
'''simple docstring'''







import json
import os
import re
import warnings
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_lowercase				:						Optional[int]												= logging.get_logger(__name__)

_lowercase				:						Dict												= {
    "source_spm": "source.spm",
    "target_spm": "target.spm",
    "vocab": "vocab.json",
    "target_vocab_file": "target_vocab.json",
    "tokenizer_config_file": "tokenizer_config.json",
}

_lowercase				:						int												= {
    "source_spm": {
        "Helsinki-NLP/opus-mt-en-de": "https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/source.spm"
    },
    "target_spm": {
        "Helsinki-NLP/opus-mt-en-de": "https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/target.spm"
    },
    "vocab": {
        "Helsinki-NLP/opus-mt-en-de": "https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/vocab.json"
    },
    "tokenizer_config_file": {
        "Helsinki-NLP/opus-mt-en-de": (
            "https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/tokenizer_config.json"
        )
    },
}

_lowercase				:						int												= {"Helsinki-NLP/opus-mt-en-de": 5_1_2}
_lowercase				:						str												= {}






class 				lowerCAmelCase__     (						lowerCamelCase_  ):
					lowerCAmelCase_       =  VOCAB_FILES_NAMES
					lowerCAmelCase_       =  PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_       =  PRETRAINED_INIT_CONFIGURATION
					lowerCAmelCase_       =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_       =  ['''input_ids''', '''attention_mask''']
					lowerCAmelCase_       =  re.compile('''>>.+<<'''  )  # type: re.Pattern






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE="<unk>"       ,							__SCREAMING_SNAKE_CASE="</s>"       ,							__SCREAMING_SNAKE_CASE="<pad>"       ,							__SCREAMING_SNAKE_CASE=5_12       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE=False       ,							**__SCREAMING_SNAKE_CASE       ,							):


											"""simple docstring"""





											lowercase_			:  int									= {} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    # bos_token=bos_token,  unused. Start decoding with config.decoder_start_token_id
											    source_lang=__SCREAMING_SNAKE_CASE       ,							target_lang=__SCREAMING_SNAKE_CASE       ,							unk_token=__SCREAMING_SNAKE_CASE       ,							eos_token=__SCREAMING_SNAKE_CASE       ,							pad_token=__SCREAMING_SNAKE_CASE       ,							model_max_length=__SCREAMING_SNAKE_CASE       ,							sp_model_kwargs=self.sp_model_kwargs       ,							target_vocab_file=__SCREAMING_SNAKE_CASE       ,							separate_vocabs=__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE       ,							)
											assert Path(__SCREAMING_SNAKE_CASE	).exists(), F'''cannot find spm source {source_spm}'''

											lowercase_			:  List[Any]									= separate_vocabs
											lowercase_			:  List[str]									= load_json(__SCREAMING_SNAKE_CASE	)
											if self.unk_token not in self.encoder:
																	raise KeyError('''<unk> token must be in vocab'''	)
											assert self.pad_token in self.encoder

											if separate_vocabs:
																	lowercase_			:  str									= load_json(__SCREAMING_SNAKE_CASE	)
																	lowercase_			:  Union[str, Any]									= {v: k for k, v in self.target_encoder.items()}
																	lowercase_			:  Union[str, Any]									= []
											else:
																	lowercase_			:  str									= {v: k for k, v in self.encoder.items()}
																	lowercase_			:  list									= [k for k in self.encoder if k.startswith('''>>'''	) and k.endswith('''<<'''	)]

											lowercase_			:  Optional[Any]									= source_lang
											lowercase_			:  Union[str, Any]									= target_lang
											lowercase_			:  List[Any]									= [source_spm, target_spm]

											# load SentencePiece model for pre-processing
											lowercase_			:  Optional[int]									= load_spm(__SCREAMING_SNAKE_CASE       ,							self.sp_model_kwargs	)
											lowercase_			:  Optional[int]									= load_spm(__SCREAMING_SNAKE_CASE       ,							self.sp_model_kwargs	)
											lowercase_			:  str									= self.spm_source
											lowercase_			:  Optional[Any]									= self.encoder

											# Multilingual target side: default to using first supported language code.

											self._setup_normalizer()






					def 			_snake_case					(     self	):


