


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


__lowerCamelCase        =     logging.get_logger(__name__)


__lowerCamelCase        =     TypeVar('''DatasetType''', Dataset, IterableDataset)



def  _a			(						__UpperCamelCase  ,  __UpperCamelCase = None  ,  __UpperCamelCase = None  ,  __UpperCamelCase = None  ,  __UpperCamelCase = None  ,  __UpperCamelCase = "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(__UpperCamelCase ):
          if not isinstance(__UpperCamelCase  ,  (Dataset, IterableDataset) ):
               if isinstance(__UpperCamelCase  ,  (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(__UpperCamelCase )}\n'''
                        F'''Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(__UpperCamelCase ) )}\']''' )
               raise ValueError(
                   F'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__UpperCamelCase ).__name__}.''' )
          if i == 0:
               a_			,			a_    :     List[str]										=    (
                   (Dataset, IterableDataset) if isinstance(__UpperCamelCase  ,  __UpperCamelCase ) else (IterableDataset, Dataset)
               )
          elif not isinstance(__UpperCamelCase  ,  __UpperCamelCase ):
               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(
              __UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase  ,  info=__UpperCamelCase  ,  split=__UpperCamelCase  ,  stopping_strategy=__UpperCamelCase )
     else:
          return _interleave_iterable_datasets(
              __UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase  ,  info=__UpperCamelCase  ,  split=__UpperCamelCase  ,  stopping_strategy=__UpperCamelCase )



def  _a			(						__UpperCamelCase  ,  __UpperCamelCase = None  ,  __UpperCamelCase = None  ,  __UpperCamelCase = 0  ,  ):

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







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCamelCase        =     {
    '''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''PegasusXForConditionalGeneration''',
           '''PegasusXModel''',
           '''PegasusXPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_pegasus_x import (
                  PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
                  PegasusXForConditionalGeneration,
                  PegasusXModel,
                  PegasusXPreTrainedModel,
              )


else:
       import sys

       __lowerCamelCase        =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



