import copy
import random

from transformers import CLIPTokenizer






class 		a__						(					A__					):

					def __init__(    self      :       List[Any],*_A      :       List[str],**_A      :       List[str]    ):







							"""simple docstring"""






							super().__init__(*_snake_case,**_snake_case    )
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    {}

					def 				__UpperCamelCase   (    self      :       Any,_A      :       List[Any],*_A      :       List[Any],**_A      :       Optional[int]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]				      =    super().add_tokens(_snake_case,*_snake_case,**_snake_case    )
							if num_added_tokens == 0:
									raise ValueError(
									    F'The tokenizer already contains the token {placeholder_token}. Please pass a different'
									    " `placeholder_token` that is not already in the tokenizer."    )

					def 				__UpperCamelCase   (    self      :       Any,_A      :       Dict,*_A      :       int,_A      :       Optional[int]=1,**_A      :       Optional[Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		str				      =    []
							if num_vec_per_token == 1:
									self.try_adding_tokens(_snake_case,*_snake_case,**_snake_case    )
									output.append(_snake_case    )
							else:
									SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    []
									for i in range(_snake_case    ):
											SCREAMING_SNAKE_CASE_  :		Any				      =    placeholder_token + F'_{i}'
											self.try_adding_tokens(_snake_case,*_snake_case,**_snake_case    )
											output.append(_snake_case    )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
							for token in self.token_map:
									if token in placeholder_token:
											raise ValueError(
											    F'The tokenizer already has placeholder token {token} that can get confused with'
											    F' {placeholder_token}keep placeholder tokens independent'    )
							SCREAMING_SNAKE_CASE_  :		Any				      =    output

					def 				__UpperCamelCase   (    self      :       int,_A      :       str,_A      :       int=False,_A      :       Optional[int]=1.0    ):







							"""simple docstring"""






							if isinstance(_snake_case,_snake_case    ):
									SCREAMING_SNAKE_CASE_  :		List[Any]				      =    []
									for i in range(len(_snake_case    )    ):
											output.append(self.replace_placeholder_tokens_in_text(text[i],vector_shuffle=_snake_case    )    )
									return output
							for placeholder_token in self.token_map:
									if placeholder_token in text:
											SCREAMING_SNAKE_CASE_  :		str				      =    self.token_map[placeholder_token]
											SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    tokens[: 1 + int(len(_snake_case    ) * prop_tokens_to_load    )]
											if vector_shuffle:
													SCREAMING_SNAKE_CASE_  :		List[Any]				      =    copy.copy(_snake_case    )
													random.shuffle(_snake_case    )
											SCREAMING_SNAKE_CASE_  :		Dict				      =    text.replace(_snake_case," ".join(_snake_case    )    )
							return text

					def __call__(    self      :       Tuple,_A      :       List[Any],*_A      :       Union[str, Any],_A      :       Optional[Any]=False,_A      :       Tuple=1.0,**_A      :       List[str]    ):







							"""simple docstring"""






							return super().__call__(
							    self.replace_placeholder_tokens_in_text(
							        _snake_case,vector_shuffle=_snake_case,prop_tokens_to_load=_snake_case    ),*_snake_case,**_snake_case,)






					def 				__UpperCamelCase   (    self      :       Any,_A      :       str,*_A      :       Optional[Any],_A      :       Tuple=False,_A      :       Optional[Any]=1.0,**_A      :       Tuple    ):







							"""simple docstring"""






							return super().encode(
							    self.replace_placeholder_tokens_in_text(
							        _snake_case,vector_shuffle=_snake_case,prop_tokens_to_load=_snake_case    ),*_snake_case,**_snake_case,)






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


snake_case_ : Any    		=       logging.get_logger(__name__)


snake_case_ : Optional[int]    		=       TypeVar("DatasetType", Dataset, IterableDataset)


def    A						(__A   :    List[DatasetType]   ,				__A   :    Optional[List[float]] = None   ,				__A   :    Optional[int] = None   ,				__A   :    Optional[DatasetInfo] = None   ,				__A   :    Optional[NamedSplit] = None   ,				__A   :    Literal["first_exhausted", "all_exhausted"] = "first_exhausted"   ,				)   ->      DatasetType:







     """simple docstring"""


     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(__A       ):
          if not isinstance(__A   ,				(Dataset, IterableDataset)       ):
               if isinstance(__A   ,				(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(__A       )}\n"""
                        F"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__A       )       )}']"""       )
               raise ValueError(
                   F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__A       ).__name__}."""       )
          if i == 0:
               UpperCAmelCase_     ,       UpperCAmelCase_          =							(
                   (Dataset, IterableDataset) if isinstance(__A   ,				__A       ) else (IterableDataset, Dataset)
               )
          elif not isinstance(__A   ,				__A       ):
               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(
              __A   ,				__A   ,				__A   ,				info=__A   ,				split=__A   ,				stopping_strategy=__A       )
     else:
          return _interleave_iterable_datasets(
              __A   ,				__A   ,				__A   ,				info=__A   ,				split=__A   ,				stopping_strategy=__A       )


def    A						(__A   :    List[DatasetType]   ,				__A   :    Optional[DatasetInfo] = None   ,				__A   :    Optional[NamedSplit] = None   ,				__A   :    int = 0   ,				)   ->      DatasetType:







     """simple docstring"""


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






