def __init__(self,<EOL>logits=None,<EOL>probs=None,<EOL>validate_args=False,<EOL>allow_nan_stats=True,<EOL>name="<STR_LIT>"):
parameters = dict(locals())<EOL>with tf.name_scope(name) as name:<EOL><INDENT>self._logits, self._probs = distribution_util.get_logits_and_probs(<EOL>logits, probs, validate_args=validate_args, name=name)<EOL>with tf.control_dependencies(<EOL>[assert_util.assert_positive(self._probs)] if validate_args else []):<EOL><INDENT>self._probs = tf.identity(self._probs, name="<STR_LIT>")<EOL><DEDENT><DEDENT>super(Geometric, self).__init__(<EOL>dtype=self._probs.dtype,<EOL>reparameterization_type=reparameterization.NOT_REPARAMETERIZED,<EOL>validate_args=validate_args,<EOL>allow_nan_stats=allow_nan_stats,<EOL>parameters=parameters,<EOL>graph_parents=[self._probs, self._logits],<EOL>name=name)<EOL>
Construct Geometric distributions.

        Args:
          logits: Floating-point `Tensor` with shape `[B1, ..., Bb]` where `b >= 0`
            indicates the number of batch dimensions. Each entry represents logits
            for the probability of success for independent Geometric distributions
            and must be in the range `(-inf, inf]`. Only one of `logits` or `probs`
            should be specified.
          probs: Positive floating-point `Tensor` with shape `[B1, ..., Bb]`
            where `b >= 0` indicates the number of batch dimensions. Each entry
            represents the probability of success for independent Geometric
            distributions and must be in the range `(0, 1]`. Only one of `logits`
            or `probs` should be specified.
          validate_args: Python `bool`, default `False`. When `True` distribution
            parameters are checked for validity despite possibly degrading runtime
            performance. When `False` invalid inputs may silently render incorrect
            outputs.
          allow_nan_stats: Python `bool`, default `True`. When `True`, statistics
            (e.g., mean, mode, variance) use the value "`NaN`" to indicate the
            result is undefined. When `False`, an exception is raised if one or
            more of the statistic's batch members are undefined.
          name: Python `str` name prefixed to Ops created by this class.