message: Use math_ops.{sinh,asin,cosh} instead of trig.{sinh,arc_sinh) in Sinh bijector.
diff: @@ -25,9 +25,6 @@ from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.distributions import bijector
  -sinh = trig.sinh
  -arcsinh = trig.arcsinh
  -cosh = trig.cosh
  log_cosh = trig.log_cosh
  __all__ = [
  @@ -114,10 +111,10 @@ class SinhArcsinh(bijector.Bijector):
  return self._tailweight
  def _forward(self, x):
  - return sinh((arcsinh(x) + self.skewness) * self.tailweight)
  + return math_ops.sinh((math_ops.asinh(x) + self.skewness) * self.tailweight)
  def _inverse(self, y):
  - return sinh(arcsinh(y) / self.tailweight - self.skewness)
  + return math_ops.sinh(math_ops.asinh(y) / self.tailweight - self.skewness)
  def _inverse_log_det_jacobian(self, y):
  # x = sinh(arcsinh(y) / tailweight - skewness)
  @@ -127,7 +124,7 @@ class SinhArcsinh(bijector.Bijector):
  # / (tailweight * sqrt(y**2 + 1))
  event_dims = self._event_dims_tensor(y)
  return math_ops.reduce_sum(
  - log_cosh(arcsinh(y) / self.tailweight - self.skewness) -
  + log_cosh(math_ops.asinh(y) / self.tailweight - self.skewness) -
  math_ops.log(self.tailweight) - 0.5 * math_ops.log1p(y**2),
  axis=event_dims)
  @@ -138,6 +135,6 @@ class SinhArcsinh(bijector.Bijector):
  # = cosh((arcsinh(x) + skewness) * tailweight) * tailweight / sqrt(x**2 + 1)
  event_dims = self._event_dims_tensor(x)
  return math_ops.reduce_sum(
  - log_cosh((arcsinh(x) + self.skewness) * self.tailweight) +
  + log_cosh((math_ops.asinh(x) + self.skewness) * self.tailweight) +
  math_ops.log(self.tailweight) - 0.5 * math_ops.log1p(x**2),
  axis=event_dims)
  