text: # Copyright 2018 Google LLC
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     https://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import numpy as onp
  import scipy.stats as osp_stats
  
  from ... import lax
  from ...numpy.lax_numpy import _promote_args_like, _constant_like, _wraps, inf, where
  
  
  @_wraps(osp_stats.pareto.logpdf)
  def logpdf(x, b, loc=0, scale=1):
    x, b, loc, scale = _promote_args_like(osp_stats.pareto.logpdf, x, b, loc, scale)
    one = _constant_like(x, 1)
    scaled_x = lax.div(lax.sub(x, loc), scale)
    normalize_term = lax.log(lax.div(scale, b))
    log_probs = lax.neg(lax.add(normalize_term, lax.mul(lax.add(b, one), lax.log(scaled_x))))
    return where(lax.lt(x, lax.add(loc, scale)), -inf, log_probs)
  
  @_wraps(osp_stats.pareto.pdf)
  def pdf(x, b, loc=0, scale=1):
    return lax.exp(logpdf(x, b, loc, scale))
  