
"""simple docstring"""

import torch

from accelerate import Accelerator, DistributedType
class    _UpperCAmelCase							:




      def __enter__(							self							)  ->    List[Any]:
          if self.enabled:
              UpperCAmelCase  	=    self.model.no_sync()
              self.model_sync_obj.__enter__()

          return self




      def __exit__(							self      ,				lowercase_      ,				lowercase_      ,				lowercase_							)  ->    List[str]:
          if self.enabled:
              # Average all models on exit
              self._sync_and_avg_model_params()
              self.model_sync_obj.__exit__(lowercase_      ,				lowercase_      ,				lowercase_							)




      def __init__(							self      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_ = True							)  ->    str:
          if accelerator.distributed_type not in [
              DistributedType.NO,
              DistributedType.MULTI_CPU,
              DistributedType.MULTI_GPU,
          ]:
              raise NotImplementedError('LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'							)
          UpperCAmelCase  	=    enabled and accelerator.distributed_type != DistributedType.NO
          UpperCAmelCase  	=    0
          if self.enabled:
              UpperCAmelCase  	=    accelerator
              UpperCAmelCase  	=    model
              UpperCAmelCase  	=    local_sgd_steps




      def 			a_					(							self							)  ->    List[str]:
          self.num_steps += 1
          if not self.enabled:
              return

          if self.num_steps % self.local_sgd_steps == 0:
              self._sync_and_avg_model_params()




      def 			a_					(							self							)  ->    Tuple:
          self.accelerator.wait_for_everyone()
          with self.accelerator.autocast():
              for param in self.model.parameters():
                  UpperCAmelCase  	=    self.accelerator.reduce(param.data      ,				reduction='mean'							)





"""simple docstring"""

import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile, rmtree
from typing import Generator

import datasets.config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.filelock import logger as fl_logger
from datasets.utils.info_utils import VerificationMode
from datasets.utils.logging import ERROR, get_logger


SCREAMING_SNAKE_CASE_			    =  get_logger(__name__)




def 			lowercase__  (    lowerCAmelCase :    Dict       )       ->					Any:






    """simple docstring"""




    return TestCommand(
        args.dataset       , args.name       , args.cache_dir       , args.data_dir       , args.all_configs       , args.save_info or args.save_infos       , args.ignore_verifications       , args.force_redownload       , args.clear_cache       , )







class    _UpperCAmelCase							(						SCREAMING_SNAKE_CASE_							):
      __SCREAMING_SNAKE_CASE      :							Optional[Any]												=		False  # to tell pytest it's not a test class




      @staticmethod
      def 			a_					(							lowercase_							)  ->    int:
          UpperCAmelCase  	=    parser.add_parser('test'      ,				help='Test dataset implementation.'							)
          test_parser.add_argument('--name'      ,				type=lowercase_      ,				default=lowercase_      ,				help='Dataset processing name'							)
          test_parser.add_argument(
              '--cache_dir'      ,				type=lowercase_      ,				default=lowercase_      ,				help='Cache directory where the datasets are stored.'      ,				)
          test_parser.add_argument(
              '--data_dir'      ,				type=lowercase_      ,				default=lowercase_      ,				help='Can be used to specify a manual directory to get the files from.'      ,				)
          test_parser.add_argument('--all_configs'      ,				action='store_true'      ,				help='Test all dataset configurations'							)
          test_parser.add_argument(
              '--save_info'      ,				action='store_true'      ,				help='Save the dataset infos in the dataset card (README.md)'							)
          test_parser.add_argument(
              '--ignore_verifications'      ,				action='store_true'      ,				help='Run the test without checksums and splits checks.'      ,				)
          test_parser.add_argument('--force_redownload'      ,				action='store_true'      ,				help='Force dataset redownload'							)
          test_parser.add_argument(
              '--clear_cache'      ,				action='store_true'      ,				help='Remove downloaded files and cached datasets after each config test'      ,				)
          # aliases
          test_parser.add_argument('--save_infos'      ,				action='store_true'      ,				help='alias to save_info'							)
          test_parser.add_argument('dataset'      ,				type=lowercase_      ,				help='Name of the dataset to download'							)
          test_parser.set_defaults(func=_test_command_factory							)




      def __init__(							self      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				)  ->    List[Any]:
          UpperCAmelCase  	=    dataset
          UpperCAmelCase  	=    name
          UpperCAmelCase  	=    cache_dir
          UpperCAmelCase  	=    data_dir
          UpperCAmelCase  	=    all_configs
          UpperCAmelCase  	=    save_infos
          UpperCAmelCase  	=    ignore_verifications
          UpperCAmelCase  	=    force_redownload
          UpperCAmelCase  	=    clear_cache
          if clear_cache and not cache_dir:
              print(
                  'When --clear_cache is used, specifying a cache directory is mandatory.\n'
                  'The \'download\' folder of the cache directory and the dataset builder cache will be deleted after each configuration test.\n'
                  'Please provide a --cache_dir that will be used to test the dataset script.'							)
              exit(1							)
          if save_infos:
              UpperCAmelCase  	=    True




