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21 September 2021, 22:50:56 UTC
Revision 5b16a12e3a21e1435badfe99c4821444260df2fa authored by John Bradshaw on 23 October 2017, 10:32:06 UTC, committed by John Bradshaw on 23 October 2017, 10:32:06 UTC 
Refactor of EP implementation to modularise and make more extensible in
 
the future.

* EP while loop broken out and made into seperate class to allow it to
be easy to reuse elsewhere. Tidy up of the variable names and made more
general. Tests written to check that it can recover the true solution
when the approximating factors have the same solution as the true
solution.
* Central moment functions moved out of EP class and live elsewhere.
Step function, Gaussian and Gaussian CDF moments implemented all with
tests.
* Likelihoods now are associated with a method that returns their central
moments generator function. Only implemented for Bernoulli but this
allows one to store moment logic with the likelihood function which is
more where it belongs.
* Updated the VGP versus EP binary classification example script to use
this new source structure. This has remained in the docs so have not
written tests for this part.
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Tip revision: 5b16a12e3a21e1435badfe99c4821444260df2fa authored by John Bradshaw on 23 October 2017, 10:32:06 UTC
Refactor of EP implementation to modularise and make more extensible in
Tip revision: 5b16a12
Dockerfile 
# Copyright 2016 The GPflow authors
#
# 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.

#USAGE:
#To run from prebuilt version use:
#docker run -it -p 8888:8888 gpflow/gpflow

#To replicate build use:
#docker build -t gpflow/gpflow .
#Assumes you are running from within cloned repo.

#Uses official Tensorflow docker for cpu only.
FROM tensorflow/tensorflow:1.0.0
COPY ./ /usr/local/GPflow/
RUN cd /usr/local/GPflow && \
    python setup.py develop && \
    rm /notebooks/*  && \
    apt-get clean  && \
    rm -rf /var/lib/apt/lists/*
COPY doc/source/notebooks/ LICENSE README.md /notebooks/
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