"""simple docstring"""




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    :							Dict													=						logging.get_logger(__name__)

__lowerCAmelCase    :							Union[str, Any]													=						"▁"

__lowerCAmelCase    :							Dict													=						{"vocab_file": "sentencepiece.bpe.model"}

__lowerCAmelCase    :							Dict													=						{
    "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    :							Optional[int]													=						{
    "facebook/mbart-large-50-one-to-many-mmt": 10_24,
}

# fmt: off
__lowerCAmelCase    :							str													=						["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       a_      (     __UpperCamelCase			):
					UpperCamelCase_ :	Optional[Any]			=    VOCAB_FILES_NAMES
					UpperCamelCase_ :	Optional[int]			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					UpperCamelCase_ :	Dict			=    PRETRAINED_VOCAB_FILES_MAP
					UpperCamelCase_ :	Optional[int]			=    ["input_ids", "attention_mask"]

					UpperCamelCase_ :	List[int]			=    []
					UpperCamelCase_ :	List[int]			=    []




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

							lowerCAmelCase__        =   {} if sp_model_kwargs is None else sp_model_kwargs

							lowerCAmelCase__        =   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=snake_case__  ,						tgt_lang=snake_case__  ,						eos_token=snake_case__  ,						unk_token=snake_case__  ,						sep_token=snake_case__  ,						cls_token=snake_case__  ,						pad_token=snake_case__  ,						mask_token=snake_case__  ,						sp_model_kwargs=self.sp_model_kwargs  ,						**snake_case__  ,						)

							lowerCAmelCase__        =   spm.SentencePieceProcessor(**self.sp_model_kwargs     )
							self.sp_model.Load(str(snake_case__     )     )
							lowerCAmelCase__        =   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
							lowerCAmelCase__        =   {"""<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
							lowerCAmelCase__        =   1

							lowerCAmelCase__        =   len(self.sp_model     )
							lowerCAmelCase__        =   {
							    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(snake_case__     )
							}
							lowerCAmelCase__        =   {v: k for k, v in self.lang_code_to_id.items()}
							lowerCAmelCase__        =   len(self.sp_model     ) + len(self.lang_code_to_id     ) + self.fairseq_offset

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

							lowerCAmelCase__        =   src_lang if src_lang is not None else """en_XX"""
							lowerCAmelCase__        =   self.lang_code_to_id[self._src_lang]
							lowerCAmelCase__        =   tgt_lang
							self.set_src_lang_special_tokens(self._src_lang     )




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




					@property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]     ):
							return self._src_lang




					@src_lang.setter
					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]  ,						snake_case__						:     str     ):
							lowerCAmelCase__        =   new_src_lang
							self.set_src_lang_special_tokens(self._src_lang     )




					def __getstate__(	self						:     Optional[Any]     ):
							lowerCAmelCase__        =   self.__dict__.copy()
							lowerCAmelCase__        =   None
							return state




					def __setstate__(	self						:     Tuple  ,						snake_case__						:     Dict     ):
							lowerCAmelCase__        =   d

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

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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]     ):
							lowerCAmelCase__        =   {self.convert_ids_to_tokens(snake_case__     ): i for i in range(self.vocab_size     )}
							vocab.update(self.added_tokens_encoder     )
							return vocab




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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]  ,						snake_case__						:     str     ):
							if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
							lowerCAmelCase__        =   self.sp_model.PieceToId(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 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]  ,						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 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[Any]  ,						snake_case__						:     Optional[int]     ):
							lowerCAmelCase__        =   []
							lowerCAmelCase__        =   """"""
							lowerCAmelCase__        =   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(snake_case__     ) + token
											lowerCAmelCase__        =   True
											lowerCAmelCase__        =   []
									else:
											current_sub_tokens.append(snake_case__     )
											lowerCAmelCase__        =   False
							out_string += self.sp_model.decode(snake_case__     )
							return out_string.strip()




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

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

							return (out_vocab_file,)




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]  ,						snake_case__						:     List[int]  ,						snake_case__						:     Optional[List[int]] = None  ,						snake_case__						:     bool = False     ):

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

							lowerCAmelCase__        =   [1] * len(self.prefix_tokens     )
							lowerCAmelCase__        =   [1] * len(self.suffix_tokens     )
							if token_ids_a is None:
									return prefix_ones + ([0] * len(snake_case__     )) + suffix_ones
							return prefix_ones + ([0] * len(snake_case__     )) + ([0] * len(snake_case__     )) + suffix_ones




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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]  ,						snake_case__						:     List[str]  ,						snake_case__						:     str = "en_XX"  ,						snake_case__						:     Optional[List[str]] = None  ,						snake_case__						:     str = "ro_RO"  ,						**snake_case__						:     Tuple  ,						):
							lowerCAmelCase__        =   src_lang
							lowerCAmelCase__        =   tgt_lang
							return super().prepare_seqaseq_batch(snake_case__  ,						snake_case__  ,						**snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     int     ):
							return self.set_src_lang_special_tokens(self.src_lang     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]     ):
							return self.set_tgt_lang_special_tokens(self.tgt_lang     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]  ,						snake_case__						:     str     ):
							lowerCAmelCase__        =   self.lang_code_to_id[src_lang]
							lowerCAmelCase__        =   [self.cur_lang_code_id]
							lowerCAmelCase__        =   [self.eos_token_id]




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Dict  ,						snake_case__						:     str     ):
							lowerCAmelCase__        =   self.lang_code_to_id[tgt_lang]
							lowerCAmelCase__        =   [self.cur_lang_code_id]
							lowerCAmelCase__        =   [self.eos_token_id]





"""simple docstring"""




from math import pi, sqrt







def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		if num <= 0:
				raise ValueError("""math domain error"""     )
		if num > 1_71.5:
				raise OverflowError("""math range error"""     )
		elif num - int(lowerCamelCase__     ) not in (0, 0.5):
				raise NotImplementedError("""num must be an integer or a half-integer"""     )
		elif num == 0.5:
				return sqrt(lowerCamelCase__     )
		else:
				return 1.0 if num == 1 else (num - 1) * gamma(num - 1     )







def 							_UpperCAmelCase		(       ):





		"""simple docstring"""




		assert gamma(0.5     ) == sqrt(lowerCamelCase__     )
		assert gamma(1     ) == 1.0
		assert gamma(2     ) == 1.0


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

			testmod()
			__lowerCAmelCase    :							Dict													=						1.0
			while num:
						__lowerCAmelCase    :							Any													=						float(input("Gamma of: "))
						print(F"gamma({num}) = {gamma(num)}")
						print("\nEnter 0 to exit...")




