
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      (					__lowerCamelCase  :				Union[str, Any]       ,      **__lowerCamelCase  :				int					):
       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       ,      **__lowerCamelCase       ,      )






class 						UpperCAmelCase	(		A_				):



   @staticmethod
   def        _SCREAMING_SNAKE_CASE     (snake_case__	:      ArgumentParser				)	->			Optional[int]:


          '''simple docstring'''


          snake_case :     Union[str, Any]           =   parser.add_parser("run_beam"					,		help="Run a Beam dataset processing pipeline"				)
          run_beam_parser.add_argument("dataset"					,		type=snake_case__					,		help="Name of the dataset to download"				)
          run_beam_parser.add_argument("--name"					,		type=snake_case__					,		default=snake_case__					,		help="Dataset config name"				)
          run_beam_parser.add_argument(
              "--cache_dir"					,		type=snake_case__					,		default=snake_case__					,		help="Cache directory where the datasets are stored"					,		)
          run_beam_parser.add_argument(
              "--beam_pipeline_options"					,		type=snake_case__					,		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=snake_case__					,		default=snake_case__					,		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=snake_case__				)



   def __init__(self	:      Union[str, Any]					,		snake_case__	:      str					,		snake_case__	:      str					,		snake_case__	:      str					,		snake_case__	:      str					,		snake_case__	:      str					,		snake_case__	:      bool					,		snake_case__	:      bool					,		snake_case__	:      bool					,		snake_case__	:      bool					,		**snake_case__	:      Any					,		)	->			str:


          '''simple docstring'''


          snake_case :     str           =   dataset
          snake_case :     Optional[int]           =   name
          snake_case :     Optional[int]           =   cache_dir
          snake_case :     Union[str, Any]           =   beam_pipeline_options
          snake_case :     Union[str, Any]           =   data_dir
          snake_case :     Union[str, Any]           =   all_configs
          snake_case :     Union[str, Any]           =   save_infos
          snake_case :     Any           =   ignore_verifications
          snake_case :     Optional[Any]           =   force_redownload
          snake_case :     Tuple           =   config_kwargs



   def        _SCREAMING_SNAKE_CASE     (self	:      Any				)	->			List[Any]:


          '''simple docstring'''


          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				)
          snake_case       ,      snake_case :     int           =   self._dataset, self._name
          snake_case :     Union[str, Any]           =   dataset_module_factory(snake_case__				)
          snake_case :     Optional[Any]           =   import_main_class(dataset_module.module_path				)
          snake_case :     List[DatasetBuilder]           =   []
          if self._beam_pipeline_options:
                 snake_case :     Dict           =   beam.options.pipeline_options.PipelineOptions(
                     flags=[f"""--{opt.strip()}""" for opt in self._beam_pipeline_options.split(","				) if opt]				)
          else:
                 snake_case :     Dict           =   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=snake_case__					,		cache_dir=self._cache_dir					,		base_path=dataset_module.builder_kwargs.get("base_path"				)					,		)				)
          else:
                 builders.append(
                     builder_cls(
                         config_name=snake_case__					,		data_dir=self._data_dir					,		beam_options=snake_case__					,		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=snake_case__					,		)
                 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:
                 snake_case :     Tuple           =   os.path.join(builder_cls.get_imported_module_dir()					,		config.DATASETDICT_INFOS_FILENAME				)

                 snake_case :     Dict           =   Path(snake_case__				).name + ".py"

                 snake_case :     Union[str, Any]           =   os.path.join(snake_case__					,		snake_case__				)
                 if os.path.isfile(snake_case__				):
                        snake_case :     int           =   os.path.dirname(snake_case__				)
                 elif os.path.isfile(snake_case__				):
                        snake_case :     List[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
                 snake_case :     Union[str, Any]           =   os.path.join(snake_case__					,		config.DATASETDICT_INFOS_FILENAME				)
                 copyfile(snake_case__					,		snake_case__				)
                 print(f"""Dataset Infos file saved at {user_dataset_infos_path}"""				)







import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import Mock, patch

import diffusers.utils.hub_utils






class 						UpperCAmelCase	(		unittest.TestCase				):



   @patch("diffusers.utils.hub_utils.get_full_repo_name"				)
   def        _SCREAMING_SNAKE_CASE     (self	:      Any					,		snake_case__	:      Mock				)	->			None:


          '''simple docstring'''


          snake_case :     str           =   "full_repo_name"
          with TemporaryDirectory() as tmpdir:
                 # Dummy args values
                 snake_case :     List[str]           =   Mock()
                 snake_case :     List[str]           =   tmpdir
                 snake_case :     Optional[int]           =   0
                 snake_case :     int           =   "hub_token"
                 snake_case :     Union[str, Any]           =   "dataset_name"
                 snake_case :     Tuple           =   0.01
                 snake_case :     int           =   10_00_00
                 snake_case :     Optional[Any]           =   1_00_00
                 snake_case :     Optional[Any]           =   0.01
                 snake_case :     Dict           =   0.02
                 snake_case :     List[Any]           =   0.03
                 snake_case :     str           =   0.0005
                 snake_case :     List[str]           =   0.000001
                 snake_case :     Tuple           =   1
                 snake_case :     Optional[int]           =   10
                 snake_case :     List[str]           =   0.001
                 snake_case :     List[Any]           =   0.1
                 snake_case :     List[str]           =   0.2
                 snake_case :     Tuple           =   True

                 # Model card mush be rendered and saved
                 diffusers.utils.hub_utils.create_model_card(snake_case__					,		model_name="model_name"				)
                 self.assertTrue((Path(snake_case__				) / "README.md").is_file()				)





