




lowerCamelCase    :		Any			   =       "2.13.1"

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("3.7"):
 raise ImportWarning(
     "To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."
 )

if version.parse(pyarrow.__version__).major < 8:
 raise ImportWarning(
     "To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"
     "If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."
 )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

lowerCamelCase    :		List[str]			   =       concatenate_datasets
lowerCamelCase    :		Union[str, Any]			   =       DownloadConfig
lowerCamelCase    :		Tuple			   =       DownloadManager
lowerCamelCase    :		Optional[Any]			   =       DownloadMode
lowerCamelCase    :		Any			   =       DownloadConfig
lowerCamelCase    :		str			   =       DownloadMode
lowerCamelCase    :		int			   =       DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager









from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase    :		Optional[Any]			   =       logging.get_logger(__name__)

lowerCamelCase    :		Tuple			   =       {
    "transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}







class   A(						UpperCamelCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						'''transfo-xl'''
 UpperCamelCase						       =						['''mems''']
 UpperCamelCase						       =						{
     '''n_token''': '''vocab_size''',
     '''hidden_size''': '''d_model''',
     '''num_attention_heads''': '''n_head''',
     '''num_hidden_layers''': '''n_layer''',
 }

 def __init__(    self :  Any						,							A_ :  Optional[Any]=267735						,							A_ :  Optional[Any]=[20000, 40000, 200000]						,							A_ :  Union[str, Any]=1024						,							A_ :  Optional[Any]=1024						,							A_ :  Optional[int]=16						,							A_ :  Any=64						,							A_ :  List[Any]=4096						,							A_ :  str=4						,							A_ :  int=False						,							A_ :  List[Any]=18						,							A_ :  Optional[int]=1600						,							A_ :  Union[str, Any]=1000						,							A_ :  Optional[Any]=True						,							A_ :  Optional[int]=True						,							A_ :  List[str]=0						,							A_ :  int=-1						,							A_ :  List[Any]=True						,							A_ :  List[Any]=0.1						,							A_ :  str=0.0						,							A_ :  Dict=True						,							A_ :  Dict="normal"						,							A_ :  Dict=0.01						,							A_ :  Optional[Any]=0.01						,							A_ :  Any=0.02						,							A_ :  int=1E-5						,							A_ :  List[str]=0						,							**A_ :  Optional[Any]						,							)       ->     Optional[int]:

       """simple docstring"""






       lowerCamelCase_							=   vocab_size
       lowerCamelCase_							=   []
       self.cutoffs.extend(A_  )
       if proj_share_all_but_first:
             lowerCamelCase_							=   [False] + [True] * len(self.cutoffs  )
       else:
             lowerCamelCase_							=   [False] + [False] * len(self.cutoffs  )
       lowerCamelCase_							=   d_model
       lowerCamelCase_							=   d_embed
       lowerCamelCase_							=   d_head
       lowerCamelCase_							=   d_inner
       lowerCamelCase_							=   div_val
       lowerCamelCase_							=   pre_lnorm
       lowerCamelCase_							=   n_layer
       lowerCamelCase_							=   n_head
       lowerCamelCase_							=   mem_len
       lowerCamelCase_							=   same_length
       lowerCamelCase_							=   attn_type
       lowerCamelCase_							=   clamp_len
       lowerCamelCase_							=   sample_softmax
       lowerCamelCase_							=   adaptive
       lowerCamelCase_							=   dropout
       lowerCamelCase_							=   dropatt
       lowerCamelCase_							=   untie_r
       lowerCamelCase_							=   init
       lowerCamelCase_							=   init_range
       lowerCamelCase_							=   proj_init_std
       lowerCamelCase_							=   init_std
       lowerCamelCase_							=   layer_norm_epsilon
       super().__init__(eos_token_id=A_						,							**A_  )

 @property
 def     a__			(    self :  Tuple  )       ->     Any:

       """simple docstring"""






       logger.info(f"""The model {self.model_type} is one of the few models that has no sequence length limit."""  )
       return -1





 @max_position_embeddings.setter
 def     a__			(    self :  Dict						,							A_ :  Optional[int]  )       ->     List[Any]:

       """simple docstring"""






       raise NotImplementedError(
           f"""The model {self.model_type} is one of the few models that has no sequence length limit."""  )



