



'''simple docstring'''






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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
						from .tokenization_mbart import MBartTokenizer
else:
						UpperCamelCase__:   Union[str, Any]								=			None


UpperCamelCase__:   List[Any]								=			logging.get_logger(__name__)


UpperCamelCase__:   Dict								=			{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

UpperCamelCase__:   int								=			{
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

UpperCamelCase__:   List[str]								=			{
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
UpperCamelCase__:   Optional[Any]								=			["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"]

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	lowerCamelCase__			 =       VOCAB_FILES_NAMES
	lowerCamelCase__			 =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCamelCase__			 =       PRETRAINED_VOCAB_FILES_MAP
	lowerCamelCase__			 =       ["""input_ids""", """attention_mask"""]
	lowerCamelCase__			 =       MBartTokenizer

	lowerCamelCase__			 =       []
	lowerCamelCase__			 =       []







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

								super().__init__(
								    vocab_file=__snake_case		,			tokenizer_file=__snake_case		,			bos_token=__snake_case		,			eos_token=__snake_case		,			sep_token=__snake_case		,			cls_token=__snake_case		,			unk_token=__snake_case		,			pad_token=__snake_case		,			mask_token=__snake_case		,			src_lang=__snake_case		,			tgt_lang=__snake_case		,			additional_special_tokens=__snake_case		,			**__snake_case		,			)

								UpperCAmelCase :       Tuple 							=		vocab_file
								UpperCAmelCase :       Union[str, Any] 							=		False if not self.vocab_file else True

								UpperCAmelCase :       Dict 							=		FAIRSEQ_LANGUAGE_CODES.copy()

								if additional_special_tokens is not None:
															# Only add those special tokens if they are not already there.
															_additional_special_tokens.extend(
															    [t for t in additional_special_tokens if t not in _additional_special_tokens]		)

								self.add_special_tokens({'''additional_special_tokens''': _additional_special_tokens}		)
								UpperCAmelCase :       int 							=		{
								    lang_code: self.convert_tokens_to_ids(__snake_case		) for lang_code in FAIRSEQ_LANGUAGE_CODES
								}

								UpperCAmelCase :       Dict 							=		src_lang if src_lang is not None else '''en_XX'''
								UpperCAmelCase :       Optional[Any] 							=		self.convert_tokens_to_ids(self._src_lang		)
								UpperCAmelCase :       Tuple 							=		tgt_lang
								self.set_src_lang_special_tokens(self._src_lang		)







	@property
	def      A	(						self			:     Tuple		)			->		str:
								return self._src_lang







	@src_lang.setter
	def      A	(						self			:     List[Any]		,			__snake_case			:     str		)			->		None:
								UpperCAmelCase :       Optional[Any] 							=		new_src_lang
								self.set_src_lang_special_tokens(self._src_lang		)







	def      A	(						self			:     Union[str, Any]		,			__snake_case			:     List[int]		,			__snake_case			:     Optional[List[int]] = None		)			->		List[int]:
								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      A	(						self			:     Optional[int]		,			__snake_case			:     List[int]		,			__snake_case			:     Optional[List[int]] = None		)			->		List[int]:
								UpperCAmelCase :       Union[str, Any] 							=		[self.sep_token_id]
								UpperCAmelCase :       Tuple 							=		[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]







	def      A	(						self			:     Tuple		,			__snake_case			:     Any		,			__snake_case			:     str		,			__snake_case			:     Optional[str]		,			__snake_case			:     Optional[str]		,			**__snake_case			:     Any		)			->		Tuple:
								if src_lang is None or tgt_lang is None:
															raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''		)
								UpperCAmelCase :       List[Any] 							=		src_lang
								UpperCAmelCase :       Union[str, Any] 							=		self(__snake_case		,			add_special_tokens=__snake_case		,			return_tensors=__snake_case		,			**__snake_case		)
								UpperCAmelCase :       str 							=		self.convert_tokens_to_ids(__snake_case		)
								UpperCAmelCase :       Union[str, Any] 							=		tgt_lang_id
								return inputs







	def      A	(						self			:     str		,			__snake_case			:     List[str]		,			__snake_case			:     str = "en_XX"		,			__snake_case			:     Optional[List[str]] = None		,			__snake_case			:     str = "ro_RO"		,			**__snake_case			:     List[Any]		,			)			->		BatchEncoding:
								UpperCAmelCase :       Dict 							=		src_lang
								UpperCAmelCase :       List[str] 							=		tgt_lang
								return super().prepare_seqaseq_batch(__snake_case		,			__snake_case		,			**__snake_case		)







	def      A	(						self			:     Any		)			->		str:
								return self.set_src_lang_special_tokens(self.src_lang		)







	def      A	(						self			:     Optional[int]		)			->		Optional[int]:
								return self.set_tgt_lang_special_tokens(self.tgt_lang		)







	def      A	(						self			:     Any		,			__snake_case			:     str		)			->		None:
								UpperCAmelCase :       Optional[int] 							=		self.convert_tokens_to_ids(__snake_case		)
								UpperCAmelCase :       Dict 							=		[]
								UpperCAmelCase :       Optional[int] 							=		[self.eos_token_id, self.cur_lang_code]

