We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Revert #961 before release
Tensorflow version temporarily has an upper bound (`tensorflow<2.16.0`) in requirements-dev.txt.
scikit-learn version temporarily has an upper bound (`scikit-learn>=1.0,<1.4.0`) in setup.py

This needs to be reverted before releasing v2.6.0.


 _Originally posted by @elisno in https://github.com/cleanlab/cleanlab/issues/961#issuecomment-1898968097_
            

--- 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 from setuptools import setup, find_packages
2 from setuptools.command.egg_info import egg_info
3 
4 # To use a consistent encoding
5 from codecs import open
6 from os import path
7 
8 
9 class egg_info_ex(egg_info):
10     """Includes license file into `.egg-info` folder."""
11 
12     def run(self):
13         # don't duplicate license into `.egg-info` when building a distribution
14         if not self.distribution.have_run.get("install", True):
15             # `install` command is in progress, copy license
16             self.mkpath(self.egg_info)
17             self.copy_file("LICENSE", self.egg_info)
18 
19         egg_info.run(self)
20 
21 
22 here = path.abspath(path.dirname(__file__))
23 
24 # Get the long description from the README file
25 with open(path.join(here, "README.md"), encoding="utf-8") as f:
26     long_description = f.read()
27 
28 # Get version number and store it in __version__
29 exec(open("cleanlab/version.py").read())
30 
31 DATALAB_REQUIRE = [
32     # Mainly for Datalab's data storage class.
33     # Still some type hints that require datasets
34     "datasets>=2.7.0",
35 ]
36 
37 IMAGE_REQUIRE = DATALAB_REQUIRE + ["cleanvision>=0.3.2"]
38 
39 EXTRAS_REQUIRE = {
40     "datalab": DATALAB_REQUIRE,
41     "image": IMAGE_REQUIRE,
42     "all": ["matplotlib>=3.5.1"],
43 }
44 EXTRAS_REQUIRE["all"] = list(set(sum(EXTRAS_REQUIRE.values(), [])))
45 
46 setup(
47     name="cleanlab",
48     version=__version__,
49     license="AGPLv3+",
50     long_description=long_description,
51     long_description_content_type="text/markdown",
52     description="The standard package for data-centric AI, machine learning with label errors, "
53     "and automatically finding and fixing dataset issues in Python.",
54     url="https://cleanlab.ai",
55     project_urls={
56         "Documentation": "https://docs.cleanlab.ai",
57         "Bug Tracker": "https://github.com/cleanlab/cleanlab/issues",
58         "Source Code": "https://github.com/cleanlab/cleanlab",
59     },
60     author="Cleanlab Inc.",
61     author_email="team@cleanlab.ai",
62     # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
63     classifiers=[
64         "Development Status :: 4 - Beta",
65         "Intended Audience :: Developers",
66         "Intended Audience :: Education",
67         "Intended Audience :: Science/Research",
68         "Intended Audience :: Information Technology",
69         "License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",
70         "Natural Language :: English",
71         # We believe this package works will these versions, but we do not guarantee it!
72         "Programming Language :: Python :: 3",
73         "Programming Language :: Python :: 3.7",
74         "Programming Language :: Python :: 3.8",
75         "Programming Language :: Python :: 3.9",
76         "Programming Language :: Python :: 3.10",
77         "Programming Language :: Python",
78         "Topic :: Software Development",
79         "Topic :: Scientific/Engineering",
80         "Topic :: Scientific/Engineering :: Mathematics",
81         "Topic :: Scientific/Engineering :: Artificial Intelligence",
82         "Topic :: Software Development :: Libraries",
83         "Topic :: Software Development :: Libraries :: Python Modules",
84     ],
85     python_requires=">=3.7",
86     # What does your project relate to?
87     keywords="machine_learning data_cleaning confident_learning classification weak_supervision "
88     "learning_with_noisy_labels unsupervised_learning datacentric_ai, datacentric",
89     # You can just specify the packages manually here if your project is
90     # simple. Or you can use find_packages().