      def 			a_					(							self							)  ->    List[Any]:
          fl_logger().setLevel(lowercase_							)
          if self._name is not None and self._all_configs:
              print('Both parameters `config` and `all_configs` can\'t be used at once.'							)
              exit(1							)
          UpperCAmelCase	,							UpperCAmelCase  	=    self._dataset, self._name
          UpperCAmelCase  	=    dataset_module_factory(lowercase_							)
          UpperCAmelCase  	=    import_main_class(module.module_path							)
          UpperCAmelCase  	=    len(builder_cls.BUILDER_CONFIGS							) if self._all_configs and builder_cls.BUILDER_CONFIGS else 1

          def get_builders() -> Generator[DatasetBuilder, None, None]:
              if self._all_configs and builder_cls.BUILDER_CONFIGS:
                  for i, config in enumerate(builder_cls.BUILDER_CONFIGS							):
                      if "config_name" in module.builder_kwargs:
                          yield builder_cls(
                              cache_dir=self._cache_dir      ,				data_dir=self._data_dir      ,				**module.builder_kwargs      ,				)
                      else:
                          yield builder_cls(
                              config_name=config.name      ,				cache_dir=self._cache_dir      ,				data_dir=self._data_dir      ,				**module.builder_kwargs      ,				)
              else:
                  if "config_name" in module.builder_kwargs:
                      yield builder_cls(cache_dir=self._cache_dir      ,				data_dir=self._data_dir      ,				**module.builder_kwargs							)
                  else:
                      yield builder_cls(
                          config_name=lowercase_      ,				cache_dir=self._cache_dir      ,				data_dir=self._data_dir      ,				**module.builder_kwargs      ,				)

          for j, builder in enumerate(get_builders()							):
              print(F"Testing builder '{builder.config.name}' ({j + 1}/{n_builders})"							)
              UpperCAmelCase  	=    os.path.exists(
                  os.path.join(builder.get_imported_module_dir()      ,				datasets.config.DATASETDICT_INFOS_FILENAME							)							)  # record checksums only if we need to update a (deprecated) dataset_infos.json
              builder.download_and_prepare(
                  download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
                  if not self._force_redownload
                  else DownloadMode.FORCE_REDOWNLOAD      ,				verification_mode=VerificationMode.NO_CHECKS
                  if self._ignore_verifications
                  else VerificationMode.ALL_CHECKS      ,				try_from_hf_gcs=lowercase_      ,				)
              builder.as_dataset()
              if self._save_infos:
                  builder._save_infos()

              # If save_infos=True, the dataset card (README.md) is created next to the loaded module file.
              # The dataset_infos are saved in the YAML part of the README.md

              # 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:
                  UpperCAmelCase  	=    os.path.join(builder_cls.get_imported_module_dir()      ,				'README.md'							)
                  UpperCAmelCase  	=    Path(lowercase_							).name + '.py'
                  UpperCAmelCase  	=    os.path.join(lowercase_      ,				lowercase_							)
                  if os.path.isfile(lowercase_							):
                      UpperCAmelCase  	=    os.path.dirname(lowercase_							)
                  elif os.path.isfile(lowercase_							):
                      UpperCAmelCase  	=    path
                  elif os.path.isdir(lowercase_							):  # for local directories containing only data files
                      UpperCAmelCase  	=    path
                  else:  # in case of a remote dataset
                      UpperCAmelCase  	=    None
                      print(F"Dataset card saved at {dataset_readme_path}"							)

                  # Move dataset_info back to the user
                  if dataset_dir is not None:
                      UpperCAmelCase  	=    os.path.join(lowercase_      ,				'README.md'							)
                      copyfile(lowercase_      ,				lowercase_							)
                      print(F"Dataset card saved at {user_dataset_readme_path}"							)

            # If clear_cache=True, the download folder and the dataset builder cache directory are deleted
              if self._clear_cache:
                  if os.path.isdir(builder._cache_dir							):
                      logger.warning(F"Clearing cache at {builder._cache_dir}"							)
                      rmtree(builder._cache_dir							)
                  UpperCAmelCase  	=    os.path.join(self._cache_dir      ,				datasets.config.DOWNLOADED_DATASETS_DIR							)
                  if os.path.isdir(lowercase_							):
                      logger.warning(F"Clearing cache at {download_dir}"							)
                      rmtree(lowercase_							)

          print('Test successful.'							)



