Bump to version 0.1.0 and prepare for release (#287)

.gitignore

@@ -15,6 +15,7 @@ pyro/contrib/examples/raw
 pyro/_version.py
 processed
 raw
+prep_seal_data.csv
 
 # Logs
 logs

.travis.yml

@@ -17,6 +17,9 @@ install:
     # Keep track of Pyro dev branch
     - pip install https://github.com/pyro-ppl/pyro/archive/dev.zip
 
+    # Keep track of pyro-api master branch
+    - pip install https://github.com/pyro-ppl/pyro-api/archive/master.zip
+
     - pip install .[test]
     - pip freeze
 

README.md

@@ -1,5 +1,5 @@
-![unstable](https://img.shields.io/badge/status-unstable-red.svg)
 [![Build Status](https://travis-ci.com/pyro-ppl/funsor.svg?branch=master)](https://travis-ci.com/pyro-ppl/funsor)
+[![Latest Version](https://badge.fury.io/py/funsor.svg)](https://pypi.python.org/pypi/funsor)
 [![Documentation Status](https://readthedocs.org/projects/funsor/badge)](http://funsor.readthedocs.io)
 
 # Funsor
@@ -17,7 +17,7 @@ for a system description.
 Funsor supports Python 3.6+.
 
 ```sh
-pip install funsor@https://api.github.com/repos/pyro-ppl/funsor/tarball/master
+pip install funsor
 ```
 
 **Install from source:**

docs/requirements.txt

@@ -1,4 +1,3 @@
-contextlib2
 multipledispatch
 numpy>=1.7
 opt_einsum>=2.3.2

examples/eeg_slds.py

@@ -8,10 +8,10 @@
 [1] Anderson, B., and J. Moore. "Optimal filtering. Prentice-Hall, Englewood Cliffs." New Jersey (1979).
 """
 import argparse
-from os.path import exists
-from urllib.request import urlopen
 import time
 from collections import OrderedDict
+from os.path import exists
+from urllib.request import urlopen
 
 import numpy as np
 import torch
@@ -20,7 +20,7 @@
 import funsor
 import funsor.distributions as dist
 import funsor.ops as ops
-from funsor.pyro.convert import matrix_and_mvn_to_funsor, mvn_to_funsor, funsor_to_cat_and_mvn, funsor_to_mvn
+from funsor.pyro.convert import funsor_to_cat_and_mvn, funsor_to_mvn, matrix_and_mvn_to_funsor, mvn_to_funsor
 
 
 # download dataset from UCI archive

examples/mixed_hmm/experiment.py

@@ -1,23 +1,20 @@
 import argparse
-import os
+import functools
 import json
+import os
 import uuid
-import functools
-
-import torch
 
 import pyro
 import pyro.poutine as poutine
+import torch
 
 import funsor.ops as ops
 from funsor.interpreter import interpretation
 from funsor.optimizer import apply_optimizer
 from funsor.sum_product import MarkovProduct, naive_sequential_sum_product, sum_product
 from funsor.terms import lazy, to_funsor
-
-
-from model import Model, Guide
-from seal_data import prepare_seal, prepare_fake
+from model import Guide, Model
+from seal_data import prepare_fake, prepare_seal
 
 
 def aic_num_parameters(model, guide=None):

examples/mixed_hmm/model.py

@@ -1,10 +1,9 @@
 from collections import OrderedDict
 
+import pyro
 import torch
 from torch.distributions import constraints
 
-import pyro
-
 import funsor.distributions as dist
 import funsor.ops as ops
 from funsor.domains import bint, reals

examples/mixed_hmm/seal_data.py

@@ -2,10 +2,8 @@
 from urllib.request import urlopen
 
 import pandas as pd
-
 import torch
 
-
 MISSING = 1e-6
 
 

funsor/adjoint.py

@@ -10,19 +10,7 @@
 from funsor.interpreter import interpretation
 from funsor.ops import AssociativeOp
 from funsor.registry import KeyedRegistry
-from funsor.terms import (
-    Binary,
-    Cat,
-    Funsor,
-    Number,
-    Reduce,
-    Slice,
-    Subs,
-    Variable,
-    reflect,
-    substitute,
-    to_funsor,
-)
+from funsor.terms import Binary, Cat, Funsor, Number, Reduce, Slice, Subs, Variable, reflect, substitute, to_funsor
 from funsor.torch import Tensor, materialize
 
 

funsor/einsum.py

@@ -7,7 +7,6 @@
 from funsor.sum_product import sum_product
 from funsor.terms import Funsor, lazy
 
