






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


__snake_case      :      Optional[Any]             =       logging.get_logger(__name__)

__snake_case      :      List[Any]             =       """▁"""

__snake_case      :      Optional[Any]             =       {"""vocab_file""": """sentencepiece.bpe.model"""}

__snake_case      :      Optional[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"""
        ),
    }
}

__snake_case      :      int             =       {
    """facebook/mbart-large-en-ro""": 10_24,
    """facebook/mbart-large-cc25""": 10_24,
}

# fmt: off
__snake_case      :      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   (				__lowercase):
						_SCREAMING_SNAKE_CASE		:    Any						=   VOCAB_FILES_NAMES
						_SCREAMING_SNAKE_CASE		:    Optional[Any]						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_SCREAMING_SNAKE_CASE		:    str						=   PRETRAINED_VOCAB_FILES_MAP
						_SCREAMING_SNAKE_CASE		:    Tuple						=   ['''input_ids''', '''attention_mask''']

						_SCREAMING_SNAKE_CASE		:    List[int]						=   []
						_SCREAMING_SNAKE_CASE		:    List[int]						=   []






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






												"""simple docstring"""
												# Mask token behave like a normal word, i.e. include the space before it
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else mask_token

												lowerCAmelCase__        =  {} 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       ,  tokenizer_file=_UpperCamelCase       ,  src_lang=_UpperCamelCase       ,  tgt_lang=_UpperCamelCase       ,  additional_special_tokens=_UpperCamelCase       ,  sp_model_kwargs=self.sp_model_kwargs       ,  **_UpperCamelCase       ,  )

												lowerCAmelCase__        =  spm.SentencePieceProcessor(**self.sp_model_kwargs				)
												self.sp_model.Load(str(_UpperCamelCase				)				)
												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(_UpperCamelCase				)
												}
												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__        =  list(self.lang_code_to_id.keys()				)

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

												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				)






						def __getstate__(		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.__dict__.copy()
												lowerCAmelCase__        =  None
												lowerCAmelCase__        =  self.sp_model.serialized_model_proto()
												return state






						def __setstate__(		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  d

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

												lowerCAmelCase__        =  spm.SentencePieceProcessor(**self.sp_model_kwargs				)
												self.sp_model.LoadFromSerializedProto(self.sp_model_proto				)






						@property
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												return len(self.sp_model				) + len(self.lang_code_to_id				) + self.fairseq_offset + 1  # Plus 1 for the mask token






						@property
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												return self._src_lang






						@src_lang.setter
						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  new_src_lang
												self.set_src_lang_special_tokens(self._src_lang				)






						def  UpperCamelCase__ (		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				)

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






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None				):






												"""simple docstring"""
												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  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None				):






												"""simple docstring"""
												lowerCAmelCase__        =  [self.sep_token_id]
												lowerCAmelCase__        =  [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  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase       ,  _UpperCamelCase       ,  _UpperCamelCase       ,  **_UpperCamelCase				):






												"""simple docstring"""
												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(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  return_tensors=_UpperCamelCase       ,  **_UpperCamelCase				)
												lowerCAmelCase__        =  self.convert_tokens_to_ids(_UpperCamelCase				)
												lowerCAmelCase__        =  tgt_lang_id
												return inputs






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  {self.convert_ids_to_tokens(_UpperCamelCase				): i for i in range(self.vocab_size				)}
												vocab.update(self.added_tokens_encoder				)
												return vocab






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												return self.sp_model.encode(_UpperCamelCase       ,  out_type=_UpperCamelCase				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												if token in self.fairseq_tokens_to_ids:
																		return self.fairseq_tokens_to_ids[token]
												lowerCAmelCase__        =  self.sp_model.PieceToId(_UpperCamelCase				)

												# 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  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												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  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  ''.join(_UpperCamelCase				).replace(_UpperCamelCase       ,  ' '				).strip()
												return out_string






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None				):






