We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Update tensorflow-probability to the next release that includes continuous approximations
# Description

This is a follow up to #302. As the bug is fixed in upstream tensorflow-probability, we just need to wait for a new release to be shipped.

This bug was because of a change in the API to get rid of the continuous approximation to the Poisson pmf which broke our tests.

### Describe the solution you'd like

Unfix tensorflow-probability to `0.3.0` and bump to the next available release post-0.4.0.
Update Tensorflow to TensorFlow 1.12.0 release
# Description

[TensorFlow 1.12.0 has been released](https://github.com/tensorflow/tensorflow/releases/tag/v1.12.0) and it has breaking changes. Most notably

> Remove `tf.contrib.linalg`. `tf.linalg` should be used instead. 

Once there is a new release of TensorFlow probability (`v0.5.0` &mdash; c.f. Issue #360 and #330) that upgrades to `v1.12.0` then we can follow them in upgrading.


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `setup.py`
Content:
```
1 #!/usr/bin/env python
2 
3 from setuptools import setup, find_packages
4 from os import path
5 import sys
6 
7 this_directory = path.abspath(path.dirname(__file__))
8 if sys.version_info.major < 3:
9     from io import open
10 with open(path.join(this_directory, 'README.md'), encoding='utf-8') as readme_md:
11     long_description = readme_md.read()
12 
13 extras_require = {
14     'tensorflow': [
15         'tensorflow<1.12.0,>=1.10.0',
16         'tensorflow-probability==0.3.0',
17         'numpy<=1.14.5,>=1.14.0',  # Lower of 1.14.0 instead of 1.13.3 to ensure doctest pass
18         'setuptools<=39.1.0',
19     ],
20     'torch': ['torch>=0.4.0'],
21     'mxnet': [
22         'mxnet>=1.0.0',
23         'requests<2.19.0,>=2.18.4',
24         'numpy<1.15.0,>=1.8.2',
25         'requests<2.19.0,>=2.18.4',
26     ],
27     # 'dask': [
28     #     'dask[array]'
29     # ],
30     'xmlimport': ['uproot'],
31     'minuit': ['iminuit'],
32     'develop': [
33         'pyflakes',
34         'pytest<4.0.0,>=3.5.1',
35         'pytest-cov>=2.5.1',
36         'pytest-mock',
37         'pytest-benchmark[histogram]',
38         'pytest-console-scripts',
39         'python-coveralls',
40         'coverage>=4.0',  # coveralls
41         'matplotlib',
42         'jupyter',
43         'nbdime',
44         'uproot>=3.0.0',
45         'papermill>=0.16.0',
46         'graphviz',
47         'bumpversion',
48         'sphinx',
49         'sphinxcontrib-bibtex',
50         'sphinxcontrib-napoleon',
51         'sphinx_rtd_theme',
52         'nbsphinx',
53         'sphinx-issues',
54         'm2r',
55         'jsonpatch',
56         'ipython<7',  # jupyter_console and ipython clash in dependency requirement -- downgrade ipython for now
57         'pre-commit',
58         'black;python_version>="3.6"',  # Black is Python3 only
59         'twine',
60     ],
61 }
62 extras_require['complete'] = sorted(set(sum(extras_require.values(), [])))
63 
64 setup(
65     name='pyhf',
66     version='0.0.15',
67     description='(partial) pure python histfactory implementation',
68     long_description=long_description,
69     long_description_content_type='text/markdown',
70     url='https://github.com/diana-hep/pyhf',
71     author='Lukas Heinrich',
72     author_email='lukas.heinrich@cern.ch',
73     license='Apache',
74     keywords='physics fitting numpy scipy tensorflow pytorch mxnet dask',
75     classifiers=[
76         "Programming Language :: Python :: 2",
77         "Programming Language :: Python :: 2.7",
78         "Programming Language :: Python :: 3",
79         "Programming Language :: Python :: 3.6",
80     ],
81     packages=find_packages(),
82     include_package_data=True,
83     python_requires=">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*",
84     install_requires=[
85         'scipy',  # requires numpy, which is required by pyhf, tensorflow, and mxnet
86         'click>=6.0',  # for console scripts,
87         'tqdm',  # for readxml
88         'six',  # for modifiers
89         'jsonschema>=v3.0.0a2',  # for utils, alpha-release for draft 6
