From 72530065eca89788ee27b979c64eda5502a3ddae Mon Sep 17 00:00:00 2001 From: rcabanasdepaz Date: Fri, 3 Aug 2018 12:20:22 +0200 Subject: [PATCH] preparing 0.1.2 --- README.rst | 4 ++-- docs/index.rst | 4 ++-- docs/notes/guidebayesian.rst | 2 +- docs/notes/guidemodels.rst | 2 +- setup.py | 4 ++-- 5 files changed, 8 insertions(+), 8 deletions(-) diff --git a/README.rst b/README.rst index caa8333..ce3eedd 100644 --- a/README.rst +++ b/README.rst @@ -7,14 +7,14 @@ :scale: 90 % :align: center -InferPy: Deep Probabilistic Modelling Made Easy +InferPy: Deep Probabilistic Modeling Made Easy =============================================== InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top of Edward and Tensorflow. InferPy's API is strongly inspired by Keras and it has a focus on enabling flexible data processing, -easy-to-code probablistic modelling, scalable inference and robust model validation. +easy-to-code probablistic modeling, scalable inference and robust model validation. Use InferPy is you need a probabilistic programming language that: diff --git a/docs/index.rst b/docs/index.rst index 458551b..cefe52f 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -3,7 +3,7 @@ You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. -InferPy: Probabilistic Modelling with Tensorflow Made Easy +InferPy: Probabilistic Modeling with Tensorflow Made Easy ========================================================== .. image:: _static/img/logo.png @@ -15,7 +15,7 @@ InferPy: Probabilistic Modelling with Tensorflow Made Easy InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top of Tensorflow. InferPy's API is strongly inspired by Keras and it has a focus on enabling flexible data processing, -easy-to-code probablistic modelling, scalable inference and robust model validation. +easy-to-code probablistic modeling, scalable inference and robust model validation. Use InferPy if you need a probabilistic programming language that: diff --git a/docs/notes/guidebayesian.rst b/docs/notes/guidebayesian.rst index 26550e0..5b1693c 100644 --- a/docs/notes/guidebayesian.rst +++ b/docs/notes/guidebayesian.rst @@ -17,7 +17,7 @@ Bayesian deep learning or deep probabilistic programming enbraces the idea of employing deep neural networks within a probabilistic model in order to capture complex non-linear dependencies between variables. -InferPy's API gives support to this powerful and flexible modelling +InferPy's API gives support to this powerful and flexible modeling framework. Let us start by showing how a variational autoencoder over binary data can be defined by mixing Keras and InferPy code. diff --git a/docs/notes/guidemodels.rst b/docs/notes/guidemodels.rst index 2edd350..d8f1b23 100644 --- a/docs/notes/guidemodels.rst +++ b/docs/notes/guidemodels.rst @@ -517,7 +517,7 @@ where the input parameter ``loc`` and ``scale`` correspond to :math:`\mu` and :m Poisson ~~~~~~~~~~~~~~~ -The Poisson distribution is a discrete probability distribution for modelling the number of times an event occurs +The Poisson distribution is a discrete probability distribution for modeling the number of times an event occurs in an interval of time or space. Its probability mass function is diff --git a/setup.py b/setup.py index 05c3968..4b87bd9 100644 --- a/setup.py +++ b/setup.py @@ -10,12 +10,12 @@ setup( name='inferpy', version=__version__, - description='Probabilistic modelling with Tensorflow made easy', + description='Probabilistic modeling with Tensorflow made easy', author='Andrés R. Masegosa, Rafael Cabañas', author_email="andresma@ual.es, rcabanas@ual.es", packages=['inferpy', 'inferpy.models', 'inferpy.util', 'inferpy.criticism', 'inferpy.inferences' ], - install_requires=['numpy>=1.7', 'tensorflow>=1.2.0rc0'], + install_requires=['numpy>=1.7', 'tensorflow >=1.2.0rc0, <1.8'], extras_require={ 'tensorflow with gpu': ['tensorflow-gpu>=1.2.0rc0'], 'visualization': ['matplotlib>=1.3',