



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

import sentencepiece as spm

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


lowerCAmelCase__					  =  logging.get_logger(__name__)

lowerCAmelCase__					  =  '''▁'''

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

lowerCAmelCase__					  =  {
    '''vocab_file''': {
        '''facebook/mbart-large-50-one-to-many-mmt''': (
            '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'''
        ),
    }
}

lowerCAmelCase__					  =  {
    '''facebook/mbart-large-50-one-to-many-mmt''': 1_0_2_4,
}

# fmt: off
lowerCAmelCase__					  =  ['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''', '''af_ZA''', '''az_AZ''', '''bn_IN''', '''fa_IR''', '''he_IL''', '''hr_HR''', '''id_ID''', '''ka_GE''', '''km_KH''', '''mk_MK''', '''ml_IN''', '''mn_MN''', '''mr_IN''', '''pl_PL''', '''ps_AF''', '''pt_XX''', '''sv_SE''', '''sw_KE''', '''ta_IN''', '''te_IN''', '''th_TH''', '''tl_XX''', '''uk_UA''', '''ur_PK''', '''xh_ZA''', '''gl_ES''', '''sl_SI''']

class 				snake_case__(_UpperCamelCase      ):

					"""simple docstring"""






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

					lowercase_								=		[]
					lowercase_								=		[]







					def __init__(							self :     Any				,       SCREAMING_SNAKE_CASE :     str				,       SCREAMING_SNAKE_CASE :     int=None				,       SCREAMING_SNAKE_CASE :     str=None				,       SCREAMING_SNAKE_CASE :     List[str]="</s>"				,       SCREAMING_SNAKE_CASE :     List[str]="</s>"				,       SCREAMING_SNAKE_CASE :     Tuple="<s>"				,       SCREAMING_SNAKE_CASE :     Optional[Any]="<unk>"				,       SCREAMING_SNAKE_CASE :     Tuple="<pad>"				,       SCREAMING_SNAKE_CASE :     int="<mask>"				,       SCREAMING_SNAKE_CASE :     Optional[Dict[str, Any]] = None				,       **SCREAMING_SNAKE_CASE :     Tuple				,       ):
								# Mask token behave like a normal word, i.e. include the space before it
								lowercase__					:   str													=					AddedToken(SCREAMING_SNAKE_CASE				,       lstrip=SCREAMING_SNAKE_CASE				,       rstrip=SCREAMING_SNAKE_CASE					) if isinstance(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE					) else mask_token

								lowercase__					:   Optional[int]													=					{} if sp_model_kwargs is None else sp_model_kwargs

								lowercase__					:   Optional[int]													=					kwargs.get("additional_special_tokens"				,       []					)
								kwargs["additional_special_tokens"] += [
								    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
								]

								super().__init__(
								    src_lang=SCREAMING_SNAKE_CASE				,       tgt_lang=SCREAMING_SNAKE_CASE				,       eos_token=SCREAMING_SNAKE_CASE				,       unk_token=SCREAMING_SNAKE_CASE				,       sep_token=SCREAMING_SNAKE_CASE				,       cls_token=SCREAMING_SNAKE_CASE				,       pad_token=SCREAMING_SNAKE_CASE				,       mask_token=SCREAMING_SNAKE_CASE				,       sp_model_kwargs=self.sp_model_kwargs				,       **SCREAMING_SNAKE_CASE				,       )

								lowercase__					:   Tuple													=					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
								self.sp_model.Load(str(SCREAMING_SNAKE_CASE					)					)
								lowercase__					:   Tuple													=					vocab_file

								# Original fairseq vocab and spm vocab must be "aligned":
								# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
								# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
								# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
								# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

								# Mimic fairseq token-to-id alignment for the first 4 token
								lowercase__					:   Optional[int]													=					{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

								# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
								lowercase__					:   List[Any]													=					1

								lowercase__					:   Tuple													=					len(self.sp_model					)
								lowercase__					:   str													=					{
								    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(SCREAMING_SNAKE_CASE					)
								}
								lowercase__					:   List[Any]													=					{v: k for k, v in self.lang_code_to_id.items()}
								lowercase__					:   int													=					len(self.sp_model					) + len(self.lang_code_to_id					) + self.fairseq_offset

								self.fairseq_tokens_to_ids.update(self.lang_code_to_id					)
								lowercase__					:   str													=					{v: k for k, v in self.fairseq_tokens_to_ids.items()}

								lowercase__					:   Optional[int]													=					src_lang if src_lang is not None else "en_XX"
								lowercase__					:   Optional[int]													=					self.lang_code_to_id[self._src_lang]
								lowercase__					:   Optional[Any]													=					tgt_lang
								self.set_src_lang_special_tokens(self._src_lang					)