91     packages=find_packages(exclude=[]),
92     # Include cleanlab license file.
93     include_package_data=True,
94     package_data={
95         "": ["LICENSE"],
96     },
97     license_files=("LICENSE",),
98     cmdclass={"egg_info": egg_info_ex},
99     # List run-time dependencies here.  These will be installed by pip when
100     # your project is installed. For an analysis of "install_requires" vs pip's
101     # requirements files see:
102     # https://packaging.python.org/en/latest/discussions/install-requires-vs-requirements/
103     install_requires=[
104         "numpy>=1.20.0",
105         "scikit-learn>=1.0,<1.4.0",
106         "tqdm>=4.53.0",
107         "pandas>=1.1.5",
108         "termcolor>=2.0.0,<2.4.0",
109     ],
110     extras_require=EXTRAS_REQUIRE,
111 )
112
```
--- 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
@@ -102,7 +102,7 @@
     # https://packaging.python.org/en/latest/discussions/install-requires-vs-requirements/
     install_requires=[
         "numpy>=1.20.0",
-        "scikit-learn>=1.0,<1.4.0",
+        "scikit-learn>=1.0",
         "tqdm>=4.53.0",
         "pandas>=1.1.5",
         "termcolor>=2.0.0,<2.4.0",

{"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -102,7 +102,7 @@\n     # https://packaging.python.org/en/latest/discussions/install-requires-vs-requirements/\n     install_requires=[\n         \"numpy>=1.20.0\",\n-        \"scikit-learn>=1.0,<1.4.0\",\n+        \"scikit-learn>=1.0\",\n         \"tqdm>=4.53.0\",\n         \"pandas>=1.1.5\",\n         \"termcolor>=2.0.0,<2.4.0\",\n", "issue": "Revert #961 before release\nTensorflow version temporarily has an upper bound (`tensorflow<2.16.0`) in requirements-dev.txt.\r\nscikit-learn version temporarily has an upper bound (`scikit-learn>=1.0,<1.4.0`) in setup.py\r\n\r\nThis needs to be reverted before releasing v2.6.0.\r\n\r\n\r\n _Originally posted by @elisno in https://github.com/cleanlab/cleanlab/issues/961#issuecomment-1898968097_\r\n            \n", "before_files": [{"content": "from setuptools import setup, find_packages\nfrom setuptools.command.egg_info import egg_info\n\n# To use a consistent encoding\nfrom codecs import open\nfrom os import path\n\n\nclass egg_info_ex(egg_info):\n    \"\"\"Includes license file into `.egg-info` folder.\"\"\"\n\n    def run(self):\n        # don't duplicate license into `.egg-info` when building a distribution\n        if not self.distribution.have_run.get(\"install\", True):\n            # `install` command is in progress, copy license\n            self.mkpath(self.egg_info)\n            self.copy_file(\"LICENSE\", self.egg_info)\n\n        egg_info.run(self)\n\n\nhere = path.abspath(path.dirname(__file__))\n\n# Get the long description from the README file\nwith open(path.join(here, \"README.md\"), encoding=\"utf-8\") as f:\n    long_description = f.read()\n\n# Get version number and store it in __version__\nexec(open(\"cleanlab/version.py\").read())\n\nDATALAB_REQUIRE = [\n    # Mainly for Datalab's data storage class.\n    # Still some type hints that require datasets\n    \"datasets>=2.7.0\",\n]\n\nIMAGE_REQUIRE = DATALAB_REQUIRE + [\"cleanvision>=0.3.2\"]\n\nEXTRAS_REQUIRE = {\n    \"datalab\": DATALAB_REQUIRE,\n    \"image\": IMAGE_REQUIRE,\n    \"all\": [\"matplotlib>=3.5.1\"],\n}\nEXTRAS_REQUIRE[\"all\"] = list(set(sum(EXTRAS_REQUIRE.values(), [])))\n\nsetup(\n    name=\"cleanlab\",\n    version=__version__,\n    license=\"AGPLv3+\",\n    long_description=long_description,\n    long_description_content_type=\"text/markdown\",\n    description=\"The standard package for data-centric AI, machine learning with label errors, \"\n    \"and automatically finding and fixing dataset issues in Python.