

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


A											=     logging.get_logger(__name__)

A											=     {'vocab_file': 'sentencepiece.bpe.model'}

A											=     {
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
}

A											=     {
    'moussaKam/mbarthez': 1024,
    'moussaKam/barthez': 1024,
    'moussaKam/barthez-orangesum-title': 1024,
}

A											=     '▁'


class SCREAMING_SNAKE_CASE  (		__snake_case							):






			"""simple docstring"""




			__A						  =  VOCAB_FILES_NAMES
			__A						  =  PRETRAINED_VOCAB_FILES_MAP
			__A						  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__A						  =  ["""input_ids""", """attention_mask"""]


			def __init__(    self ,				__UpperCamelCase ,				__UpperCamelCase="<s>" ,				__UpperCamelCase="</s>" ,				__UpperCamelCase="</s>" ,				__UpperCamelCase="<s>" ,				__UpperCamelCase="<unk>" ,				__UpperCamelCase="<pad>" ,				__UpperCamelCase="<mask>" ,				__UpperCamelCase = None ,				**__UpperCamelCase ,				):

				"""simple docstring"""


				snake_case_      		= AddedToken(__UpperCamelCase ,				lstrip=__UpperCamelCase ,				rstrip=__UpperCamelCase							) if isinstance(__UpperCamelCase ,				__UpperCamelCase							) else mask_token

				snake_case_      		= {} if sp_model_kwargs is None else sp_model_kwargs

				super().__init__(
				    bos_token=__UpperCamelCase ,				eos_token=__UpperCamelCase ,				unk_token=__UpperCamelCase ,				sep_token=__UpperCamelCase ,				cls_token=__UpperCamelCase ,				pad_token=__UpperCamelCase ,				mask_token=__UpperCamelCase ,				sp_model_kwargs=self.sp_model_kwargs ,				**__UpperCamelCase ,				)

				snake_case_      		= vocab_file
				snake_case_      		= spm.SentencePieceProcessor(**self.sp_model_kwargs							)
				self.sp_model.Load(str(__UpperCamelCase							)							)

				snake_case_      		= {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

				snake_case_      		= len(self.sp_model							) - 1
				snake_case_      		= {v: k for k, v in self.fairseq_tokens_to_ids.items()}


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase ,				__UpperCamelCase = None							):

				"""simple docstring"""


				if token_ids_a is None:
					return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
				snake_case_      		= [self.cls_token_id]
				snake_case_      		= [self.sep_token_id]
				return cls + token_ids_a + sep + sep + token_ids_a + sep


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase ,				__UpperCamelCase = None ,				__UpperCamelCase = False							):

				"""simple docstring"""


				if already_has_special_tokens:
					return super().get_special_tokens_mask(
					    token_ids_a=__UpperCamelCase ,				token_ids_a=__UpperCamelCase ,				already_has_special_tokens=__UpperCamelCase							)

				if token_ids_a is None:
					return [1] + ([0] * len(__UpperCamelCase							)) + [1]
				return [1] + ([0] * len(__UpperCamelCase							)) + [1, 1] + ([0] * len(__UpperCamelCase							)) + [1]


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase ,				__UpperCamelCase = None							):

				"""simple docstring"""


				snake_case_      		= [self.sep_token_id]
				snake_case_      		= [self.cls_token_id]

				if token_ids_a is None:
					return len(cls + token_ids_a + sep							) * [0]
				return len(cls + token_ids_a + sep + sep + token_ids_a + sep							) * [0]


			@property
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				return len(self.sp_model							)


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				snake_case_      		= {self.convert_ids_to_tokens(__UpperCamelCase							): i for i in range(self.vocab_size							)}
				vocab.update(self.added_tokens_encoder							)
				return vocab


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return self.sp_model.encode(__UpperCamelCase ,				out_type=__UpperCamelCase							)


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				if token in self.fairseq_tokens_to_ids:
					return self.fairseq_tokens_to_ids[token]
				snake_case_      		= self.sp_model.PieceToId(__UpperCamelCase							)

				return spm_id if spm_id else self.unk_token_id


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				if index in self.fairseq_ids_to_tokens:
					return self.fairseq_ids_to_tokens[index]
				return self.sp_model.IdToPiece(__UpperCamelCase							)


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= []
				snake_case_      		= ''
				snake_case_      		= False
				for token in tokens:
					# make sure that special tokens are not decoded using sentencepiece model
					if token in self.all_special_tokens:
						if not prev_is_special:
							out_string += " "
						out_string += self.sp_model.decode(__UpperCamelCase							) + token
						snake_case_      		= True
						snake_case_      		= []
					else:
						current_sub_tokens.append(__UpperCamelCase							)
						snake_case_      		= False
				out_string += self.sp_model.decode(__UpperCamelCase							)
				return out_string.strip()


			def __getstate__(    self							):

				"""simple docstring"""


				snake_case_      		= self.__dict__.copy()
				snake_case_      		= None
				return state


			def __setstate__(    self ,				__UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= d

				# for backward compatibility
				if not hasattr(self ,				'sp_model_kwargs'							):
					snake_case_      		= {}

				snake_case_      		= spm.SentencePieceProcessor(**self.sp_model_kwargs							)
				self.sp_model.Load(self.vocab_file							)







			def 			__lowerCAmelCase (    self ,				__UpperCamelCase ,				__UpperCamelCase = None							):

				"""simple docstring"""


				if not os.path.isdir(__UpperCamelCase							):
					logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
					return
				snake_case_      		= os.path.join(
				    __UpperCamelCase ,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']							)

				if os.path.abspath(self.vocab_file							) != os.path.abspath(__UpperCamelCase							) and os.path.isfile(self.vocab_file							):
					copyfile(self.vocab_file ,				__UpperCamelCase							)
				elif not os.path.isfile(self.vocab_file							):
					with open(__UpperCamelCase ,				'wb'							) as fi:
						snake_case_      		= self.sp_model.serialized_model_proto()
						fi.write(__UpperCamelCase							)

				return (out_vocab_file,)



from collections import defaultdict





def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= first_str.lower().strip()
	snake_case_      		= second_str.lower().strip()

	# Remove whitespace
	snake_case_      		= first_str.replace(' '			, ''	)
	snake_case_      		= second_str.replace(' '			, ''	)

	# Strings of different lengths are not anagrams
	if len(lowercase__	) != len(lowercase__	):
		return False

	# Default values for count should be 0
	snake_case_      		= defaultdict(lowercase__	)

	# For each character in input strings,
	# increment count in the corresponding
	for i in range(len(lowercase__	)	):
		count[first_str[i]] += 1
		count[second_str[i]] -= 1

	return all(_count == 0 for _count in count.values()	)


if __name__ == "__main__":
		from doctest import testmod

		testmod()
		A											=     input('Enter the first string ').strip()
		A											=     input('Enter the second string ').strip()

		A											=     check_anagrams(input_a, input_b)
		print(f"""{input_a} and {input_b} are {"" if status else "not "}anagrams.""")
