code: def testParamTensorFromLogits(self):
      x = tf.constant([-1.0, 0.5, 1.0])
      d = binomial_lib.Binomial(
          total_count=1, logits=x, validate_args=True
      )
      logit = lambda x: tf.math.log(x) - tf.math.log1p(-x)
      self.assertAllClose(
          *self.evaluate([logit(d.prob(1.0)), d.logits_parameter()]),
          atol=0,
          rtol=1e-4,
      )
      self.assertAllClose(
          *self.evaluate([d.prob(1.0), d.probs_parameter()]),
          atol=0,
          rtol=1e-4,
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 29 for calling the BinomialTest obj's underlying member method code with example usage: obj.testParamTensorFromLogits() without return types