


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		:Any											=       get_logger(__name__)



def      _lowerCAmelCase  (							lowerCAmelCase_							:Optional[Any]							)->str:
   '''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       __lowerCAmelCase       (	SCREAMING_SNAKE_CASE__   ):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE						      =    False  # to tell pytest it's not a test class



  @staticmethod
  def    lowerCAmelCase__					(       _lowerCAmelCase    :    List[Any]					)				->	Any:




     """simple docstring"""
     snake_case_         =   parser.add_parser("test"      ,			help="Test dataset implementation."					)
     test_parser.add_argument("--name"      ,			type=_UpperCAmelCase      ,			default=_UpperCAmelCase      ,			help="Dataset processing name"					)
     test_parser.add_argument(
         "--cache_dir"      ,			type=_UpperCAmelCase      ,			default=_UpperCAmelCase      ,			help="Cache directory where the datasets are stored."      ,			)
     test_parser.add_argument(
         "--data_dir"      ,			type=_UpperCAmelCase      ,			default=_UpperCAmelCase      ,			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=_UpperCAmelCase      ,			help="Name of the dataset to download"					)
     test_parser.set_defaults(func=_test_command_factory					)



  def __init__(       self    :    Any      ,			_lowerCAmelCase    :    Tuple      ,			_lowerCAmelCase    :    Any      ,			_lowerCAmelCase    :    int      ,			_lowerCAmelCase    :    int      ,			_lowerCAmelCase    :    Dict      ,			_lowerCAmelCase    :    Dict      ,			_lowerCAmelCase    :    Dict      ,			_lowerCAmelCase    :    Optional[Any]      ,			_lowerCAmelCase    :    Tuple      ,			)				->	int:




     """simple docstring"""
     snake_case_         =   dataset
     snake_case_         =   name
     snake_case_         =   cache_dir
     snake_case_         =   data_dir
     snake_case_         =   all_configs
     snake_case_         =   save_infos
     snake_case_         =   ignore_verifications
     snake_case_         =   force_redownload
     snake_case_         =   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:
        snake_case_         =   True



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




     """simple docstring"""
     fl_logger().setLevel(_UpperCAmelCase					)
     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					)
     snake_case_         =   self._dataset, self._name
     snake_case_         =   dataset_module_factory(_UpperCAmelCase					)
     snake_case_         =   import_main_class(module.module_path					)
     snake_case_         =   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=_UpperCAmelCase      ,			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})'''					)
        snake_case_         =   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=_UpperCAmelCase      ,			)
        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:
           snake_case_         =   os.path.join(builder_cls.get_imported_module_dir()      ,			"README.md"					)
           snake_case_         =   Path(_UpperCAmelCase					).name + ".py"
           snake_case_         =   os.path.join(_UpperCAmelCase      ,			_UpperCAmelCase					)
           if os.path.isfile(_UpperCAmelCase					):
              snake_case_         =   os.path.dirname(_UpperCAmelCase					)
           elif os.path.isfile(_UpperCAmelCase					):
              snake_case_         =   path
           elif os.path.isdir(_UpperCAmelCase					):  # for local directories containing only data files
              snake_case_         =   path
           else:  # in case of a remote dataset
              snake_case_         =   None
              print(F'''Dataset card saved at {dataset_readme_path}'''					)

           # Move dataset_info back to the user
           if dataset_dir is not None:
              snake_case_         =   os.path.join(_UpperCAmelCase      ,			"README.md"					)
              copyfile(_UpperCAmelCase      ,			_UpperCAmelCase					)
              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					)
           snake_case_         =   os.path.join(self._cache_dir      ,			datasets.config.DOWNLOADED_DATASETS_DIR					)
           if os.path.isdir(_UpperCAmelCase					):
              logger.warning(F'''Clearing cache at {download_dir}'''					)
              rmtree(_UpperCAmelCase					)

     print("Test successful."					)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE		:str											=       {'''configuration_cvt''': ['''CVT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CvtConfig''']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE		:Any											=       [
       '''CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''CvtForImageClassification''',
       '''CvtModel''',
       '''CvtPreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE		:Any											=       [
       '''TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFCvtForImageClassification''',
       '''TFCvtModel''',
       '''TFCvtPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_cvt import (
          CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
          CvtForImageClassification,
          CvtModel,
          CvtPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_cvt import (
          TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFCvtForImageClassification,
          TFCvtModel,
          TFCvtPreTrainedModel,
      )


else:
   import sys

   SCREAMING_SNAKE_CASE		:str											=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




