class_docstr: Geometric distribution.
  
  The Geometric distribution is parameterized by p, the probability of a
  positive event. It represents the probability that in k + 1 Bernoulli trials,
  the first k trials failed, before seeing a success.
  
  The pmf of this distribution is:
  
  #### Mathematical Details
  
  ```none
  pmf(k; p) = (1 - p)**k * p
  ```
  
  where:
  
  * `p` is the success probability, `0 < p <= 1`, and,
  * `k` is a non-negative integer.
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code: def _mode(self):
      return tf.zeros(self.batch_shape_tensor(), dtype=self.dtype)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import generic
label_desc: Use image node_id 15 for calling the Geometric obj's underlying member method code with example usage: obj._mode() and returns: tf