




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 				UpperCAmelCase__  (							_A      ,      **_A			):






  """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      ,      **_A      ,      )




class 							__lowercase   (			a__    ):



     @staticmethod
     def 				__magic_name__		(  lowercase__   :							ArgumentParser       ):
       a_		    =  parser.add_parser('''run_beam'''      ,		help='''Run a Beam dataset processing pipeline'''       )
       run_beam_parser.add_argument('''dataset'''      ,		type=lowercase__      ,		help='''Name of the dataset to download'''       )
       run_beam_parser.add_argument('''--name'''      ,		type=lowercase__      ,		default=lowercase__      ,		help='''Dataset config name'''       )
       run_beam_parser.add_argument(
           '''--cache_dir'''      ,		type=lowercase__      ,		default=lowercase__      ,		help='''Cache directory where the datasets are stored'''      ,		)
       run_beam_parser.add_argument(
           '''--beam_pipeline_options'''      ,		type=lowercase__      ,		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=lowercase__      ,		default=lowercase__      ,		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=lowercase__       )



     def __init__(  self   :							Optional[int]      ,		lowercase__   :							str      ,		lowercase__   :							str      ,		lowercase__   :							str      ,		lowercase__   :							str      ,		lowercase__   :							str      ,		lowercase__   :							bool      ,		lowercase__   :							bool      ,		lowercase__   :							bool      ,		lowercase__   :							bool      ,		**lowercase__   :							str      ,		):
       a_		    =  dataset
       a_		    =  name
       a_		    =  cache_dir
       a_		    =  beam_pipeline_options
       a_		    =  data_dir
       a_		    =  all_configs
       a_		    =  save_infos
       a_		    =  ignore_verifications
       a_		    =  force_redownload
       a_		    =  config_kwargs



     def 				__magic_name__		(  self   :							str       ):
       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       )
       a_    , a_		    =  self._dataset, self._name
       a_		    =  dataset_module_factory(lowercase__       )
       a_		    =  import_main_class(dataset_module.module_path       )
       a_		    =  []
       if self._beam_pipeline_options:
         a_		    =  beam.options.pipeline_options.PipelineOptions(
             flags=[f"--{opt.strip()}" for opt in self._beam_pipeline_options.split(''','''       ) if opt]       )
       else:
         a_		    =  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=lowercase__      ,		cache_dir=self._cache_dir      ,		base_path=dataset_module.builder_kwargs.get('''base_path'''       )      ,		)       )
       else:
         builders.append(
             builder_cls(
                 config_name=lowercase__      ,		data_dir=self._data_dir      ,		beam_options=lowercase__      ,		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=lowercase__      ,		)
         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:
         a_		    =  os.path.join(builder_cls.get_imported_module_dir()      ,		config.DATASETDICT_INFOS_FILENAME       )

         a_		    =  Path(lowercase__       ).name + '''.py'''

         a_		    =  os.path.join(lowercase__      ,		lowercase__       )
         if os.path.isfile(lowercase__       ):
           a_		    =  os.path.dirname(lowercase__       )
         elif os.path.isfile(lowercase__       ):
           a_		    =  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
         a_		    =  os.path.join(lowercase__      ,		config.DATASETDICT_INFOS_FILENAME       )
         copyfile(lowercase__      ,		lowercase__       )
         print(f"Dataset Infos file saved at {user_dataset_infos_path}"       )






import io
import json
import subprocess


UpperCamelCase__       				=	[
    ['''en''', '''ru'''],
    ['''ru''', '''en'''],
    ['''en''', '''de'''],
    ['''de''', '''en'''],
]

UpperCamelCase__       				=	8






def 				UpperCAmelCase__  (							_A      ,      _A			):






  """simple docstring"""


  a_		    =  {}
  for src, tgt in pairs:
    a_		    =  f"{src}-{tgt}"
    a_		    =  f"sacrebleu -t wmt19 -l {pair} --echo src".split()
    a_		    =  subprocess.run(_A      ,      stdout=subprocess.PIPE			).stdout.decode('''utf-8'''			).splitlines()
    a_		    =  f"sacrebleu -t wmt19 -l {pair} --echo ref".split()
    a_		    =  subprocess.run(_A      ,      stdout=subprocess.PIPE			).stdout.decode('''utf-8'''			).splitlines()
    a_		    =  {'''src''': src_lines[:n_objs], '''tgt''': tgt_lines[:n_objs]}
  return text


UpperCamelCase__       				=	get_all_data(pairs, n_objs)
UpperCamelCase__       				=	'''./fsmt_val_data.json'''
with io.open(filename, '''w''', encoding='''utf-8''') as f:
  UpperCamelCase__       				=	json.dump(text, f, indent=2, ensure_ascii=False)
