code: def testOperatorBinaryLogical(self, op):
      loc = np.array([True, False])
      x = dtc._TensorCoercible(
          FakeBoolDistribution(), distribution.Distribution.mean
      )
      y1 = op(True, x)
      y2 = op(x, False)
      self.assertAllEqual(
          [op(True, loc), op(loc, False)], self.evaluate([y1, y2])
      )
  
imports: import gc
  import operator
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.layers import distribution_layer
  from tensorflow_probability.python.layers.internal import distribution_tensor_coercible
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 8 for calling the DistributionTensorConversionTest obj's underlying member method code with example usage: obj.testOperatorBinaryLogical(op) without return types