



"""simple docstring"""

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

import sentencepiece

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


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

lowercase__    :  List[str]							    =	'''▁'''

lowercase__    :  Optional[int]							    =	{
    '''vocab_file''': '''vocab.json''',
    '''spm_file''': '''sentencepiece.bpe.model''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowercase__    :  Optional[Any]							    =	{
    '''vocab_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json''',
    },
    '''spm_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_config_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json''',
    },
}

lowercase__    :  str							    =	{
    '''facebook/m2m100_418M''': 10_24,
}

# fmt: off
lowercase__    :  Union[str, Any]							    =	{
    '''m2m100''': ['''af''', '''am''', '''ar''', '''ast''', '''az''', '''ba''', '''be''', '''bg''', '''bn''', '''br''', '''bs''', '''ca''', '''ceb''', '''cs''', '''cy''', '''da''', '''de''', '''el''', '''en''', '''es''', '''et''', '''fa''', '''ff''', '''fi''', '''fr''', '''fy''', '''ga''', '''gd''', '''gl''', '''gu''', '''ha''', '''he''', '''hi''', '''hr''', '''ht''', '''hu''', '''hy''', '''id''', '''ig''', '''ilo''', '''is''', '''it''', '''ja''', '''jv''', '''ka''', '''kk''', '''km''', '''kn''', '''ko''', '''lb''', '''lg''', '''ln''', '''lo''', '''lt''', '''lv''', '''mg''', '''mk''', '''ml''', '''mn''', '''mr''', '''ms''', '''my''', '''ne''', '''nl''', '''no''', '''ns''', '''oc''', '''or''', '''pa''', '''pl''', '''ps''', '''pt''', '''ro''', '''ru''', '''sd''', '''si''', '''sk''', '''sl''', '''so''', '''sq''', '''sr''', '''ss''', '''su''', '''sv''', '''sw''', '''ta''', '''th''', '''tl''', '''tn''', '''tr''', '''uk''', '''ur''', '''uz''', '''vi''', '''wo''', '''xh''', '''yi''', '''yo''', '''zh''', '''zu'''],
    '''wmt21''': ['''en''', '''ha''', '''is''', '''ja''', '''cs''', '''ru''', '''zh''', '''de''']
}




class        _UpperCAmelCase       (			lowerCAmelCase__):
 _lowerCAmelCase   :			Optional[Any]							=		VOCAB_FILES_NAMES
 _lowerCAmelCase   :			int							=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCAmelCase   :			List[str]							=		PRETRAINED_VOCAB_FILES_MAP
 _lowerCAmelCase   :			Dict							=		["""input_ids""", """attention_mask"""]

 _lowerCAmelCase   :			List[int]							=		[]
 _lowerCAmelCase   :			List[int]							=		[]

 def __init__(     self		:       List[str]  ,     lowercase_		:       List[str]  ,     lowercase_		:       Dict  ,     lowercase_		:       List[str]=None  ,     lowercase_		:       Optional[Any]=None  ,     lowercase_		:       List[Any]="<s>"  ,     lowercase_		:       Optional[int]="</s>"  ,     lowercase_		:       List[Any]="</s>"  ,     lowercase_		:       Any="<pad>"  ,     lowercase_		:       Union[str, Any]="<unk>"  ,     lowercase_		:       Dict="m2m100"  ,     lowercase_		:       Optional[Dict[str, Any]] = None  ,     lowercase_		:       int=8  ,     **lowercase_		:       int  ,     ):
     snake_case_ :     Union[str, Any]				=	{} if sp_model_kwargs is None else sp_model_kwargs

     snake_case_ :     Union[str, Any]				=	language_codes
     snake_case_ :     int				=	FAIRSEQ_LANGUAGE_CODES[language_codes]
     snake_case_ :     Optional[Any]				=	{lang_code: f"__{lang_code}__" for lang_code in fairseq_language_code}

     snake_case_ :     Optional[int]				=	kwargs.get('''additional_special_tokens'''  ,     []				)
     kwargs["additional_special_tokens"] += [
         self.get_lang_token(lowercase_				)
         for lang_code in fairseq_language_code
         if self.get_lang_token(lowercase_				) not in kwargs["additional_special_tokens"]
     ]

     super().__init__(
         src_lang=lowercase_  ,     tgt_lang=lowercase_  ,     bos_token=lowercase_  ,     eos_token=lowercase_  ,     sep_token=lowercase_  ,     unk_token=lowercase_  ,     pad_token=lowercase_  ,     language_codes=lowercase_  ,     sp_model_kwargs=self.sp_model_kwargs  ,     num_madeup_words=lowercase_  ,     **lowercase_  ,     )

     snake_case_ :     str				=	vocab_file
     snake_case_ :     Optional[int]				=	load_json(lowercase_				)
     snake_case_ :     str				=	{v: k for k, v in self.encoder.items()}
     snake_case_ :     Dict				=	spm_file
     snake_case_ :     Dict				=	load_spm(lowercase_  ,     self.sp_model_kwargs				)