\",\n    url=\"https://cleanlab.ai\",\n    project_urls={\n        \"Documentation\": \"https://docs.cleanlab.ai\",\n        \"Bug Tracker\": \"https://github.com/cleanlab/cleanlab/issues\",\n        \"Source Code\": \"https://github.com/cleanlab/cleanlab\",\n    },\n    author=\"Cleanlab Inc.\",\n    author_email=\"team@cleanlab.ai\",\n    # See https://pypi.python.org/pypi?%3Aaction=list_classifiers\n    classifiers=[\n        \"Development Status :: 4 - Beta\",\n        \"Intended Audience :: Developers\",\n        \"Intended Audience :: Education\",\n        \"Intended Audience :: Science/Research\",\n        \"Intended Audience :: Information Technology\",\n        \"License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)\",\n        \"Natural Language :: English\",\n        # We believe this package works will these versions, but we do not guarantee it!\n        \"Programming Language :: Python :: 3\",\n        \"Programming Language :: Python :: 3.7\",\n        \"Programming Language :: Python :: 3.8\",\n        \"Programming Language :: Python :: 3.9\",\n        \"Programming Language :: Python :: 3.10\",\n        \"Programming Language :: Python\",\n        \"Topic :: Software Development\",\n        \"Topic :: Scientific/Engineering\",\n        \"Topic :: Scientific/Engineering :: Mathematics\",\n        \"Topic :: Scientific/Engineering :: Artificial Intelligence\",\n        \"Topic :: Software Development :: Libraries\",\n        \"Topic :: Software Development :: Libraries :: Python Modules\",\n    ],\n    python_requires=\">=3.7\",\n    # What does your project relate to?\n    keywords=\"machine_learning data_cleaning confident_learning classification weak_supervision \"\n    \"learning_with_noisy_labels unsupervised_learning datacentric_ai, datacentric\",\n    # You can just specify the packages manually here if your project is\n    # simple. Or you can use find_packages().\n    packages=find_packages(exclude=[]),\n    # Include cleanlab license file.\n    include_package_data=True,\n    package_data={\n        \"\": [\"LICENSE\"],\n    },\n    license_files=(\"LICENSE\",),\n    cmdclass={\"egg_info\": egg_info_ex},\n    # List run-time dependencies here.  These will be installed by pip when\n    # your project is installed. For an analysis of \"install_requires\" vs pip's\n    # requirements files see:\n    # https://packaging.python.org/en/latest/discussions/install-requires-vs-requirements/\n    install_requires=[\n        \"numpy>=1.20.0\",\n        \"scikit-learn>=1.0,<1.4.0\",\n        \"tqdm>=4.53.0\",\n        \"pandas>=1.1.5\",\n        \"termcolor>=2.0.0,<2.4.0\",\n    ],\n    extras_require=EXTRAS_REQUIRE,\n)\n", "path": "setup.py"}], "after_files": [{"content": "from setuptools import setup, find_packages\nfrom setuptools.command.egg_info import egg_info\n\n# To use a consistent encoding\nfrom codecs import open\nfrom os import path\n\n\nclass egg_info_ex(egg_info):\n    \"\"\"Includes license file into `.egg-info` folder.\"\"\"\n\n    def run(self):\n        # don't duplicate license into `.egg-info` when building a distribution\n        if not self.distribution.have_run.get(\"install\", True):\n            # `install` command is in progress, copy license\n            self.mkpath(self.egg_info)\n            self.copy_file(\"LICENSE\", self.egg_info)\n\n        egg_info.run(self)\n\n\nhere = path.abspath(path.dirname(__file__))\n\n# Get the long description from the README file\nwith open(path.join(here, \"README.md\"), encoding=\"utf-8\") as f:\n    long_description = f.read()\n\n# Get version number and store it in __version__\nexec(open(\"cleanlab/version.py\").read())\n\nDATALAB_REQUIRE = [\n    # Mainly for Datalab's data storage class.