					@property
					def 			snake_case					(							self :     int					):
								return len(self.sp_model					) + len(self.lang_code_to_id					) + self.fairseq_offset + 1  # Plus 1 for the mask token







					@property
					def 			snake_case					(							self :     Tuple					):
								return self._src_lang







					@src_lang.setter
					def 			snake_case					(							self :     List[Any]				,       SCREAMING_SNAKE_CASE :     str					):
								lowercase__					:   int													=					new_src_lang
								self.set_src_lang_special_tokens(self._src_lang					)







					def __getstate__(							self :     int					):
								lowercase__					:   Tuple													=					self.__dict__.copy()
								lowercase__					:   List[Any]													=					None
								return state







					def __setstate__(							self :     str				,       SCREAMING_SNAKE_CASE :     Dict					):
								lowercase__					:   Optional[Any]													=					d

								# for backward compatibility
								if not hasattr(self				,       "sp_model_kwargs"					):
											lowercase__					:   Tuple													=					{}

								lowercase__					:   Dict													=					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
								self.sp_model.Load(self.vocab_file					)







					def 			snake_case					(							self :     Dict					):
								lowercase__					:   Optional[int]													=					{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE					): i for i in range(self.vocab_size					)}
								vocab.update(self.added_tokens_encoder					)
								return vocab







					def 			snake_case					(							self :     List[Any]				,       SCREAMING_SNAKE_CASE :     str					):
								return self.sp_model.encode(SCREAMING_SNAKE_CASE				,       out_type=SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     Tuple				,       SCREAMING_SNAKE_CASE :     str					):
								if token in self.fairseq_tokens_to_ids:
											return self.fairseq_tokens_to_ids[token]
								lowercase__					:   str													=					self.sp_model.PieceToId(SCREAMING_SNAKE_CASE					)

								# Need to return unknown token if the SP model returned 0
								return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







					def 			snake_case					(							self :     Optional[Any]				,       SCREAMING_SNAKE_CASE :     int					):
								if index in self.fairseq_ids_to_tokens:
											return self.fairseq_ids_to_tokens[index]
								return self.sp_model.IdToPiece(index - self.fairseq_offset					)







					def 			snake_case					(							self :     Dict				,       SCREAMING_SNAKE_CASE :     Optional[Any]					):
								lowercase__					:   int													=					[]
								lowercase__					:   str													=					""
								lowercase__					:   str													=					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(SCREAMING_SNAKE_CASE					) + token
														lowercase__					:   Optional[Any]													=					True
														lowercase__					:   Optional[int]													=					[]
											else:
														current_sub_tokens.append(SCREAMING_SNAKE_CASE					)
														lowercase__					:   Tuple													=					False
								out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE					)
								return out_string.strip()







					def 			snake_case					(							self :     List[str]				,       SCREAMING_SNAKE_CASE :     str				,       SCREAMING_SNAKE_CASE :     Optional[str] = None					):
								if not os.path.isdir(SCREAMING_SNAKE_CASE					):
											logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""					)
											return
								lowercase__					:   Union[str, Any]													=					os.path.join(
								    SCREAMING_SNAKE_CASE				,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)

								if os.path.abspath(self.vocab_file					) != os.path.abspath(SCREAMING_SNAKE_CASE					) and os.path.isfile(self.vocab_file					):
											copyfile(self.vocab_file				,       SCREAMING_SNAKE_CASE					)
								elif not os.path.isfile(self.vocab_file					):
											with open(SCREAMING_SNAKE_CASE				,       "wb"					) as fi:
														lowercase__					:   int													=					self.sp_model.serialized_model_proto()
														fi.write(SCREAMING_SNAKE_CASE					)

								return (out_vocab_file,)







					def 			snake_case					(							self :     Optional[int]				,       SCREAMING_SNAKE_CASE :     List[int]				,       SCREAMING_SNAKE_CASE :     Optional[List[int]] = None				,       SCREAMING_SNAKE_CASE :     bool = False					):

