class_docstr: Bijector mapping R**n to non-negative reals.
  
  Forward computation maps R**n to the support of the `GeneralizedPareto`
  distribution with parameters `loc`, `scale`, and `concentration`.
  
  #### Mathematical Details
  
  The forward computation from `y` in R**n to `x` constrains `x` as follows:
  
  `x >= loc`                                             if `concentration >= 0`
  `x >= loc` and `x <= loc + scale / abs(concentration)` if `concentration < 0`
  
  This bijector is used as the `experimental_default_event_space_bijector` of
  the `GeneralizedPareto` distribution.
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code: def _is_increasing(self):
      return True
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
label_desc: Use image node_id 3 for calling the GeneralizedPareto obj's underlying member method code with example usage: obj._is_increasing() and returns: True