





from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


lowercase    : List[str]    	=  logging.get_logger(__name__)


lowercase    : Dict    	=  TypeVar("""DatasetType""", Dataset, IterableDataset)


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase = None    ,       lowerCAmelCase = None    ,       lowerCAmelCase = None    ,       lowerCAmelCase = None    ,       lowerCAmelCase = "first_exhausted"    ,       ):
       from .arrow_dataset import Dataset
       from .iterable_dataset import IterableDataset

       if not datasets:
              raise ValueError('''Unable to interleave an empty list of datasets.'''					)
       for i, dataset in enumerate(lowerCAmelCase					):
              if not isinstance(lowerCAmelCase    ,       (Dataset, IterableDataset)					):
                     if isinstance(lowerCAmelCase    ,       (DatasetDict, IterableDatasetDict)					):
                            if not dataset:
                                   raise ValueError(
                                       f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '''
                                       '''is an empty dataset dictionary.'''					)
                            raise ValueError(
                                f'''Dataset at position {i} has at least one split: {list(lowerCAmelCase					)}\n'''
                                f'''Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(lowerCAmelCase					)					)}\']'''					)
                     raise ValueError(
                         f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(lowerCAmelCase					).__name__}.'''					)
              if i == 0:
                     _UpperCamelCase       ,		_UpperCamelCase              =						(
                         (Dataset, IterableDataset) if isinstance(lowerCAmelCase    ,       lowerCAmelCase					) else (IterableDataset, Dataset)
                     )
              elif not isinstance(lowerCAmelCase    ,       lowerCAmelCase					):
                     raise ValueError(
                         f'''Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'''					)
       if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
              raise ValueError(f'''{stopping_strategy} is not supported. Please enter a valid stopping_strategy.'''					)
       if dataset_type is Dataset:
              return _interleave_map_style_datasets(
                  lowerCAmelCase    ,       lowerCAmelCase    ,       lowerCAmelCase    ,       info=lowerCAmelCase    ,       split=lowerCAmelCase    ,       stopping_strategy=lowerCAmelCase					)
       else:
              return _interleave_iterable_datasets(
                  lowerCAmelCase    ,       lowerCAmelCase    ,       lowerCAmelCase    ,       info=lowerCAmelCase    ,       split=lowerCAmelCase    ,       stopping_strategy=lowerCAmelCase					)


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase = None    ,       lowerCAmelCase = None    ,       lowerCAmelCase = 0    ,       ):

       if not dsets:
              raise ValueError('''Unable to concatenate an empty list of datasets.'''					)
       for i, dataset in enumerate(lowerCAmelCase					):
              if not isinstance(lowerCAmelCase    ,       (Dataset, IterableDataset)					):
                     if isinstance(lowerCAmelCase    ,       (DatasetDict, IterableDatasetDict)					):
                            if not dataset:
                                   raise ValueError(
                                       f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '''
                                       '''is an empty dataset dictionary.'''					)
                            raise ValueError(
                                f'''Dataset at position {i} has at least one split: {list(lowerCAmelCase					)}\n'''
                                f'''Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(lowerCAmelCase					)					)}\']'''					)
                     raise ValueError(
                         f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(lowerCAmelCase					).__name__}.'''					)
              if i == 0:
                     _UpperCamelCase       ,		_UpperCamelCase              =						(
                         (Dataset, IterableDataset) if isinstance(lowerCAmelCase    ,       lowerCAmelCase					) else (IterableDataset, Dataset)
                     )
              elif not isinstance(lowerCAmelCase    ,       lowerCAmelCase					):
                     raise ValueError(
                         f'''Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'''					)
       if dataset_type is Dataset:
              return _concatenate_map_style_datasets(lowerCAmelCase    ,       info=lowerCAmelCase    ,       split=lowerCAmelCase    ,       axis=lowerCAmelCase					)
       else:
              return _concatenate_iterable_datasets(lowerCAmelCase    ,       info=lowerCAmelCase    ,       split=lowerCAmelCase    ,       axis=lowerCAmelCase					)













import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


lowercase    : str    	=  logging.get_logger(__name__)

class  __A(						__UpperCAmelCase ):

     def __init__(      self,       *A,       **A      ):





            """simple docstring"""

            warnings.warn(
                '''The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
                ''' use CLIPImageProcessor instead.''',       A,       )
            super().__init__(*A,       **A      )






