



'''simple docstring'''




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


lowerCamelCase				:Union[str, Any]							       =   logging.get_logger(__name__)

lowerCamelCase				:Optional[Any]							       =   {
    "uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
}







class       _lowerCAmelCase				(     __UpperCAmelCase					):
	__SCREAMING_SNAKE_CASE  :						Dict						     =   'mra'


	def __init__(self			, lowercase=50265			, lowercase=768			, lowercase=12			, lowercase=12			, lowercase=3072			, lowercase="gelu"			, lowercase=0.1			, lowercase=0.1			, lowercase=512			, lowercase=1			, lowercase=0.02			, lowercase=1E-5			, lowercase="absolute"			, lowercase=4			, lowercase="full"			, lowercase=0			, lowercase=0			, lowercase=1			, lowercase=0			, lowercase=2			, **lowercase			, ):
				super().__init__(pad_token_id=snake_case__			, bos_token_id=snake_case__			, eos_token_id=snake_case__			, **snake_case__				)

				A_      :		Dict      =	vocab_size
				A_      :		Optional[Any]      =	max_position_embeddings
				A_      :		Any      =	hidden_size
				A_      :		str      =	num_hidden_layers
				A_      :		Dict      =	num_attention_heads
				A_      :		int      =	intermediate_size
				A_      :		int      =	hidden_act
				A_      :		Optional[int]      =	hidden_dropout_prob
				A_      :		Union[str, Any]      =	attention_probs_dropout_prob
				A_      :		Any      =	initializer_range
				A_      :		List[Any]      =	type_vocab_size
				A_      :		str      =	layer_norm_eps
				A_      :		Tuple      =	position_embedding_type
				A_      :		List[Any]      =	block_per_row
				A_      :		Optional[int]      =	approx_mode
				A_      :		Optional[Any]      =	initial_prior_first_n_blocks
				A_      :		Union[str, Any]      =	initial_prior_diagonal_n_blocks


import re

from filelock import FileLock


try:
      import nltk

      a_     :    Optional[Any]     		=   True
except (ImportError, ModuleNotFoundError):
      a_     :    Union[str, Any]     		=   False

if NLTK_AVAILABLE:
      with FileLock(".lock") as lock:
            nltk.download("punkt", quiet=True)


def 							__lowerCAmelCase     (							_UpperCamelCase		:	str						)		->				str:
 '''simple docstring'''


 re.sub('<n>'		,				''		,				_UpperCamelCase						)  # remove pegasus newline char
 assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
 return "\n".join(nltk.sent_tokenize(_UpperCamelCase						)						)