											"""simple docstring"""





											try:
																	from sacremoses import MosesPunctNormalizer

																	lowercase_			:  Union[str, Any]									= MosesPunctNormalizer(self.source_lang	).normalize
											except (ImportError, FileNotFoundError):
																	warnings.warn('''Recommended: pip install sacremoses.'''	)
																	lowercase_			:  Optional[Any]									= lambda __SCREAMING_SNAKE_CASE	: x






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return self.punc_normalizer(__SCREAMING_SNAKE_CASE	) if x else ""






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return self.current_encoder.get(__SCREAMING_SNAKE_CASE       ,							self.current_encoder[self.unk_token]	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Dict									= self.language_code_re.match(__SCREAMING_SNAKE_CASE	)
											lowercase_			:  list									= [match.group(0	)] if match else []
											return code, self.language_code_re.sub(''''''       ,							__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_		,				lowercase_			:  str									= self.remove_language_code(__SCREAMING_SNAKE_CASE	)
											lowercase_			:  Any									= self.current_spm.encode(__SCREAMING_SNAKE_CASE       ,							out_type=__SCREAMING_SNAKE_CASE	)
											return code + pieces






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return self.decoder.get(__SCREAMING_SNAKE_CASE       ,							self.unk_token	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return super().batch_decode(__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return super().decode(__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  List[Any]									= self.spm_source if self._decode_use_source_tokenizer else self.spm_target
											lowercase_			:  Dict									= []
											lowercase_			:  List[str]									= ''''''
											for token in tokens:
																	# make sure that special tokens are not decoded using sentencepiece model
																	if token in self.all_special_tokens:
																							out_string += sp_model.decode_pieces(__SCREAMING_SNAKE_CASE	) + token + " "
																							lowercase_			:  Optional[int]									= []
																	else:
																							current_sub_tokens.append(__SCREAMING_SNAKE_CASE	)
											out_string += sp_model.decode_pieces(__SCREAMING_SNAKE_CASE	)
											return out_string.strip()






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE=None	):


											"""simple docstring"""





											if token_ids_a is None:
																	return token_ids_a + [self.eos_token_id]
											# We don't expect to process pairs, but leave the pair logic for API consistency
											return token_ids_a + token_ids_a + [self.eos_token_id]






					def 			_snake_case					(     self	):


											"""simple docstring"""





											lowercase_			:  Optional[Any]									= self.spm_source
											lowercase_			:  Tuple									= self.encoder






					def 			_snake_case					(     self	):


											"""simple docstring"""





											lowercase_			:  int									= self.spm_target
											if self.separate_vocabs:
																	lowercase_			:  Dict									= self.target_encoder






					@property
					def 			_snake_case					(     self	):


											"""simple docstring"""





											return len(self.encoder	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE = None	):


											"""simple docstring"""





											if not os.path.isdir(__SCREAMING_SNAKE_CASE	):
																	logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''	)
																	return
											lowercase_			:  List[Any]									= []

											if self.separate_vocabs:
																	lowercase_			:  List[Any]									= os.path.join(
																	    __SCREAMING_SNAKE_CASE       ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']       ,							)
																	lowercase_			:  Dict									= os.path.join(
																	    __SCREAMING_SNAKE_CASE       ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''target_vocab_file''']       ,							)
																	save_json(self.encoder       ,							__SCREAMING_SNAKE_CASE	)
																	save_json(self.target_encoder       ,							__SCREAMING_SNAKE_CASE	)
																	saved_files.append(__SCREAMING_SNAKE_CASE	)
																	saved_files.append(__SCREAMING_SNAKE_CASE	)
											else:
																	lowercase_			:  Union[str, Any]									= os.path.join(
																	    __SCREAMING_SNAKE_CASE       ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']	)
																	save_json(self.encoder       ,							__SCREAMING_SNAKE_CASE	)
																	saved_files.append(__SCREAMING_SNAKE_CASE	)

