code: 
  
  import os
  from argparse import ArgumentParser
  from pathlib import Path
  from shutil import copyfile
  from typing import List
  
  from datasets import config
  from datasets.builder import DatasetBuilder
  from datasets.commands import BaseDatasetsCLICommand
  from datasets.download.download_config import DownloadConfig
  from datasets.download.download_manager import DownloadMode
  from datasets.load import dataset_module_factory, import_main_class
  from datasets.utils.info_utils import VerificationMode
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Optional[int]			,  **SCREAMING_SNAKE_CASE_	:					str    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       return RunBeamCommand(
           args.dataset			,  args.name			,  args.cache_dir			,  args.beam_pipeline_options			,  args.data_dir			,  args.all_configs			,  args.save_info or args.save_infos			,  args.ignore_verifications			,  args.force_redownload			,  **SCREAMING_SNAKE_CASE_			,  )
  
  
  class    SCREAMING_SNAKE_CASE__      (__snake_case  ):
  
  
  
  
  
      @staticmethod
      def    snake_case_       (   a):
           lowercase__					:     List[str]   = parser.add_parser('run_beam'		,     help='Run a Beam dataset processing pipeline')
           run_beam_parser.add_argument('dataset'		,     type=a		,     help='Name of the dataset to download')
           run_beam_parser.add_argument('--name'		,     type=a		,     default=a		,     help='Dataset config name')
           run_beam_parser.add_argument(
               '--cache_dir'		,     type=a		,     default=a		,     help='Cache directory where the datasets are stored'		,     )
           run_beam_parser.add_argument(
               '--beam_pipeline_options'		,     type=a		,     default=''		,     help='Beam pipeline options, separated by commas. Example:: `--beam_pipeline_options=job_name=my-job,project=my-project`'		,     )
           run_beam_parser.add_argument(
               '--data_dir'		,     type=a		,     default=a		,     help='Can be used to specify a manual directory to get the files from'		,     )
           run_beam_parser.add_argument('--all_configs'		,     action='store_true'		,     help='Test all dataset configurations')
           run_beam_parser.add_argument('--save_info'		,     action='store_true'		,     help='Save the dataset infos file')
           run_beam_parser.add_argument(
               '--ignore_verifications'		,     action='store_true'		,     help='Run the test without checksums and splits checks')
           run_beam_parser.add_argument('--force_redownload'		,     action='store_true'		,     help='Force dataset redownload')
           # aliases
           run_beam_parser.add_argument('--save_infos'		,     action='store_true'		,     help='alias for save_info')
           run_beam_parser.set_defaults(func=a)
  
  
  
  
  
      def __init__(   self		,     a		,     a		,     a		,     a		,     a		,     a		,     a		,     a		,     a		,     **a		,     ):
           lowercase__					:     List[Any]   = dataset
           lowercase__					:     List[Any]   = name
           lowercase__					:     str   = cache_dir
           lowercase__					:     Any   = beam_pipeline_options
           lowercase__					:     Dict   = data_dir
           lowercase__					:     Dict   = all_configs
           lowercase__					:     Optional[int]   = save_infos
           lowercase__					:     Any   = ignore_verifications
           lowercase__					:     str   = force_redownload
           lowercase__					:     Union[str, Any]   = config_kwargs
  
  
  
  
  
