code: def testDistributionWithVars(self, dist_name, data):
      dist = data.draw(
          dhps.base_distributions(dist_name=dist_name, enable_vars=True)
      )
      self.evaluate([var.initializer for var in dist.variables])
      self.assume_loc_scale_ok(dist)
      self.check_event_space_bijector_constrains(dist, data)
  
imports: import collections
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python import distributions
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import expm1
  from tensorflow_probability.python.bijectors import normal_cdf
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import hypothesis_testlib
label_desc: Use image node_id 2 for calling the EventSpaceBijectorsTest obj's underlying member method code with example usage: obj.testDistributionWithVars(dist_name, data) without return types