												"""simple docstring"""
												if not os.path.isdir(_UpperCamelCase				):
																		logger.error(F"Vocabulary path ({save_directory}) should be a directory"				)
																		return
												lowerCAmelCase__        =  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:
																								lowerCAmelCase__        =  self.sp_model.serialized_model_proto()
																								fi.write(_UpperCamelCase				)

												return (out_vocab_file,)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = "en_XX"       ,  _UpperCamelCase = None       ,  _UpperCamelCase = "ro_RO"       ,  **_UpperCamelCase       ,  ):






												"""simple docstring"""
												lowerCAmelCase__        =  src_lang
												lowerCAmelCase__        =  tgt_lang
												return super().prepare_seqaseq_batch(_UpperCamelCase       ,  _UpperCamelCase       ,  **_UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												return self.set_src_lang_special_tokens(self.src_lang				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												return self.set_tgt_lang_special_tokens(self.tgt_lang				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.lang_code_to_id[src_lang]
												lowerCAmelCase__        =  []
												lowerCAmelCase__        =  [self.eos_token_id, self.cur_lang_code]







						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.lang_code_to_id[lang]
												lowerCAmelCase__        =  []
												lowerCAmelCase__        =  [self.eos_token_id, self.cur_lang_code]













import colorsys

from PIL import Image  # type: ignore







def 		_UpperCamelCase				(      UpperCamelCase_    :   float      ,    UpperCamelCase_    :   float      ,    UpperCamelCase_    :   int						)					->				float:

						"""simple docstring"""



						lowerCAmelCase__        =  x
						lowerCAmelCase__        =  y
						for step in range(UpperCamelCase_						):  # noqa: B007
												lowerCAmelCase__        =  a * a - b * b + x
												lowerCAmelCase__        =  2 * a * b + y
												lowerCAmelCase__        =  a_new

												# divergence happens for all complex number with an absolute value
												# greater than 4
												if a * a + b * b > 4:
																		break
						return step / (max_step - 1)







def 		_UpperCamelCase				(      UpperCamelCase_    :   float						)					->				tuple:

						"""simple docstring"""



						if distance == 1:
												return (0, 0, 0)
						else:
												return (255, 255, 255)







def 		_UpperCamelCase				(      UpperCamelCase_    :   float						)					->				tuple:

						"""simple docstring"""



						if distance == 1:
												return (0, 0, 0)
						else:
												return tuple(round(i * 255						) for i in colorsys.hsv_to_rgb(UpperCamelCase_      ,    1      ,    1						)						)







def 		_UpperCamelCase				(      UpperCamelCase_    :   int = 800      ,    UpperCamelCase_    :   int = 600      ,    UpperCamelCase_    :   float = -0.6      ,    UpperCamelCase_    :   float = 0      ,    UpperCamelCase_    :   float = 3.2      ,    UpperCamelCase_    :   int = 50      ,    UpperCamelCase_    :   bool = True      ,    )					->				Image.Image:

						"""simple docstring"""



						lowerCAmelCase__        =  Image.new('RGB'      ,    (image_width, image_height)						)
						lowerCAmelCase__        =  img.load()

						# loop through the image-coordinates
						for image_x in range(UpperCamelCase_						):
												for image_y in range(UpperCamelCase_						):
																		# determine the figure-coordinates based on the image-coordinates
																		lowerCAmelCase__        =  figure_width / image_width * image_height
																		lowerCAmelCase__        =  figure_center_x + (image_x / image_width - 0.5) * figure_width
																		lowerCAmelCase__        =  figure_center_y + (image_y / image_height - 0.5) * figure_height

																		lowerCAmelCase__        =  get_distance(UpperCamelCase_      ,    UpperCamelCase_      ,    UpperCamelCase_						)

																		# color the corresponding pixel based on the selected coloring-function
																		if use_distance_color_coding:
																								lowerCAmelCase__        =  get_color_coded_rgb(UpperCamelCase_						)
																		else:
																								lowerCAmelCase__        =  get_black_and_white_rgb(UpperCamelCase_						)

						return img


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					# colored version, full figure
					__snake_case      :      str             =       get_image()

					# uncomment for colored version, different section, zoomed in
					# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
					# figure_width = 0.8)

					# uncomment for black and white version, full figure
					# img = get_image(use_distance_color_coding = False)

					# uncomment to save the image
					# img.save("mandelbrot.png")

					img.show()





