code: def _test(
      self,
      transform_factory,
      shape=True,
      jacobian=True,
      inverse=True,
      autodiff=True,
      event_dim=1,
  ):
      for event_shape in [(2,), (5,)]:
          if event_dim > 1:
              event_shape = tuple(
                  [event_shape[0] + i for i in range(event_dim)]
              )
          transform = transform_factory(
              event_shape[0] if len(event_shape) == 1 else event_shape
          )
  
          if inverse:
              self._test_inverse(event_shape, transform)
          if shape:
              for shape in [(3,), (3, 4), (3, 4, 5)]:
                  base_shape = shape + event_shape
                  self._test_shape(base_shape, transform)
          if jacobian and transform.bijective:
              if event_dim > 1:
                  transform = Flatten(transform, event_shape)
              self._test_jacobian(
                  reduce(operator.mul, event_shape, 1), transform
              )
          if isinstance(transform, dist.TransformModule) and autodiff:
              # If the function doesn't have an explicit inverse, then use the forward op for autodiff
              self._test_autodiff(
                  reduce(operator.mul, event_shape, 1),
                  transform,
                  inverse=not inverse,
              )
  
imports: import operator
  from functools import partial, reduce
  from unittest import TestCase
  import pytest
  import torch
  import pyro.distributions
  import pyro.distributions.transforms
  from pyro.distributions import constraints
  from tests.common import assert_close
label_desc: Use image node_id 6 for calling the TransformTests obj's underlying member method code with example usage: obj._test(transform_factory, shape, jacobian, inverse, autodiff, event_dim) without return types