\n    # Still some type hints that require datasets\n    \"datasets>=2.7.0\",\n]\n\nIMAGE_REQUIRE = DATALAB_REQUIRE + [\"cleanvision>=0.3.2\"]\n\nEXTRAS_REQUIRE = {\n    \"datalab\": DATALAB_REQUIRE,\n    \"image\": IMAGE_REQUIRE,\n    \"all\": [\"matplotlib>=3.5.1\"],\n}\nEXTRAS_REQUIRE[\"all\"] = list(set(sum(EXTRAS_REQUIRE.values(), [])))\n\nsetup(\n    name=\"cleanlab\",\n    version=__version__,\n    license=\"AGPLv3+\",\n    long_description=long_description,\n    long_description_content_type=\"text/markdown\",\n    description=\"The standard package for data-centric AI, machine learning with label errors, \"\n    \"and automatically finding and fixing dataset issues in Python.\",\n    url=\"https://cleanlab.ai\",\n    project_urls={\n        \"Documentation\": \"https://docs.cleanlab.ai\",\n        \"Bug Tracker\": \"https://github.com/cleanlab/cleanlab/issues\",\n        \"Source Code\": \"https://github.com/cleanlab/cleanlab\",\n    },\n    author=\"Cleanlab Inc.\",\n    author_email=\"team@cleanlab.ai\",\n    # See https://pypi.python.org/pypi?%3Aaction=list_classifiers\n    classifiers=[\n        \"Development Status :: 4 - Beta\",\n        \"Intended Audience :: Developers\",\n        \"Intended Audience :: Education\",\n        \"Intended Audience :: Science/Research\",\n        \"Intended Audience :: Information Technology\",\n        \"License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)\",\n        \"Natural Language :: English\",\n        # We believe this package works will these versions, but we do not guarantee it!\n        \"Programming Language :: Python :: 3\",\n        \"Programming Language :: Python :: 3.7\",\n        \"Programming Language :: Python :: 3.8\",\n        \"Programming Language :: Python :: 3.9\",\n        \"Programming Language :: Python :: 3.10\",\n        \"Programming Language :: Python\",\n        \"Topic :: Software Development\",\n        \"Topic :: Scientific/Engineering\",\n        \"Topic :: Scientific/Engineering :: Mathematics\",\n        \"Topic :: Scientific/Engineering :: Artificial Intelligence\",\n        \"Topic :: Software Development :: Libraries\",\n        \"Topic :: Software Development :: Libraries :: Python Modules\",\n    ],\n    python_requires=\">=3.7\",\n    # What does your project relate to?\n    keywords=\"machine_learning data_cleaning confident_learning classification weak_supervision \"\n    \"learning_with_noisy_labels unsupervised_learning datacentric_ai, datacentric\",\n    # You can just specify the packages manually here if your project is\n    # simple. Or you can use find_packages().\n    packages=find_packages(exclude=[]),\n    # Include cleanlab license file.\n    include_package_data=True,\n    package_data={\n        \"\": [\"LICENSE\"],\n    },\n    license_files=(\"LICENSE\",),\n    cmdclass={\"egg_info\": egg_info_ex},\n    # List run-time dependencies here.  These will be installed by pip when\n    # your project is installed. For an analysis of \"install_requires\" vs pip's\n    # requirements files see:\n    # https://packaging.python.org/en/latest/discussions/install-requires-vs-requirements/\n    install_requires=[\n        \"numpy>=1.20.0\",\n        \"scikit-learn>=1.0\",\n        \"tqdm>=4.53.0\",\n        \"pandas>=1.1.5\",\n        \"termcolor>=2.0.0,<2.4.0\",\n    ],\n    extras_require=EXTRAS_REQUIRE,\n)\n", "path": "setup.py"}]}