90         'jsonpatch',
91     ],
92     extras_require=extras_require,
93     entry_points={'console_scripts': ['pyhf=pyhf.commandline:pyhf']},
94     dependency_links=[],
95 )
96
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/setup.py b/setup.py
--- a/setup.py
+++ b/setup.py
@@ -12,8 +12,8 @@
 
 extras_require = {
     'tensorflow': [
-        'tensorflow<1.12.0,>=1.10.0',
-        'tensorflow-probability==0.3.0',
+        'tensorflow>=1.12.0',
+        'tensorflow-probability>=0.5.0',
         'numpy<=1.14.5,>=1.14.0',  # Lower of 1.14.0 instead of 1.13.3 to ensure doctest pass
         'setuptools<=39.1.0',
     ],

{"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -12,8 +12,8 @@\n \n extras_require = {\n     'tensorflow': [\n-        'tensorflow<1.12.0,>=1.10.0',\n-        'tensorflow-probability==0.3.0',\n+        'tensorflow>=1.12.0',\n+        'tensorflow-probability>=0.5.0',\n         'numpy<=1.14.5,>=1.14.0',  # Lower of 1.14.0 instead of 1.13.3 to ensure doctest pass\n         'setuptools<=39.1.0',\n     ],\n", "issue": "Update tensorflow-probability to the next release that includes continuous approximations\n# Description\r\n\r\nThis is a follow up to #302. As the bug is fixed in upstream tensorflow-probability, we just need to wait for a new release to be shipped.\r\n\r\nThis bug was because of a change in the API to get rid of the continuous approximation to the Poisson pmf which broke our tests.\r\n\r\n### Describe the solution you'd like\r\n\r\nUnfix tensorflow-probability to `0.3.0` and bump to the next available release post-0.4.0.\nUpdate Tensorflow to TensorFlow 1.12.0 release\n# Description\r\n\r\n[TensorFlow 1.12.0 has been released](https://github.com/tensorflow/tensorflow/releases/tag/v1.12.0) and it has breaking changes. Most notably\r\n\r\n> Remove `tf.contrib.linalg`. `tf.linalg` should be used instead. \r\n\r\nOnce there is a new release of TensorFlow probability (`v0.5.0` &mdash; c.f. Issue #360 and #330) that upgrades to `v1.12.0` then we can follow them in upgrading.\r\n\n", "before_files": [{"content": "#!/usr/bin/env python\n\nfrom setuptools import setup, find_packages\nfrom os import path\nimport sys\n\nthis_directory = path.abspath(path.dirname(__file__))\nif sys.version_info.major < 3:\n    from io import open\nwith open(path.join(this_directory, 'README.md'), encoding='utf-8') as readme_md:\n    long_description = readme_md.read()\n\nextras_require = {\n    'tensorflow': [\n        'tensorflow<1.12.0,>=1.10.0',\n        'tensorflow-probability==0.3.0',\n        'numpy<=1.14.5,>=1.14.0',  # Lower of 1.14.0 instead of 1.13.3 to ensure doctest pass\n        'setuptools<=39.1.0',\n    ],\n    'torch': ['torch>=0.4.0'],\n    'mxnet': [\n        'mxnet>=1.0.0',\n        'requests<2.19.0,>=2.18.4',\n        'numpy<1.15.0,>=1.8.2',\n        'requests<2.19.0,>=2.18.4',\n    ],\n    # 'dask': [\n    #     'dask[array]'\n    # ],\n    'xmlimport': ['uproot'],\n    'minuit': ['iminuit'],\n    'develop': [\n        'pyflakes',\n        'pytest<4.0.0,>=3.5.1',\n        'pytest-cov>=2.5.1',\n        'pytest-mock',\n        'pytest-benchmark[histogram]',\n        'pytest-console-scripts',\n        'python-coveralls',\n        'coverage>=4.0',  # coveralls\n        'matplotlib',\n        'jupyter',\n        'nbdime',\n        'uproot>=3.0.0',\n        'papermill>=0.16.0',\n        'graphviz',\n        'bumpversion',\n        'sphinx',\n        'sphinxcontrib-bibtex',\n        'sphinxcontrib-napoleon',\n        'sphinx_rtd_theme',\n        'nbsphinx',\n        'sphinx-issues',\n        'm2r',\n        'jsonpatch',\n        'ipython<7',  # jupyter_console and ipython clash in dependency requirement -- downgrade ipython for now\n        'pre-commit',\n        'black;python_version>=\"3.6\"',  # Black is Python3 only\n        'twine',\n    ],\n}\nextras_require['complete'] = sorted(set(sum(extras_require.values(), [])))\n\nsetup(\n    name='pyhf',\n    version='0.0.15',\n    description='(partial) pure python histfactory implementation',\n    long_description=long_description,\n    long_description_content_type='text/markdown',\n    url='https://github.com/diana-hep/pyhf',\n    