Source code for gpflow.utilities.parameter_or_function
# Copyright 2022 The GPflow Contributors. All Rights Reserved.
#
# 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
#
# http://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 typing import Optional, Union
import tensorflow as tf
from check_shapes import check_shapes
from ..base import Parameter, TensorData, TensorType
from ..functions import Function
from . import positive
ConstantOrFunction = Union[Function, TensorData]
ParameterOrFunction = Union[Function, Parameter]
[docs]
def prepare_parameter_or_function(
value: ConstantOrFunction,
*,
lower_bound: Optional[float] = None,
) -> ParameterOrFunction:
if isinstance(value, Function):
return value
else:
if lower_bound is None:
return Parameter(value)
else:
return Parameter(value, transform=positive(lower_bound))
[docs]
@check_shapes(
"X: [batch..., N, D]",
"return: [broadcast batch..., broadcast N, broadcast P]",
)
def evaluate_parameter_or_function(
value: ParameterOrFunction,
X: TensorType,
*,
lower_bound: Optional[float] = None,
) -> TensorType:
if isinstance(value, Function):
result = value(X)
if lower_bound is not None:
result = tf.maximum(result, lower_bound)
return result
else:
return value