								UpperCAmelCase :       Dict 							=		self.convert_ids_to_tokens(self.prefix_tokens		)
								UpperCAmelCase :       str 							=		self.convert_ids_to_tokens(self.suffix_tokens		)

								UpperCAmelCase :       Optional[int] 							=		processors.TemplateProcessing(
								    single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str		,			pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str		,			special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str		,			self.prefix_tokens + self.suffix_tokens		)		)		,			)







	def      A	(						self			:     Dict		,			__snake_case			:     str		)			->		None:
								UpperCAmelCase :       Optional[Any] 							=		self.convert_tokens_to_ids(__snake_case		)
								UpperCAmelCase :       Dict 							=		[]
								UpperCAmelCase :       Optional[Any] 							=		[self.eos_token_id, self.cur_lang_code]

								UpperCAmelCase :       Tuple 							=		self.convert_ids_to_tokens(self.prefix_tokens		)
								UpperCAmelCase :       Any 							=		self.convert_ids_to_tokens(self.suffix_tokens		)

								UpperCAmelCase :       Tuple 							=		processors.TemplateProcessing(
								    single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str		,			pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str		,			special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str		,			self.prefix_tokens + self.suffix_tokens		)		)		,			)







	def      A	(						self			:     Any		,			__snake_case			:     str		,			__snake_case			:     Optional[str] = None		)			->		Tuple[str]:
								if not self.can_save_slow_tokenizer:
															raise ValueError(
															    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
															    '''tokenizer.'''		)

								if not os.path.isdir(__snake_case		):
															logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""		)
															return
								UpperCAmelCase :       List[str] 							=		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		):
															copyfile(self.vocab_file		,			__snake_case		)

								return (out_vocab_file,)










'''simple docstring'''






from math import isclose, sqrt


def  snake_case_     (					_lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float  )      ->   tuple[float, float, float]:
							UpperCAmelCase :       Optional[int] 							=		point_y / 4 / point_x
							UpperCAmelCase :       str 							=		2 * normal_gradient / (1 + normal_gradient * normal_gradient)
							UpperCAmelCase :       Any 							=		(1 - normal_gradient * normal_gradient) / (
							    1 + normal_gradient * normal_gradient
							)
							UpperCAmelCase :       Union[str, Any] 							=		(sa - ca * incoming_gradient) / (ca + sa * incoming_gradient)

							# to find the next point, solve the simultaeneous equations:
							# y^2 + 4x^2 = 100
							# y - b = m * (x - a)
							# ==> A x^2 + B x + C = 0
							UpperCAmelCase :       Union[str, Any] 							=		outgoing_gradient**2 + 4
							UpperCAmelCase :       Dict 							=		2 * outgoing_gradient * (point_y - outgoing_gradient * point_x)
							UpperCAmelCase :       List[Any] 							=		(point_y - outgoing_gradient * point_x) ** 2 - 100

							UpperCAmelCase :       List[str] 							=		(
							    -linear_term - sqrt(linear_term**2 - 4 * quadratic_term * constant_term  )
							) / (2 * quadratic_term)
							UpperCAmelCase :       Optional[int] 							=		(
							    -linear_term + sqrt(linear_term**2 - 4 * quadratic_term * constant_term  )
							) / (2 * quadratic_term)

							# two solutions, one of which is our input point
							UpperCAmelCase :       Optional[Any] 							=		x_minus if isclose(_lowerCAmelCase   ,      _lowerCAmelCase  ) else x_plus
							UpperCAmelCase :       Union[str, Any] 							=		point_y + outgoing_gradient * (next_x - point_x)

							return next_x, next_y, outgoing_gradient


def  snake_case_     (					_lowerCAmelCase  :						float = 1.4   ,      _lowerCAmelCase  :						float = -9.6  )      ->   int:
							UpperCAmelCase :       int 							=		0
							UpperCAmelCase :       float 							=		first_x_coord
							UpperCAmelCase :       float 							=		first_y_coord
							UpperCAmelCase :       float 							=		(1_0.1 - point_y) / (0.0 - point_x)

							while not (-0.0_1 <= point_x <= 0.0_1 and point_y > 0):
														UpperCAmelCase							,		UpperCAmelCase							,		UpperCAmelCase :       str 							=		next_point(_lowerCAmelCase   ,      _lowerCAmelCase   ,      _lowerCAmelCase  )
														num_reflections += 1

							return num_reflections


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





