prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Update scikit-learn-intelex version
  - [ ] Check if scikit-learn-intelex can be upgraded.
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `tabular/setup.py`
  Content:
  ```
  1 #!/usr/bin/env python
  2 ###########################
  3 # This code block is a HACK (!), but is necessary to avoid code duplication. Do NOT alter these lines.
  4 import os
  5 from setuptools import setup
  6 import importlib.util
  7 filepath = os.path.abspath(os.path.dirname(__file__))
  8 filepath_import = os.path.join(filepath, '..', 'core', 'src', 'autogluon', 'core', '_setup_utils.py')
  9 spec = importlib.util.spec_from_file_location("ag_min_dependencies", filepath_import)
  10 ag = importlib.util.module_from_spec(spec)
  11 # Identical to `from autogluon.core import _setup_utils as ag`, but works without `autogluon.core` being installed.
  12 spec.loader.exec_module(ag)
  13 ###########################
  14 
  15 import sys
  16 
  17 version = ag.load_version_file()
  18 version = ag.update_version(version)
  19 
  20 submodule = 'tabular'
  21 install_requires = [
  22     # version ranges added in ag.get_dependency_version_ranges()
  23     'numpy',  # version range defined in `core/_setup_utils.py`
  24     'scipy',  # version range defined in `core/_setup_utils.py`
  25     'pandas',  # version range defined in `core/_setup_utils.py`
  26     'scikit-learn',  # version range defined in `core/_setup_utils.py`
  27     'networkx',  # version range defined in `core/_setup_utils.py`
  28     f'{ag.PACKAGE_NAME}.core=={version}',
  29     f'{ag.PACKAGE_NAME}.features=={version}',
  30 ]
  31 
  32 extras_require = {
  33     'lightgbm': [
  34         'lightgbm>=3.3,<3.4',
  35     ],
  36     'catboost': [
  37         'catboost>=1.0,<1.2',
  38     ],
  39     # FIXME: Debug why xgboost 1.6 has 4x+ slower inference on multiclass datasets compared to 1.4
  40     #  It is possibly only present on MacOS, haven't tested linux.
  41     # XGBoost made API breaking changes in 1.6 with custom metric and callback support, so we don't support older versions.
  42     'xgboost': [
  43         'xgboost>=1.6,<1.8',
  44     ],
  45     'fastai': [
  46         'torch>=1.9,<1.14',
  47         'fastai>=2.3.1,<2.8',
  48     ],
  49     'ray': [
  50         f'{ag.PACKAGE_NAME}.core[all]=={version}',
  51     ],
  52     'skex': [
  53         'scikit-learn-intelex>=2021.6,<2021.8',
  54     ],
  55     'imodels': [
  56         'imodels>=1.3.10,<1.4.0',  # 1.3.8/1.3.9 either remove/renamed attribute `complexity_` causing failures. https://github.com/csinva/imodels/issues/147
  57     ],
  58     'vowpalwabbit': [
  59         # FIXME: 9.5+ causes VW to save an empty model which always predicts 0. Confirmed on MacOS (Intel CPU). Unknown how to fix.
  60         'vowpalwabbit>=9,<9.5',
  61     ],
  62     'skl2onnx': [
  63         'skl2onnx>=1.13.0,<1.14.0',
  64         # For macOS, there isn't a onnxruntime-gpu package installed with skl2onnx.
  65         # Therefore, we install onnxruntime explicitly here just for macOS.
  66         'onnxruntime>=1.13.0,<1.14.0'
  67     ] if sys.platform == 'darwin' else [
  68         'skl2onnx>=1.13.0,<1.14.0'
  69     ]
  70 }
  71 
  72 all_requires = []
  73 # TODO: Consider adding 'skex' to 'all'
  74 for extra_package in ['lightgbm', 'catboost', 'xgboost', 'fastai', 'ray']:
  75     all_requires += extras_require[extra_package]
  76 all_requires = list(set(all_requires))
  77 extras_require['all'] = all_requires
  78 
  79 
  80 test_requires = []
  81 for test_package in ['imodels', 'vowpalwabbit', 'skl2onnx']:
  82     test_requires += extras_require[test_package]
  83 extras_require['tests'] = test_requires
  84 install_requires = ag.get_dependency_version_ranges(install_requires)
  85 
  86 if __name__ == '__main__':
  87     ag.create_version_file(version=version, submodule=submodule)
  88     setup_args = ag.default_setup_args(version=version, submodule=submodule)
  89     setup(
  90         install_requires=install_requires,
  91         extras_require=extras_require,
  92         **setup_args,
  93     )
  94
  ```
  --- 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()
  
  ```
  
golden_diff: diff --git a/tabular/setup.py b/tabular/setup.py
  --- a/tabular/setup.py