											for spm_save_filename, spm_orig_path, spm_model in zip(
											    [VOCAB_FILES_NAMES['''source_spm'''], VOCAB_FILES_NAMES['''target_spm''']]       ,							self.spm_files       ,							[self.spm_source, self.spm_target]       ,							):
																	lowercase_			:  Dict									= os.path.join(
																	    __SCREAMING_SNAKE_CASE       ,							(filename_prefix + '''-''' if filename_prefix else '''''') + spm_save_filename	)
																	if os.path.abspath(__SCREAMING_SNAKE_CASE	) != os.path.abspath(__SCREAMING_SNAKE_CASE	) and os.path.isfile(__SCREAMING_SNAKE_CASE	):
																							copyfile(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	)
																							saved_files.append(__SCREAMING_SNAKE_CASE	)
																	elif not os.path.isfile(__SCREAMING_SNAKE_CASE	):
																							with open(__SCREAMING_SNAKE_CASE       ,							'''wb'''	) as fi:
																													lowercase_			:  Tuple									= spm_model.serialized_model_proto()
																													fi.write(__SCREAMING_SNAKE_CASE	)
																							saved_files.append(__SCREAMING_SNAKE_CASE	)

											return tuple(__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self	):


											"""simple docstring"""





											return self.get_src_vocab()






					def 			_snake_case					(     self	):


											"""simple docstring"""





											return dict(self.encoder       ,							**self.added_tokens_encoder	)






					def 			_snake_case					(     self	):


											"""simple docstring"""





											return dict(self.target_encoder       ,							**self.added_tokens_decoder	)






					def __getstate__(     self	):


											"""simple docstring"""





											lowercase_			:  List[str]									= self.__dict__.copy()
											state.update(
											    {k: None for k in ['''spm_source''', '''spm_target''', '''current_spm''', '''punc_normalizer''', '''target_vocab_file''']}	)
											return state






					def __setstate__(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Optional[Any]									= d

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

											lowercase_		,				lowercase_			:  Any									= (load_spm(__SCREAMING_SNAKE_CASE       ,							self.sp_model_kwargs	) for f in self.spm_files)
											lowercase_			:  List[str]									= self.spm_source
											self._setup_normalizer()






					def 			_snake_case					(     self       ,							*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return 1






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  List[Any]									= set(self.all_special_ids	)  # call it once instead of inside list comp
											all_special_ids.remove(self.unk_token_id	)  # <unk> is only sometimes special
											return [1 if x in all_special_ids else 0 for x in seq]






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE = False	):


											"""simple docstring"""





											if already_has_special_tokens:
																	return self._special_token_mask(__SCREAMING_SNAKE_CASE	)
											elif token_ids_a is None:
																	return self._special_token_mask(__SCREAMING_SNAKE_CASE	) + [1]
											else:
																	return self._special_token_mask(token_ids_a + token_ids_a	) + [1]







def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				str   ,   __SCREAMING_SNAKE_CASE      :				Dict[str, Any]							):



						"""simple docstring"""





						lowercase_			:  Optional[int]									= sentencepiece.SentencePieceProcessor(**__SCREAMING_SNAKE_CASE							)
						spm.Load(__SCREAMING_SNAKE_CASE							)
						return spm
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				str   ,   __SCREAMING_SNAKE_CASE      :				str							):



						"""simple docstring"""





						with open(__SCREAMING_SNAKE_CASE   ,   '''w'''							) as f:
												json.dump(__SCREAMING_SNAKE_CASE   ,   __SCREAMING_SNAKE_CASE   ,   indent=2							)




def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				str							):



						"""simple docstring"""





						with open(__SCREAMING_SNAKE_CASE   ,   '''r'''							) as f:
												return json.load(__SCREAMING_SNAKE_CASE							)





'''simple docstring'''







from itertools import combinations, product
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int   ,   __SCREAMING_SNAKE_CASE      :				int   ,   __SCREAMING_SNAKE_CASE      :				int   ,   __SCREAMING_SNAKE_CASE      :				int							):



						"""simple docstring"""





						if xa == ya == 0 or xa == ya == 0:
												return False
						lowercase_			:  Optional[Any]									= xa * xa + ya * ya
						lowercase_			:  List[str]									= xa * xa + ya * ya
						lowercase_			:  Any									= (xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
						return (
						    a_square + b_square == c_square
						    or a_square + c_square == b_square
						    or b_square + c_square == a_square
						)
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 50							):



						"""simple docstring"""





						return sum(
						    1
						    for pta, pta in combinations(product(range(limit + 1							)   ,   repeat=2							)   ,   2							)
						    if is_right(*__SCREAMING_SNAKE_CASE   ,   *__SCREAMING_SNAKE_CASE							)							)


if __name__ == "__main__":
							print(f"""{solution() = }""")



