


from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream




class A  (   UpperCamelCase_     ):






      def __init__(					self						:     Any			,   lowercase_						:     Callable			,   lowercase_						:     Optional[Features] = None			,   lowercase_						:     str = None			,   lowercase_						:     bool = False			,   lowercase_						:     bool = False			,   lowercase_						:     Optional[dict] = None			,   lowercase_						:     Optional[int] = None			,   **lowercase_						:     List[Any]			,   )					->						Dict:
             """simple docstring"""




             super().__init__(
                 features=lowercase_			,   cache_dir=lowercase_			,   keep_in_memory=lowercase_			,   streaming=lowercase_			,   num_proc=lowercase_			,   **lowercase_			,   )
             _lowerCamelCase       :		Optional[int]		=Generator(
                 cache_dir=lowercase_			,   features=lowercase_			,   generator=lowercase_			,   gen_kwargs=lowercase_			,   **lowercase_			,   )






      def        lowerCamelCase       (					self						:     Optional[Any] )					->						Dict:
             """simple docstring"""




             if self.streaming:
                    _lowerCamelCase       :		Any		=self.builder.as_streaming_dataset(split='train' )
             # Build regular (map-style) dataset
             else:
                    _lowerCamelCase       :		Union[str, Any]		=None
                    _lowerCamelCase       :		Union[str, Any]		=None
                    _lowerCamelCase       :		Tuple		=None
                    _lowerCamelCase       :		Tuple		=None

                    self.builder.download_and_prepare(
                        download_config=lowercase_			,   download_mode=lowercase_			,   verification_mode=lowercase_			,   base_path=lowercase_			,   num_proc=self.num_proc			,   )
                    _lowerCamelCase       :		Optional[Any]		=self.builder.as_dataset(
                        split='train'			,   verification_mode=lowercase_			,   in_memory=self.keep_in_memory )
             return dataset






import sys

from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

lowerCamelCase											=       'python tqdm regex requests packaging filelock numpy tokenizers'.split()
if sys.version_info < (3, 7):
 pkgs_to_check_at_runtime.append('dataclasses')
if sys.version_info < (3, 8):
 pkgs_to_check_at_runtime.append('importlib_metadata')

for pkg in pkgs_to_check_at_runtime:
 if pkg in deps:
  if pkg == "tokenizers":
   # must be loaded here, or else tqdm check may fail
   from .utils import is_tokenizers_available

   if not is_tokenizers_available():
    continue  # not required, check version only if installed

  require_version_core(deps[pkg])
 else:
  raise ValueError(F"""can't find {pkg} in {deps.keys()}, check dependency_versions_table.py""")




def 	a_      (    SCREAMING_SNAKE_CASE__					:      int		,			SCREAMING_SNAKE_CASE__					:      str=None     ):
       '''simple docstring'''





       require_version(deps[pkg]		,			SCREAMING_SNAKE_CASE__     )