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

								lowercase__					:   Any													=					[1] * len(self.prefix_tokens					)
								lowercase__					:   Optional[Any]													=					[1] * len(self.suffix_tokens					)
								if token_ids_a is None:
											return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE					)) + suffix_ones
								return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE					)) + ([0] * len(SCREAMING_SNAKE_CASE					)) + suffix_ones







					def 			snake_case					(							self :     List[Any]				,       SCREAMING_SNAKE_CASE :     List[int]				,       SCREAMING_SNAKE_CASE :     Optional[List[int]] = None					):
								if token_ids_a is None:
											return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







					def 			snake_case					(							self :     Dict				,       SCREAMING_SNAKE_CASE :     Union[str, Any]				,       SCREAMING_SNAKE_CASE :     str				,       SCREAMING_SNAKE_CASE :     Optional[str]				,       SCREAMING_SNAKE_CASE :     Optional[str]				,       **SCREAMING_SNAKE_CASE :     Any					):
								if src_lang is None or tgt_lang is None:
											raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"					)
								lowercase__					:   int													=					src_lang
								lowercase__					:   Optional[Any]													=					self(SCREAMING_SNAKE_CASE				,       add_special_tokens=SCREAMING_SNAKE_CASE				,       return_tensors=SCREAMING_SNAKE_CASE				,       **SCREAMING_SNAKE_CASE					)
								lowercase__					:   Dict													=					self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE					)
								lowercase__					:   Dict													=					tgt_lang_id
								return inputs







					def 			snake_case					(							self :     Union[str, Any]				,       SCREAMING_SNAKE_CASE :     List[str]				,       SCREAMING_SNAKE_CASE :     str = "en_XX"				,       SCREAMING_SNAKE_CASE :     Optional[List[str]] = None				,       SCREAMING_SNAKE_CASE :     str = "ro_RO"				,       **SCREAMING_SNAKE_CASE :     Optional[Any]				,       ):
								lowercase__					:   Optional[Any]													=					src_lang
								lowercase__					:   int													=					tgt_lang
								return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE				,       SCREAMING_SNAKE_CASE				,       **SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     Any					):
								return self.set_src_lang_special_tokens(self.src_lang					)







					def 			snake_case					(							self :     str					):
								return self.set_tgt_lang_special_tokens(self.tgt_lang					)







					def 			snake_case					(							self :     Dict				,       SCREAMING_SNAKE_CASE :     str					):
								lowercase__					:   str													=					self.lang_code_to_id[src_lang]
								lowercase__					:   Any													=					[self.cur_lang_code_id]
								lowercase__					:   Optional[Any]													=					[self.eos_token_id]







					def 			snake_case					(							self :     Dict				,       SCREAMING_SNAKE_CASE :     str					):
								lowercase__					:   Optional[Any]													=					self.lang_code_to_id[tgt_lang]
								lowercase__					:   Union[str, Any]													=					[self.cur_lang_code_id]
								lowercase__					:   Any													=					[self.eos_token_id]









from collections import Counter
from timeit import timeit


def  __lowerCamelCase (       lowerCamelCase__ = ""					,			):

				"""simple docstring"""


				return sum(c % 2 for c in Counter(input_str.replace(" "					,			""						).lower()						).values()						) < 2


def  __lowerCamelCase (       lowerCamelCase__ = ""						):

				"""simple docstring"""


				if len(lowerCamelCase__						) == 0:
								return True
				lowercase__					:   str													=					input_str.replace(" "					,			""						).lower()
				# character_freq_dict: Stores the frequency of every character in the input string
				lowercase__					:   dict[str, int]													=					{}

				for character in lower_case_input_str:
								lowercase__					:   List[Any]													=					character_freq_dict.get(lowerCamelCase__					,			0						) + 1
				lowercase__					:   List[Any]													=					0

				for character_count in character_freq_dict.values():
								if character_count % 2:
												odd_char += 1
				if odd_char > 1:
								return False
				return True


def  __lowerCamelCase (       lowerCamelCase__ = ""						):

				"""simple docstring"""


				print("\nFor string = "					,			lowerCamelCase__					,			":"						)
				print(
				    "> can_string_be_rearranged_as_palindrome_counter()"					,			"\tans ="					,			can_string_be_rearranged_as_palindrome_counter(lowerCamelCase__						)					,			"\ttime ="					,			timeit(
				        "z.can_string_be_rearranged_as_palindrome_counter(z.check_str)"					,			setup="import __main__ as z"					,			)					,			"seconds"					,			)
				print(
				    "> can_string_be_rearranged_as_palindrome()"					,			"\tans ="					,			can_string_be_rearranged_as_palindrome(lowerCamelCase__						)					,			"\ttime ="					,			timeit(
				        "z.can_string_be_rearranged_as_palindrome(z.check_str)"					,			setup="import __main__ as z"					,			)					,			"seconds"					,			)


if __name__ == "__main__":
				lowerCAmelCase__					  =  input(
				    '''Enter string to determine if it can be rearranged as a palindrome or not: '''
				).strip()
				benchmark(check_str)
				lowerCAmelCase__					  =  can_string_be_rearranged_as_palindrome_counter(check_str)
				print(f'''{check_str} can {"" if status else "not "}be rearranged as a palindrome''')




