





# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

A   : 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

A   : Dict			=				concatenate_datasets
A   : Dict			=				DownloadConfig
A   : Dict			=				DownloadManager
A   : Dict			=				DownloadMode
A   : Optional[int]			=				DownloadConfig
A   : Dict			=				DownloadMode
A   : Dict			=				DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager










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


A   : Dict			=				logging.get_logger(__name__)

A   : Dict			=				{
    '''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}


class   A      (SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''




			__lowerCamelCase     :	Tuple          =   '''pegasus'''
			__lowerCamelCase     :	Any          =   ['''past_key_values''']
			__lowerCamelCase     :	List[str]          =   {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}






			def __init__(      self       :   List[Any]							,     __lowerCAmelCase       :   str=5_02_65							,     __lowerCAmelCase       :   Dict=10_24							,     __lowerCAmelCase       :   Union[str, Any]=12							,     __lowerCAmelCase       :   Any=40_96							,     __lowerCAmelCase       :   Optional[Any]=16							,     __lowerCAmelCase       :   Dict=12							,     __lowerCAmelCase       :   Optional[int]=40_96							,     __lowerCAmelCase       :   Dict=16							,     __lowerCAmelCase       :   Optional[int]=0.0							,     __lowerCAmelCase       :   Optional[Any]=0.0							,     __lowerCAmelCase       :   Union[str, Any]=True							,     __lowerCAmelCase       :   List[str]=True							,     __lowerCAmelCase       :   str="gelu"							,     __lowerCAmelCase       :   Union[str, Any]=10_24							,     __lowerCAmelCase       :   Union[str, Any]=0.1							,     __lowerCAmelCase       :   Dict=0.0							,     __lowerCAmelCase       :   Union[str, Any]=0.0							,     __lowerCAmelCase       :   Union[str, Any]=0.0_2							,     __lowerCAmelCase       :   List[Any]=0							,     __lowerCAmelCase       :   str=False							,     __lowerCAmelCase       :   int=0							,     __lowerCAmelCase       :   Optional[Any]=1							,     __lowerCAmelCase       :   Optional[int]=1							,     **__lowerCAmelCase       :   Dict							,     )     ->     Dict:







					"""simple docstring"""






					A__  				=       vocab_size
					A__  				=       max_position_embeddings
					A__  				=       d_model
					A__  				=       encoder_ffn_dim
					A__  				=       encoder_layers
					A__  				=       encoder_attention_heads
					A__  				=       decoder_ffn_dim
					A__  				=       decoder_layers
					A__  				=       decoder_attention_heads
					A__  				=       dropout
					A__  				=       attention_dropout
					A__  				=       activation_dropout
					A__  				=       activation_function
					A__  				=       init_std
					A__  				=       encoder_layerdrop
					A__  				=       decoder_layerdrop
					A__  				=       use_cache
					A__  				=       encoder_layers
					A__  				=       scale_embedding  # scale factor will be sqrt(d_model) if True
					super().__init__(
					    pad_token_id=__lowerCAmelCase							,     eos_token_id=__lowerCAmelCase							,     is_encoder_decoder=__lowerCAmelCase							,     decoder_start_token_id=__lowerCAmelCase							,     forced_eos_token_id=__lowerCAmelCase							,     **__lowerCAmelCase							,     )






			@property
			def        a_	(      self       :   Dict       )     ->     int:







					"""simple docstring"""






					return self.encoder_attention_heads







			@property
			def        a_	(      self       :   Optional[Any]       )     ->     int:







					"""simple docstring"""






					return self.d_model



