





import logging

from transformers import PretrainedConfig


UpperCAmelCase_           =	logging.getLogger(__name__)


UpperCAmelCase_           =	{
    "bertabs-finetuned-cnndm": "https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json",
}




class 			__UpperCamelCase    (							A__    ):
     __A	:  Tuple							  =   """bertabs"""





     def __init__(     self				,							_UpperCamelCase=30522				,							_UpperCamelCase=512				,							_UpperCamelCase=6				,							_UpperCamelCase=512				,							_UpperCamelCase=8				,							_UpperCamelCase=512				,							_UpperCamelCase=0.2				,							_UpperCamelCase=6				,							_UpperCamelCase=768				,							_UpperCamelCase=8				,							_UpperCamelCase=2048				,							_UpperCamelCase=0.2				,							**_UpperCamelCase				,							):
        super().__init__(**_UpperCamelCase					)

        _UpperCAmelCase           =   vocab_size
        _UpperCAmelCase           =   max_pos

        _UpperCAmelCase           =   enc_layers
        _UpperCAmelCase           =   enc_hidden_size
        _UpperCAmelCase           =   enc_heads
        _UpperCAmelCase           =   enc_ff_size
        _UpperCAmelCase           =   enc_dropout

        _UpperCAmelCase           =   dec_layers
        _UpperCAmelCase           =   dec_hidden_size
        _UpperCAmelCase           =   dec_heads
        _UpperCAmelCase           =   dec_ff_size
        _UpperCAmelCase           =   dec_dropout



from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class 						lowerCamelCase_							(					lowerCAmelCase__					):



					'''simple docstring'''







					def __init__(					self			,							snake_case_			,							snake_case_ = None			,							snake_case_ = None			,							snake_case_ = None			,							snake_case_ = False			,							snake_case_ = False			,							snake_case_ = None			,							**snake_case_			,							) ->      Dict:







								'''simple docstring'''

								super().__init__(
								    snake_case_			,							split=snake_case_			,							features=snake_case_			,							cache_dir=snake_case_			,							keep_in_memory=snake_case_			,							streaming=snake_case_			,							num_proc=snake_case_			,							**snake_case_			,							)
								__lowercase			       = path_or_paths if isinstance(snake_case_			,							snake_case_    ) else {self.split: path_or_paths}
								__lowercase			       = Text(
								    cache_dir=snake_case_			,							data_files=snake_case_			,							features=snake_case_			,							**snake_case_			,							)






					def A   (					self    ) ->      int:







								'''simple docstring'''

								if self.streaming:
											__lowercase			       = self.builder.as_streaming_dataset(split=self.split    )
								# Build regular (map-style) dataset
								else:
											__lowercase			       = None
											__lowercase			       = None
											__lowercase			       = None
											__lowercase			       = None

											self.builder.download_and_prepare(
											    download_config=snake_case_			,							download_mode=snake_case_			,							verification_mode=snake_case_			,							base_path=snake_case_			,							num_proc=self.num_proc			,							)
											__lowercase			       = self.builder.as_dataset(
											    split=self.split			,							verification_mode=snake_case_			,							in_memory=self.keep_in_memory    )
								return dataset