author='Lukas Heinrich',\n    author_email='lukas.heinrich@cern.ch',\n    license='Apache',\n    keywords='physics fitting numpy scipy tensorflow pytorch mxnet dask',\n    classifiers=[\n        \"Programming Language :: Python :: 2\",\n        \"Programming Language :: Python :: 2.7\",\n        \"Programming Language :: Python :: 3\",\n        \"Programming Language :: Python :: 3.6\",\n    ],\n    packages=find_packages(),\n    include_package_data=True,\n    python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*\",\n    install_requires=[\n        'scipy',  # requires numpy, which is required by pyhf, tensorflow, and mxnet\n        'click>=6.0',  # for console scripts,\n        'tqdm',  # for readxml\n        'six',  # for modifiers\n        'jsonschema>=v3.0.0a2',  # for utils, alpha-release for draft 6\n        'jsonpatch',\n    ],\n    extras_require=extras_require,\n    entry_points={'console_scripts': ['pyhf=pyhf.commandline:pyhf']},\n    dependency_links=[],\n)\n", "path": "setup.py"}], "after_files": [{"content": "#!/usr/bin/env python\n\nfrom setuptools import setup, find_packages\nfrom os import path\nimport sys\n\nthis_directory = path.abspath(path.dirname(__file__))\nif sys.version_info.major < 3:\n    from io import open\nwith open(path.join(this_directory, 'README.md'), encoding='utf-8') as readme_md:\n    long_description = readme_md.read()\n\nextras_require = {\n    'tensorflow': [\n        'tensorflow>=1.12.0',\n        'tensorflow-probability>=0.5.0',\n        'numpy<=1.14.5,>=1.14.0',  # Lower of 1.14.0 instead of 1.13.3 to ensure doctest pass\n        'setuptools<=39.1.0',\n    ],\n    'torch': ['torch>=0.4.0'],\n    'mxnet': [\n        'mxnet>=1.0.0',\n        'requests<2.19.0,>=2.18.4',\n        'numpy<1.15.0,>=1.8.2',\n        'requests<2.19.0,>=2.18.4',\n    ],\n    # 'dask': [\n    #     'dask[array]'\n    # ],\n    'xmlimport': ['uproot'],\n    'minuit': ['iminuit'],\n    'develop': [\n        'pyflakes',\n        'pytest<4.0.0,>=3.5.1',\n        'pytest-cov>=2.5.1',\n        'pytest-mock',\n        'pytest-benchmark[histogram]',\n        'pytest-console-scripts',\n        'python-coveralls',\n        'coverage>=4.0',  # coveralls\n        'matplotlib',\n        'jupyter',\n        'nbdime',\n        'uproot>=3.0.0',\n        'papermill>=0.16.0',\n        'graphviz',\n        'bumpversion',\n        'sphinx',\n        'sphinxcontrib-bibtex',\n        'sphinxcontrib-napoleon',\n        'sphinx_rtd_theme',\n        'nbsphinx',\n        'sphinx-issues',\n        'm2r',\n        'jsonpatch',\n        'ipython<7',  # jupyter_console and ipython clash in dependency requirement -- downgrade ipython for now\n        'pre-commit',\n        'black;python_version>=\"3.6\"',  # Black is Python3 only\n        'twine',\n    ],\n}\nextras_require['complete'] = sorted(set(sum(extras_require.values(), [])))\n\nsetup(\n    name='pyhf',\n    version='0.0.15',\n    description='(partial) pure python histfactory implementation',\n    long_description=long_description,\n    long_description_content_type='text/markdown',\n    url='https://github.com/diana-hep/pyhf',\n    author='Lukas Heinrich',\n    author_email='lukas.heinrich@cern.ch',\n    license='Apache',\n    keywords='physics fitting numpy scipy tensorflow pytorch mxnet dask',\n    classifiers=[\n        \"Programming Language :: Python :: 2\",\n        \"Programming Language :: Python :: 2.7\",\n        \"Programming Language :: Python :: 3\",\n        \"Programming Language :: Python :: 3.6\",\n    ],\n    packages=find_packages(),\n    include_package_data=True,\n    python_requires=\">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*\",\n    install_requires=[\n        'scipy',  # requires numpy, which is required by pyhf, tensorflow, and mxnet\n        'click>=6.0',  # for console scripts,\n        'tqdm',  # for readxml\n        'six',  # for modifiers\n        'jsonschema>=v3.0.0a2',  # for utils, alpha-release for draft 6\n        'jsonpatch',\n    ],\n    extras_require=extras_require,\n    entry_points={'console_scripts': ['pyhf=pyhf.commandline:pyhf']},\n    dependency_links=[],\n)\n", "path": "setup.py"}]}