     snake_case_ :     Any				=	len(self.encoder				)

     snake_case_ :     List[str]				=	{
         self.get_lang_token(lowercase_				): self.encoder_size + i for i, lang_code in enumerate(lowercase_				)
     }
     snake_case_ :     Tuple				=	{lang_code: self.encoder_size + i for i, lang_code in enumerate(lowercase_				)}
     snake_case_ :     Optional[int]				=	{v: k for k, v in self.lang_token_to_id.items()}

     snake_case_ :     List[Any]				=	src_lang if src_lang is not None else '''en'''
     snake_case_ :     Dict				=	tgt_lang
     snake_case_ :     Any				=	self.get_lang_id(self._src_lang				)
     self.set_src_lang_special_tokens(self._src_lang				)

     snake_case_ :     Tuple				=	num_madeup_words

 @property
 def 						_snake_case					(     self		:       List[str]				):
     return len(self.encoder				) + len(self.lang_token_to_id				)

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

 @src_lang.setter
 def 						_snake_case					(     self		:       Any  ,     lowercase_		:       str				):
     snake_case_ :     Dict				=	new_src_lang
     self.set_src_lang_special_tokens(self._src_lang				)

 def 						_snake_case					(     self		:       List[str]  ,     lowercase_		:       str				):
     return self.sp_model.encode(lowercase_  ,     out_type=lowercase_				)

 def 						_snake_case					(     self		:       str  ,     lowercase_		:       str				):
     if token in self.lang_token_to_id:
         return self.lang_token_to_id[token]
     return self.encoder.get(lowercase_  ,     self.encoder[self.unk_token]				)

 def 						_snake_case					(     self		:       List[Any]  ,     lowercase_		:       int				):
     if index in self.id_to_lang_token:
         return self.id_to_lang_token[index]
     return self.decoder.get(lowercase_  ,     self.unk_token				)

 def 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       Dict				):
     snake_case_ :     Dict				=	[]
     snake_case_ :     Optional[Any]				=	''''''
     for token in tokens:
         # make sure that special tokens are not decoded using sentencepiece model
         if token in self.all_special_tokens:
             out_string += self.sp_model.decode(lowercase_				) + token
             snake_case_ :     Dict				=	[]
         else:
             current_sub_tokens.append(lowercase_				)
     out_string += self.sp_model.decode(lowercase_				)
     return out_string.strip()

 def 						_snake_case					(     self		:       int  ,     lowercase_		:       List[int]  ,     lowercase_		:       Optional[List[int]] = None  ,     lowercase_		:       bool = False				):

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

     snake_case_ :     List[str]				=	[1] * len(self.prefix_tokens				)
     snake_case_ :     str				=	[1] * len(self.suffix_tokens				)
     if token_ids_a is None:
         return prefix_ones + ([0] * len(lowercase_				)) + suffix_ones
     return prefix_ones + ([0] * len(lowercase_				)) + ([0] * len(lowercase_				)) + suffix_ones

 def 						_snake_case					(     self		:       List[Any]  ,     lowercase_		:       List[int]  ,     lowercase_		:       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		:       Tuple				):
     snake_case_ :     Optional[Any]				=	{self.convert_ids_to_tokens(lowercase_				): i for i in range(self.vocab_size				)}
     vocab.update(self.added_tokens_encoder				)
     return vocab

 def __getstate__(     self		:       Union[str, Any]				):
     snake_case_ :     Optional[Any]				=	self.__dict__.copy()
     snake_case_ :     str				=	None
     return state

 def __setstate__(     self		:       Optional[Any]  ,     lowercase_		:       Dict				):
     snake_case_ :     str				=	d

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

     snake_case_ :     Any				=	load_spm(self.spm_file  ,     self.sp_model_kwargs				)

 def 						_snake_case					(     self		:       List[Any]  ,     lowercase_		:       str  ,     lowercase_		:       Optional[str] = None				):
     snake_case_ :     int				=	Path(lowercase_				)
     if not save_dir.is_dir():
         raise OSError(f"{save_directory} should be a directory"				)
     snake_case_ :     List[str]				=	save_dir / (
         (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''vocab_file''']
     )
     snake_case_ :     Any				=	save_dir / (
         (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''spm_file''']
     )

     save_json(self.encoder  ,     lowercase_				)

     if os.path.abspath(self.spm_file				) != os.path.abspath(lowercase_				) and os.path.isfile(self.spm_file				):
         copyfile(self.spm_file  ,     lowercase_				)
     elif not os.path.isfile(self.spm_file				):
         with open(lowercase_  ,     '''wb'''				) as fi:
             snake_case_ :     List[str]				=	self.sp_model.serialized_model_proto()
             fi.write(lowercase_				)

     return (str(lowercase_				), str(lowercase_				))