  +++ b/tabular/setup.py
  @@ -50,7 +50,8 @@
           f'{ag.PACKAGE_NAME}.core[all]=={version}',
       ],
       'skex': [
  -        'scikit-learn-intelex>=2021.6,<2021.8',
  +        # Note: 2021.7 released on Sep 2022, version 2022.x doesn't exist (went directly from 2021.7 to 2023.0)
  +        'scikit-learn-intelex>=2021.7,<2023.1',
       ],
       'imodels': [
           'imodels>=1.3.10,<1.4.0',  # 1.3.8/1.3.9 either remove/renamed attribute `complexity_` causing failures. https://github.com/csinva/imodels/issues/147
  
verification_info: {"golden_diff": "diff --git a/tabular/setup.py b/tabular/setup.py\n--- a/tabular/setup.py\n+++ b/tabular/setup.py\n@@ -50,7 +50,8 @@\n         f'{ag.PACKAGE_NAME}.core[all]=={version}',\n     ],\n     'skex': [\n-        'scikit-learn-intelex>=2021.6,<2021.8',\n+        # Note: 2021.7 released on Sep 2022, version 2022.x doesn't exist (went directly from 2021.7 to 2023.0)\n+        'scikit-learn-intelex>=2021.7,<2023.1',\n     ],\n     'imodels': [\n         'imodels>=1.3.10,<1.4.0',  # 1.3.8/1.3.9 either remove/renamed attribute `complexity_` causing failures. https://github.com/csinva/imodels/issues/147\n", "issue": "Update scikit-learn-intelex version\n- [ ] Check if scikit-learn-intelex can be upgraded.\n", "before_files": [{"content": "#!/usr/bin/env python\n###########################\n# This code block is a HACK (!), but is necessary to avoid code duplication. Do NOT alter these lines.\nimport os\nfrom setuptools import setup\nimport importlib.util\nfilepath = os.path.abspath(os.path.dirname(__file__))\nfilepath_import = os.path.join(filepath, '..', 'core', 'src', 'autogluon', 'core', '_setup_utils.py')\nspec = importlib.util.spec_from_file_location(\"ag_min_dependencies\", filepath_import)\nag = importlib.util.module_from_spec(spec)\n# Identical to `from autogluon.core import _setup_utils as ag`, but works without `autogluon.core` being installed.\nspec.loader.exec_module(ag)\n###########################\n\nimport sys\n\nversion = ag.load_version_file()\nversion = ag.update_version(version)\n\nsubmodule = 'tabular'\ninstall_requires = [\n    # version ranges added in ag.get_dependency_version_ranges()\n    'numpy',  # version range defined in `core/_setup_utils.py`\n    'scipy',  # version range defined in `core/_setup_utils.py`\n    'pandas',  # version range defined in `core/_setup_utils.py`\n    'scikit-learn',  # version range defined in `core/_setup_utils.py`\n    'networkx',  # version range defined in `core/_setup_utils.py`\n    f'{ag.PACKAGE_NAME}.core=={version}',\n    f'{ag.PACKAGE_NAME}.features=={version}',\n]\n\nextras_require = {\n    'lightgbm': [\n        'lightgbm>=3.3,<3.4',\n    ],\n    'catboost': [\n        'catboost>=1.0,<1.2',\n    ],\n    # FIXME: Debug why xgboost 1.6 has 4x+ slower inference on multiclass datasets compared to 1.4\n    #  It is possibly only present on MacOS, haven't tested linux.\n    # XGBoost made API breaking changes in 1.6 with custom metric and callback support, so we don't support older versions.\n    'xgboost': [\n        'xgboost>=1.6,<1.8',\n    ],\n    'fastai': [\n        'torch>=1.9,<1.14',\n        'fastai>=2.3.1,<2.8',\n    ],\n    'ray': [\n        f'{ag.PACKAGE_NAME}.core[all]=={version}',\n    ],\n    'skex': [\n        'scikit-learn-intelex>=2021.6,<2021.8',\n    ],\n    'imodels': [\n        'imodels>=1.3.10,<1.4.0',  # 1.3.8/1.3.9 either remove/renamed attribute `complexity_` causing failures. https://github.com/csinva/imodels/issues/147\n    ],\n    'vowpalwabbit': [\n        # FIXME: 9.5+ causes VW to save an empty model which always predicts 0. Confirmed on MacOS (Intel CPU). Unknown how to fix.\n        'vowpalwabbit>=9,<9.5',\n    ],\n    'skl2onnx': [\n        'skl2onnx>=1.13.0,<1.14.0',\n        # For macOS, there isn't a onnxruntime-gpu package installed with skl2onnx.\n        # Therefore, we install onnxruntime explicitly here just for macOS.