code: def setup_package():
      metadata = dict(
          name="bigdl-chronos",
          version=VERSION,
          description="Scalable time series analysis using AutoML",
          long_description=long_description,
          long_description_content_type="text/markdown",
          author="BigDL Authors",
          author_email="bigdl-user-group@googlegroups.com",
          license="Apache License, Version 2.0",
          url="https://github.com/intel-analytics/BigDL",
          packages=get_bigdl_packages(),
          install_requires=[
              "pandas>=1.0.5, <=1.3.5",
              "scikit-learn>=0.22.0, <=1.0.2",
              "bigdl-nano==" + VERSION,
          ],
          extras_require={
              "pytorch": ["bigdl-nano[pytorch]==" + VERSION],
              "tensorflow": ["bigdl-nano==" + VERSION] + TF_DEP,
              "automl": [
                  "optuna<=2.10.1",
                  "configspace<=0.5.0",
                  "SQLAlchemy<=1.4.27",
              ],
              'distributed:platform_system!="Windows"': [
                  "bigdl-orca-spark3==" + VERSION,
                  "grpcio==1.53.0",
                  "pyarrow",
              ]
              + ORCA_AUTOML_DEP,
              "inference": ["bigdl-nano[inference]==" + VERSION],
              "all": [
                  "bigdl-nano[pytorch]==" + VERSION,
                  TF_DEP,
                  "optuna<=2.10.1",
                  "configspace<=0.5.0",
                  "SQLAlchemy<=1.4.27",
                  "bigdl-orca-spark3=="
                  + VERSION
                  + ';platform_system!="Windows"',
                  "grpcio==1.53.0",
                  "pmdarima==1.8.5",
                  "prophet==1.1.0",
                  "holidays==0.24",
                  "tsfresh==0.17.0",
                  "pyarrow==6.0.1",
                  "matplotlib",
                  "inotify_simple",
                  "bigdl-nano[inference]==" + VERSION,
              ]
              + ORCA_AUTOML_DEP,
          },
          dependency_links=[
              "https://d3kbcqa49mib13.cloudfront.net/spark-2.0.0-bin-hadoop2.7.tgz"
          ],
          include_package_data=True,
          entry_points={
              "console_scripts": [
                  "benchmark-chronos=bigdl.chronos.benchmark.benchmark_chronos:main",
              ]
          },
          classifiers=[
              "License :: OSI Approved :: Apache Software License",
              "Programming Language :: Python :: 3",
              "Programming Language :: Python :: 3.7",
              "Programming Language :: Python :: Implementation :: CPython",
          ],
          platforms=["mac", "linux", "windows"],
      )
  
      setup(**metadata)
  
imports: import os
  import fnmatch
  from setuptools import setup
label_desc: Use image node_id 2 for calling a global function with example usage: setup_package() without return types