(0, 1, (2, 2)),
                  np.random.uniform(2, 3, (2, 2)),
              ],
          ),
          (
              "HalfOpenInterval",
              [
                  np.random.uniform(0, 1, (2, 2)),
                  np.random.uniform(2, 3, (2, 2)),
              ],
          ),
      ]
  
      test_sample = np.random.randn(2, 2)
  
      for constraint_type, constraint_arg in constraints_zoo:
          for bijective in [True, False]:
              for hybridize in [True, False]:
                  net = TestDomainMap(constraint_type, bijective)
                  if hybridize:
                      net.hybridize()
                  constrained_out, constraint_status = net(
                      test_sample, *constraint_arg
                  )
                  assert_almost_equal(
                      constrained_out.asnumpy(),
                      constraint_status.asnumpy(),
                  )
  
imports: import mxnet
  import numpy
  from mxnet import np, npx, autograd
  from mxnet import gluon
  import mxnet.gluon.probability
  from mxnet.gluon.probability import StochasticBlock, StochasticSequential
  from mxnet.gluon import HybridBlock
  from mxnet.test_utils import use_np, assert_almost_equal
  from numpy.testing import assert_array_equal
  import pytest
  import scipy.stats
  import scipy.special
  import itertools
  from numbers import Number
label_desc: Use image node_id 37 for calling a global function with example usage: test_gluon_domain_map() and returns: value,  constraint