\n        'onnxruntime>=1.13.0,<1.14.0'\n    ] if sys.platform == 'darwin' else [\n        'skl2onnx>=1.13.0,<1.14.0'\n    ]\n}\n\nall_requires = []\n# TODO: Consider adding 'skex' to 'all'\nfor extra_package in ['lightgbm', 'catboost', 'xgboost', 'fastai', 'ray']:\n    all_requires += extras_require[extra_package]\nall_requires = list(set(all_requires))\nextras_require['all'] = all_requires\n\n\ntest_requires = []\nfor test_package in ['imodels', 'vowpalwabbit', 'skl2onnx']:\n    test_requires += extras_require[test_package]\nextras_require['tests'] = test_requires\ninstall_requires = ag.get_dependency_version_ranges(install_requires)\n\nif __name__ == '__main__':\n    ag.create_version_file(version=version, submodule=submodule)\n    setup_args = ag.default_setup_args(version=version, submodule=submodule)\n    setup(\n        install_requires=install_requires,\n        extras_require=extras_require,\n        **setup_args,\n    )\n", "path": "tabular/setup.py"}], "after_files": [{"content": "#!/usr/bin/env python\n###########################\n# This code block is a HACK (!), but is necessary to avoid code duplication. Do NOT alter these lines.\nimport os\nfrom setuptools import setup\nimport importlib.util\nfilepath = os.path.abspath(os.path.dirname(__file__))\nfilepath_import = os.path.join(filepath, '..', 'core', 'src', 'autogluon', 'core', '_setup_utils.py')\nspec = importlib.util.spec_from_file_location(\"ag_min_dependencies\", filepath_import)\nag = importlib.util.module_from_spec(spec)\n# Identical to `from autogluon.core import _setup_utils as ag`, but works without `autogluon.core` being installed.\nspec.loader.exec_module(ag)\n###########################\n\nimport sys\n\nversion = ag.load_version_file()\nversion = ag.update_version(version)\n\nsubmodule = 'tabular'\ninstall_requires = [\n    # version ranges added in ag.get_dependency_version_ranges()\n    'numpy',  # version range defined in `core/_setup_utils.py`\n    'scipy',  # version range defined in `core/_setup_utils.py`\n    'pandas',  # version range defined in `core/_setup_utils.py`\n    'scikit-learn',  # version range defined in `core/_setup_utils.py`\n    'networkx',  # version range defined in `core/_setup_utils.py`\n    f'{ag.PACKAGE_NAME}.core=={version}',\n    f'{ag.PACKAGE_NAME}.features=={version}',\n]\n\nextras_require = {\n    'lightgbm': [\n        'lightgbm>=3.3,<3.4',\n    ],\n    'catboost': [\n        'catboost>=1.0,<1.2',\n    ],\n    # FIXME: Debug why xgboost 1.6 has 4x+ slower inference on multiclass datasets compared to 1.4\n    #  It is possibly only present on MacOS, haven't tested linux.\n    # XGBoost made API breaking changes in 1.6 with custom metric and callback support, so we don't support older versions.\n    'xgboost': [\n        'xgboost>=1.6,<1.8',\n    ],\n    'fastai': [\n        'torch>=1.9,<1.14',\n        'fastai>=2.3.1,<2.8',\n    ],\n    'ray': [\n        f'{ag.PACKAGE_NAME}.core[all]=={version}',\n    ],\n    'skex': [\n        # Note: 2021.7 released on Sep 2022, version 2022.x doesn't exist (went directly from 2021.7 to 2023.0)\n        'scikit-learn-intelex>=2021.7,<2023.1',\n    ],\n    'imodels': [\n        'imodels>=1.3.10,<1.4.0',  # 1.3.8/1.3.9 either remove/renamed attribute `complexity_` causing failures. https://github.com/csinva/imodels/issues/147\n    ],\n    'vowpalwabbit': [\n        # FIXME: 9.5+ causes VW to save an empty model which always predicts 0. Confirmed on MacOS (Intel CPU). Unknown how to fix.\n        'vowpalwabbit>=9,<9.5',\n    ],\n    'skl2onnx': [\n        'skl2onnx>=1.13.0,<1.14.0',\n        # For macOS, there isn't a onnxruntime-gpu package installed with skl2onnx.\n        # Therefore, we install onnxruntime explicitly here just for macOS.\n        'onnxruntime>=1.13.0,<1.14.0'\n    ] if sys.platform == 'darwin' else [\n        'skl2onnx>=1.13.0,<1.14.0'\n    ]\n}\n\nall_requires = []\n# TODO: Consider adding 'skex' to 'all'\nfor extra_package in ['lightgbm', 'catboost', 'xgboost', 'fastai', 'ray']:\n    all_requires += extras_require[extra_package]\nall_requires = list(set(all_requires))\nextras_require['all'] = all_requires\n\n\ntest_requires = []\nfor test_package in ['imodels', 'vowpalwabbit', 'skl2onnx']:\n    test_requires += extras_require[test_package]\nextras_require['tests'] = test_requires\ninstall_requires = ag.get_dependency_version_ranges(install_requires)\n\nif __name__ == '__main__':\n    ag.create_version_file(version=version, submodule=submodule)\n    setup_args = ag.default_setup_args(version=version, submodule=submodule)\n    setup(\n        install_requires=install_requires,\n        extras_require=extras_require,\n        **setup_args,\n    )\n", "path": "tabular/setup.py"}]}