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conditional_bijector_impl.py
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conditional_bijector_impl.py
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# Copyright 2016 The TensorFlow Authors. 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.
# ==============================================================================
"""ConditionalBijector base."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.ops.distributions import bijector
from tensorflow.python.ops.distributions import util as distribution_util
__all__ = ["ConditionalBijector"]
class ConditionalBijector(bijector.Bijector):
"""Conditional Bijector is a Bijector that allows intrinsic conditioning."""
@distribution_util.AppendDocstring(kwargs_dict={
"**condition_kwargs":
"Named arguments forwarded to subclass implementation."})
def forward(self, x, name="forward", **condition_kwargs):
return self._call_forward(x, name, **condition_kwargs)
@distribution_util.AppendDocstring(kwargs_dict={
"**condition_kwargs":
"Named arguments forwarded to subclass implementation."})
def inverse(self, y, name="inverse", **condition_kwargs):
return self._call_inverse(y, name, **condition_kwargs)
@distribution_util.AppendDocstring(kwargs_dict={
"**condition_kwargs":
"Named arguments forwarded to subclass implementation."})
def inverse_log_det_jacobian(
self, y, name="inverse_log_det_jacobian", **condition_kwargs):
return self._call_inverse_log_det_jacobian(y, name, **condition_kwargs)
@distribution_util.AppendDocstring(kwargs_dict={
"**condition_kwargs":
"Named arguments forwarded to subclass implementation."})
def forward_log_det_jacobian(
self, x, name="forward_log_det_jacobian", **condition_kwargs):
return self._call_forward_log_det_jacobian(x, name, **condition_kwargs)