[WIP] Edward 2.0

docker/Dockerfile

@@ -42,7 +42,7 @@ USER edward
 ARG python_version=3.5.3-0
 ARG python_qt_version=4
 RUN conda install -y python=${python_version} && \
-    pip install observations numpy six tensorflow keras prettytensor && \
+    pip install observations numpy six tensorflow keras && \
     pip install ipdb pytest pytest-cov python-coveralls coverage==3.7.1 pytest-xdist pep8 pytest-pep8 pydot_ng && \
     conda install Pillow scikit-learn matplotlib notebook pandas seaborn pyyaml h5py && \
     conda install -y pyqt=${python_qt_version} && \

docker/Dockerfile-gpu

@@ -42,7 +42,7 @@ USER edward
 # Python
 ARG python_version=3.5.3-0
 RUN conda install -y python=${python_version} && \
-    pip install observations numpy six tensorflow-gpu keras prettytensor && \
+    pip install observations numpy six tensorflow-gpu keras && \
     pip install ipdb pytest pytest-cov python-coveralls coverage==3.7.1 pytest-xdist pep8 pytest-pep8 pydot_ng && \
     conda install Pillow scikit-learn matplotlib notebook pandas seaborn pyyaml h5py && \
     pip install edward && \

docs/tex/bib.bib

@@ -484,6 +484,13 @@ @inproceedings{welling2011bayesian
 year = {2011}
 }
 
+@inproceedings{wingate2011lightweight,
+  title={Lightweight implementations of probabilistic programming languages via transformational compilation},
+  author={Wingate, David and Stuhlmueller, Andreas and Goodman, Noah},
+  booktitle={Artificial Intelligence and Statistics},
+  year={2011}
+}
+
 @inproceedings{goodman2012church,
 author = {Goodman, Noah and Mansinghka, Vikash and Roy, Daniel M and Bonawitz, Keith and Tenenbaum, Joshua B},
 title = {{Church: a language for generative models}},
@@ -720,6 +727,13 @@ @article{johnson2016composing
   year = {2016},
 }
 
+@inproceedings{li2016preconditioned,
+  title={Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks.},
+  author={Li, Chunyuan and Chen, Changyou and Carlson, David E and Carin, Lawrence},
+  booktitle={Association for the Advancement of Artificial Intelligence},
+  year={2016}
+}
+
 @article{mohamed2016learning,
 author = {Mohamed, Shakir and Lakshminarayanan, Balaji},
 title = {{Learning in Implicit Generative Models}},

edward/__init__.py

@@ -2,94 +2,80 @@
 from __future__ import division
 from __future__ import print_function
 
-from edward import criticisms
 from edward import inferences
 from edward import models
-from edward import util
 
 # Direct imports for convenience
-from edward.criticisms import (
-    evaluate, ppc, ppc_density_plot, ppc_stat_hist_plot)
 from edward.inferences import (
-    Inference, MonteCarlo, VariationalInference,
-    HMC, MetropolisHastings, SGLD, SGHMC,
-    KLpq, KLqp, ReparameterizationKLqp, ReparameterizationKLKLqp,
-    ReparameterizationEntropyKLqp, ScoreKLqp, ScoreKLKLqp, ScoreEntropyKLqp,
-    ScoreRBKLqp, WakeSleep, GANInference, BiGANInference, WGANInference,
-    ImplicitKLqp, MAP, Laplace, complete_conditional, Gibbs)
-from edward.models import RandomVariable
-from edward.util import (
-    check_data, check_latent_vars, copy, dot,
-    get_ancestors, get_blanket, get_children, get_control_variate_coef,
-    get_descendants, get_parents, get_session, get_siblings, get_variables,
-    is_independent, Progbar, random_variables, rbf, set_seed,
-    to_simplex, transform)
+    bigan_inference,
+    complete_conditional,
+    gan_inference,
+    hmc,
+    klpq,
+    klqp,
+    klqp_implicit,
+    klqp_reparameterization,
+    klqp_reparameterization_kl,
+    klqp_score,
+    laplace,
+    map,
+    metropolis_hastings,
+    sghmc,
+    sgld,
+    wake_sleep,
+    wgan_inference)
+from edward.models import (
+    call_with_manipulate,
+    get_ancestors,
+    get_blanket,
+    get_children,
+    get_descendants,
+    get_parents,
+    get_siblings,
+    get_variables,
+    is_independent,
+    random_variables)
 from edward.version import __version__, VERSION
 
 from tensorflow.python.util.all_util import remove_undocumented
 
 # Export modules and constants.
 _allowed_symbols = [
-    'criticisms',
     'inferences',
     'models',
-    'util',
-    'evaluate',
-    'ppc',
-    'ppc_density_plot',
-    'ppc_stat_hist_plot',
-    'Inference',
-    'MonteCarlo',
-    'VariationalInference',
-    'HMC',
-    'MetropolisHastings',
-    'SGLD',
-    'SGHMC',
-    'KLpq',
-    'KLqp',
-    'ReparameterizationKLqp',
-    'ReparameterizationKLKLqp',
-    'ReparameterizationEntropyKLqp',
-    'ScoreKLqp',
-    'ScoreKLKLqp',
-    'ScoreEntropyKLqp',
-    'ScoreRBKLqp',
-    'WakeSleep',
-    'GANInference',
-    'BiGANInference',
-    'WGANInference',
-    'ImplicitKLqp',
-    'MAP',
-    'Laplace',
+    'bigan_inference',
+    'call_with_manipulate',
     'complete_conditional',
-    'Gibbs',
-    'RandomVariable',
-    'check_data',
-    'check_latent_vars',
-    'copy',
-    'dot',
+    'gan_inference',
+    'hmc',
+    'klpq',
+    'klqp',
+    'klqp_implicit',
+    'klqp_reparameterization',
+    'klqp_reparameterization_kl',
+    'klqp_score',
+    'laplace',
+    'map',
+    'metropolis_hastings',
+    'sghmc',
+    'sgld',
+    'wake_sleep',
+    'wgan_inference',
     'get_ancestors',
     'get_blanket',
     'get_children',
-    'get_control_variate_coef',
     'get_descendants',
     'get_parents',
-    'get_session',
     'get_siblings',
     'get_variables',
     'is_independent',
-    'Progbar',
     'random_variables',
-    'rbf',
-    'set_seed',
-    'to_simplex',
-    'transform',
     '__version__',
     'VERSION',
 ]
 
 # Remove all extra symbols that don't have a docstring or are not explicitly
 # referenced in the whitelist.
 remove_undocumented(__name__, _allowed_symbols, [
-    criticisms, inferences, models, util
+    inferences, models
 ])