https://github.com/GPflow/GPflow
Tip revision: e24fd815cdfb8c654249da4576aeff6c2ce5a8ea authored by vdutor on 10 September 2020, 15:35:12 UTC
Start multioutput likelihood
Start multioutput likelihood
Tip revision: e24fd81
bijectors.py
from typing import Optional
import tensorflow_probability as tfp
from .. import config
from .utilities import to_default_float
__all__ = ["positive", "triangular"]
def positive(lower: Optional[float] = None, base: Optional[str] = None) -> tfp.bijectors.Bijector:
"""
Returns a positive bijector (a reversible transformation from real to positive numbers).
:param lower: overrides default lower bound
(if None, defaults to gpflow.config.default_positive_minimum())
:param base: overrides base positive bijector
(if None, defaults to gpflow.config.default_positive_bijector())
:returns: a bijector instance
"""
bijector = base if base is not None else config.default_positive_bijector()
bijector = config.positive_bijector_type_map()[bijector.lower()]()
lower_bound = lower if lower is not None else config.default_positive_minimum()
if lower_bound != 0.0:
shift = tfp.bijectors.Shift(to_default_float(lower_bound))
bijector = tfp.bijectors.Chain([shift, bijector]) # from unconstrained to constrained
return bijector
def triangular() -> tfp.bijectors.Bijector:
"""
Returns instance of a triangular bijector.
"""
return tfp.bijectors.FillTriangular()