      def    snake_case_       (   self):
           import apache_beam as beam
  
           if self._name is not None and self._all_configs:
                print('Both parameters `name` and `all_configs` can\'t be used at once.')
                exit(1)
           lowercase__   ,				lowercase__					:     Optional[int]   = self._dataset, self._name
           lowercase__					:     Dict   = dataset_module_factory(a)
           lowercase__					:     Tuple   = import_main_class(dataset_module.module_path)
           lowercase__					:     List[DatasetBuilder]   = []
           if self._beam_pipeline_options:
                lowercase__					:     Union[str, Any]   = beam.options.pipeline_options.PipelineOptions(
                    flags=[f"""--{opt.strip()}""" for opt in self._beam_pipeline_options.split(',') if opt])
           else:
                lowercase__					:     Any   = None
           if self._all_configs and len(builder_cls.BUILDER_CONFIGS) > 0:
                for builder_config in builder_cls.BUILDER_CONFIGS:
                     builders.append(
                         builder_cls(
                             config_name=builder_config.name		,     data_dir=self._data_dir		,     hash=dataset_module.hash		,     beam_options=a		,     cache_dir=self._cache_dir		,     base_path=dataset_module.builder_kwargs.get('base_path')		,     ))
           else:
                builders.append(
                    builder_cls(
                        config_name=a		,     data_dir=self._data_dir		,     beam_options=a		,     cache_dir=self._cache_dir		,     base_path=dataset_module.builder_kwargs.get('base_path')		,     **self._config_kwargs		,     ))
  
           for builder in builders:
                builder.download_and_prepare(
                    download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
                    if not self._force_redownload
                    else DownloadMode.FORCE_REDOWNLOAD		,     download_config=DownloadConfig(cache_dir=config.DOWNLOADED_DATASETS_PATH)		,     verification_mode=VerificationMode.NO_CHECKS
                    if self._ignore_verifications
                    else VerificationMode.ALL_CHECKS		,     try_from_hf_gcs=a		,     )
                if self._save_infos:
                     builder._save_infos()
  
           print('Apache beam run successful.')
  
           # If save_infos=True, the dataset infos file is created next to the loaded module file.
           # Let's move it to the original directory of the dataset script, to allow the user to
           # upload them on S3 at the same time afterwards.
           if self._save_infos:
                lowercase__					:     Tuple   = os.path.join(builder_cls.get_imported_module_dir()		,     config.DATASETDICT_INFOS_FILENAME)
  
                lowercase__					:     str   = Path(a).name + '.py'
  
                lowercase__					:     Optional[int]   = os.path.join(a		,     a)
                if os.path.isfile(a):
                     lowercase__					:     Optional[Any]   = os.path.dirname(a)
                elif os.path.isfile(a):
                     lowercase__					:     str   = path
                else:  # in case of a remote dataset
                     print(f"""Dataset Infos file saved at {dataset_infos_path}""")
                     exit(1)
  
                # Move datasetinfo back to the user
                lowercase__					:     Dict   = os.path.join(a		,     config.DATASETDICT_INFOS_FILENAME)
                copyfile(a		,     a)
                print(f"""Dataset Infos file saved at {user_dataset_infos_path}""")
  
  
style_context: 
  
  from __future__ import annotations
  
  
  class    SCREAMING_SNAKE_CASE__      :
  
  
  
  
  
      def __init__(   self		,     a = 0):
           lowercase__					:     int   = value
           lowercase__					:     Node | None   = None
           lowercase__					:     Node | None   = None
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Node | None			,  SCREAMING_SNAKE_CASE_	:					Node | None    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if treea is None:
            return treea
       if treea is None:
            return treea
  
       lowercase__					:     Optional[Any]   = treea.value + treea.value
       lowercase__					:     Union[str, Any]   = merge_two_binary_trees(treea.left			,  treea.left    )
       lowercase__					:     Optional[Any]   = merge_two_binary_trees(treea.right			,  treea.right    )
       return treea
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Node | None    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if root:
            print(root.value    )
            print_preorder(root.left    )
            print_preorder(root.right    )
  
  
  if __name__ == "__main__":
         snake_case_    						=				Node(1)
         snake_case_    						=				Node(2)
         snake_case_    						=				Node(3)
         snake_case_    						=				Node(4)
  
         snake_case_    						=				Node(2)
         snake_case_    						=				Node(4)
         snake_case_    						=				Node(6)
         snake_case_    						=				Node(9)
         snake_case_    						=				Node(5)
  
         print('''Tree1 is: ''')
         print_preorder(treea)
         print('''Tree2 is: ''')
         print_preorder(treea)
         snake_case_    						=				merge_two_binary_trees(treea, treea)
         print('''Merged Tree is: ''')
         print_preorder(merged_tree)
  
  