





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_a						=   logging.get_logger(__name__)

_a						=   {
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			lowerCAmelCase_							  =		"""roberta-prelayernorm"""





			def __init__(					self ,						__lowerCAmelCase=5_0_2_6_5 ,						__lowerCAmelCase=7_6_8 ,						__lowerCAmelCase=1_2 ,						__lowerCAmelCase=1_2 ,						__lowerCAmelCase=3_0_7_2 ,						__lowerCAmelCase="gelu" ,						__lowerCAmelCase=0.1 ,						__lowerCAmelCase=0.1 ,						__lowerCAmelCase=5_1_2 ,						__lowerCAmelCase=2 ,						__lowerCAmelCase=0.02 ,						__lowerCAmelCase=1E-12 ,						__lowerCAmelCase=1 ,						__lowerCAmelCase=0 ,						__lowerCAmelCase=2 ,						__lowerCAmelCase="absolute" ,						__lowerCAmelCase=True ,						__lowerCAmelCase=None ,						**__lowerCAmelCase ,						):



				'''simple docstring'''







				super().__init__(pad_token_id=__lowerCAmelCase ,						bos_token_id=__lowerCAmelCase ,						eos_token_id=__lowerCAmelCase ,						**__lowerCAmelCase							)

				lowerCamelCase__              =	vocab_size
				lowerCamelCase__              =	hidden_size
				lowerCamelCase__              =	num_hidden_layers
				lowerCamelCase__              =	num_attention_heads
				lowerCamelCase__              =	hidden_act
				lowerCamelCase__              =	intermediate_size
				lowerCamelCase__              =	hidden_dropout_prob
				lowerCamelCase__              =	attention_probs_dropout_prob
				lowerCamelCase__              =	max_position_embeddings
				lowerCamelCase__              =	type_vocab_size
				lowerCamelCase__              =	initializer_range
				lowerCamelCase__              =	layer_norm_eps
				lowerCamelCase__              =	position_embedding_type
				lowerCamelCase__              =	use_cache
				lowerCamelCase__              =	classifier_dropout






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			@property
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				if self.task == "multiple-choice":
					lowerCamelCase__              =	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
					lowerCamelCase__              =	{0: '''batch''', 1: '''sequence'''}
				return OrderedDict(
				    [
				        ('''input_ids''', dynamic_axis),
				        ('''attention_mask''', dynamic_axis),
				    ]							)










import string
from math import logaa





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   int:







	'''simple docstring'''







	lowerCamelCase__              =	document.translate(
	    str.maketrans('''''' ,'''''' ,string.punctuation							)							).replace('''\n''' ,''''''							)
	lowerCamelCase__              =	document_without_punctuation.split(''' '''							)  # word tokenization
	return len([word for word in tokenize_document if word.lower() == term.lower()]							)





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   tuple[int, int]:







	'''simple docstring'''







	lowerCamelCase__              =	corpus.lower().translate(
	    str.maketrans('''''' ,'''''' ,string.punctuation							)							)  # strip all punctuation and replace it with ''
	lowerCamelCase__              =	corpus_without_punctuation.split('''\n'''							)
	lowerCamelCase__              =	term.lower()
	return (len([doc for doc in docs if term in doc]							), len(__snake_case							))





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case=False							)       ->   float:







	'''simple docstring'''







	if smoothing:
		if n == 0:
			raise ValueError('''log10(0) is undefined.'''							)
		return round(1 + logaa(n / (1 + df)							) ,3							)

	if df == 0:
		raise ZeroDivisionError('''df must be > 0'''							)
	elif n == 0:
		raise ValueError('''log10(0) is undefined.'''							)
	return round(logaa(n / df							) ,3							)





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   float:







	'''simple docstring'''







	return round(tf * idf ,3							)



