code: def testPMFFloats(self):
      logits = np.log(np.array([0.2, 0.8]))
      dist = categorical.Categorical(
          logits=logits, force_probs_to_zero_outside_support=True
      )
      inputs = [0.0, 0.5, 1.0, 1.5]
      # Should be 0 for non-integers.
      expected_outputs = np.array([0.2, 0.0, 0.8, 0.0])
      self.assertAllClose(
          self.evaluate(dist.prob(inputs)), expected_outputs
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import prefer_static
  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.util import deferred_tensor
label_desc: Use image node_id 1 for calling the ForceProbsToZeroOutsideSupportTest obj's underlying member method code with example usage: obj.testPMFFloats() without return types