-
 BACKEND_OPS = {
     "torch": (ops.add, ops.mul),
     "pyro.ops.einsum.torch_log": (ops.logaddexp, ops.add),

funsor/interpreter.py

@@ -4,11 +4,11 @@
 import re
 import types
 from collections import OrderedDict
+from contextlib import contextmanager
 from functools import singledispatch
 
 import numpy
 import torch
-from contextlib2 import contextmanager
 
 from funsor.domains import Domain
 from funsor.ops import Op

funsor/memoize.py

@@ -1,5 +1,5 @@
 from collections import Hashable
-from contextlib2 import contextmanager
+from contextlib import contextmanager
 
 import funsor.interpreter as interpreter
 

funsor/montecarlo.py

@@ -1,6 +1,5 @@
 from collections import OrderedDict
-
-from contextlib2 import contextmanager
+from contextlib import contextmanager
 
 from funsor.integrate import Integrate
 from funsor.interpreter import dispatched_interpretation, interpretation

funsor/torch.py

@@ -2,11 +2,11 @@
 import itertools
 import warnings
 from collections import OrderedDict
+from contextlib import contextmanager
 from functools import reduce
 
 import opt_einsum
 import torch
-from contextlib2 import contextmanager
 from multipledispatch import dispatch
 from multipledispatch.variadic import Variadic
 

setup.py

@@ -1,19 +1,39 @@
+import sys
+
 from setuptools import find_packages, setup
 
+# READ README.md for long description on PyPi.
+# This requires uploading via twine, e.g.:
+# $ python setup.py sdist bdist_wheel
+# $ twine upload --repository-url https://test.pypi.org/legacy/ dist/*  # test version
+# $ twine upload dist/*
+try:
+    long_description = open('README.md', encoding='utf-8').read()
+except Exception as e:
+    sys.stderr.write(f'Failed to convert README.md to rst:\n  {e}\n')
+    sys.stderr.flush()
+    long_description = ''
+
+# Remove badges since they will always be obsolete.
+# This assumes the first 4 lines contain badge info.
+long_description = '\n'.join(line for line in long_description.split('\n')[4:])
+
 setup(
     name='funsor',
-    version='0.0.0',
-    description='Functional analysis + tensors + symbolic algebra',
+    version='0.1.0',
+    description='A tensor-like library for functions and distributions',
     packages=find_packages(include=['funsor', 'funsor.*']),
     url='https://github.com/pyro-ppl/funsor',
+    project_urls={
+        "Documentation": "https://funsor.pyro.ai",
+    },
     author='Uber AI Labs',
     author_email='[email protected]',
     install_requires=[
-        'contextlib2',
         'multipledispatch',
         'numpy>=1.7',
         'opt_einsum>=2.3.2',
-        'pyro-ppl>=0.3',
+        'pyro-ppl>=0.5',
         'torch>=1.3.0',
     ],
     extras_require={
@@ -23,7 +43,7 @@
             'pytest>=4.1',
             'pytest-xdist==1.27.0',
             'torchvision==0.2.1',
-            'pyro-api@https://api.github.com/repos/pyro-ppl/pyro-api/tarball/master',
+            'pyro-api>=0.1',
         ],
         'dev': [
             'flake8',
@@ -36,7 +56,8 @@
             'torchvision==0.2.1',
         ],
     },
-    tests_require=['flake8', 'pandas', 'pytest>=4.1'],
+    long_description=long_description,
+    long_description_content_type='text/markdown',
     keywords='probabilistic machine learning bayesian statistics pytorch',
     classifiers=[
         'Intended Audience :: Developers',

test/test_adjoint.py

@@ -12,12 +12,7 @@
 from funsor.einsum import BACKEND_ADJOINT_OPS, einsum, naive_einsum, naive_plated_einsum
 from funsor.interpreter import interpretation
 from funsor.optimizer import apply_optimizer
-from funsor.sum_product import (
-    MarkovProduct,
-    naive_sequential_sum_product,
-    sequential_sum_product,
-    sum_product
-)
+from funsor.sum_product import MarkovProduct, naive_sequential_sum_product, sequential_sum_product, sum_product
 from funsor.terms import Variable, reflect
 from funsor.testing import (
     assert_close,
@@ -26,10 +21,9 @@
     make_plated_hmm_einsum,
     random_gaussian,
     random_tensor,
-    xfail_param,
+    xfail_param
 )
 
-
 EINSUM_EXAMPLES = [
     "a->",
     "ab->",

test/test_joint.py

@@ -6,7 +6,7 @@
 
 import funsor.ops as ops
 from funsor.cnf import Contraction
-from funsor.delta import Delta, Delta
+from funsor.delta import Delta
 from funsor.domains import bint, reals
 from funsor.gaussian import Gaussian
 from funsor.integrate import Integrate

test/test_memoize.py

@@ -9,7 +9,6 @@
 from funsor.terms import reflect
 from funsor.testing import make_einsum_example, xfail_param
 
-
 EINSUM_EXAMPLES = [
     ("a,b->", ''),
     ("ab,a->", ''),

test/test_optimizer.py

@@ -1,8 +1,8 @@
 from collections import OrderedDict
 
-from pyro.ops.contract import einsum as pyro_einsum
 import pytest
 import torch
+from pyro.ops.contract import einsum as pyro_einsum
 
 import funsor
 from funsor.distributions import Categorical

test/test_torch.py

@@ -10,7 +10,7 @@
 from funsor.interpreter import interpretation
 from funsor.terms import Cat, Lambda, Number, Slice, Stack, Variable, lazy
 from funsor.testing import assert_close, assert_equiv, check_funsor, random_tensor
-from funsor.torch import REDUCE_OP_TO_TORCH, Einsum, Tensor, arange, align_tensors, torch_stack, torch_tensordot
+from funsor.torch import REDUCE_OP_TO_TORCH, Einsum, Tensor, align_tensors, arange, torch_stack, torch_tensordot
 
 
 @pytest.mark.parametrize('output_shape', [(), (2,), (3, 2)], ids=str)