 def 						_snake_case					(     self		:       Tuple  ,     lowercase_		:       List[str]  ,     lowercase_		:       str = "en"  ,     lowercase_		:       Optional[List[str]] = None  ,     lowercase_		:       str = "ro"  ,     **lowercase_		:       Tuple  ,     ):
     snake_case_ :     int				=	src_lang
     snake_case_ :     Tuple				=	tgt_lang
     self.set_src_lang_special_tokens(self.src_lang				)
     return super().prepare_seqaseq_batch(lowercase_  ,     lowercase_  ,     **lowercase_				)

 def 						_snake_case					(     self		:       Any  ,     lowercase_		:       Any  ,     lowercase_		:       Optional[str]  ,     lowercase_		:       Optional[str]  ,     **lowercase_		:       Optional[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'''				)
     snake_case_ :     str				=	src_lang
     snake_case_ :     Union[str, Any]				=	self(lowercase_  ,     add_special_tokens=lowercase_  ,     **lowercase_				)
     snake_case_ :     str				=	self.get_lang_id(lowercase_				)
     snake_case_ :     Optional[Any]				=	tgt_lang_id
     return inputs

 def 						_snake_case					(     self		:       Tuple				):
     self.set_src_lang_special_tokens(self.src_lang				)

 def 						_snake_case					(     self		:       Dict				):
     self.set_tgt_lang_special_tokens(self.tgt_lang				)

 def 						_snake_case					(     self		:       Optional[int]  ,     lowercase_		:       str				):
     snake_case_ :     int				=	self.get_lang_token(lowercase_				)
     snake_case_ :     int				=	self.lang_token_to_id[lang_token]
     snake_case_ :     Dict				=	[self.cur_lang_id]
     snake_case_ :     List[Any]				=	[self.eos_token_id]

 def 						_snake_case					(     self		:       Tuple  ,     lowercase_		:       str				):
     snake_case_ :     str				=	self.get_lang_token(lowercase_				)
     snake_case_ :     Optional[Any]				=	self.lang_token_to_id[lang_token]
     snake_case_ :     str				=	[self.cur_lang_id]
     snake_case_ :     int				=	[self.eos_token_id]

 def 						_snake_case					(     self		:       str  ,     lowercase_		:       str				):
     return self.lang_code_to_token[lang]






 def 						_snake_case					(     self		:       int  ,     lowercase_		:       str				):
     snake_case_ :     Union[str, Any]				=	self.get_lang_token(lowercase_				)
     return self.lang_token_to_id[lang_token]





def __lowercase			(							_a		,			_a    ):
    snake_case_ :     Union[str, Any]				=	sentencepiece.SentencePieceProcessor(**_a    )
    spm.Load(str(_a    )    )
    return spm




def __lowercase			(							_a    ):
    with open(_a		,			'''r'''    ) as f:
        return json.load(_a    )






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










"""simple docstring"""

import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt




class        _UpperCAmelCase       :

 def __init__(     self		:       List[Any]				):
     snake_case_ :     List[str]				=	''''''
     snake_case_ :     Tuple				=	''''''
     snake_case_ :     int				=	[]
     snake_case_ :     Optional[int]				=	0
     snake_case_ :     Optional[Any]				=	256
     snake_case_ :     Tuple				=	0
     snake_case_ :     Tuple				=	0
     snake_case_ :     Optional[Any]				=	0
     snake_case_ :     Any				=	0

 def 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       List[Any]				):
     snake_case_ :     List[Any]				=	cva.imread(lowercase_  ,     0				)
     snake_case_ :     Tuple				=	copy.deepcopy(self.img				)
     snake_case_,	snake_case_,	snake_case_ :     List[Any]				=	plt.hist(self.img.ravel()  ,     256  ,     [0, 256]  ,     label='''x'''				)
     snake_case_ :     str				=	np.sum(lowercase_				)
     for i in range(len(lowercase_				)				):
         snake_case_ :     Optional[Any]				=	x[i] / self.k
         self.sk += prk
         snake_case_ :     Any				=	(self.L - 1) * self.sk
         if self.rem != 0:
             snake_case_ :     Dict				=	int(last % last				)
         snake_case_ :     Union[str, Any]				=	int(last + 1 if self.rem >= 0.5 else last				)
         self.last_list.append(lowercase_				)
         snake_case_ :     int				=	int(np.ma.count(self.img				) / self.img[1].size				)
         snake_case_ :     Tuple				=	self.img[1].size
     for i in range(self.number_of_cols				):
         for j in range(self.number_of_rows				):
             snake_case_ :     Union[str, Any]				=	self.img[j][i]
             if num != self.last_list[num]:
                 snake_case_ :     List[str]				=	self.last_list[num]
     cva.imwrite('''output_data/output.jpg'''  ,     self.img				)

 def 						_snake_case					(     self		:       Tuple				):
     plt.hist(self.img.ravel()  ,     256  ,     [0, 256]				)






 def 						_snake_case					(     self		:       int				):
     cva.imshow('''Output-Image'''  ,     self.img				)
     cva.imshow('''Input-Image'''  ,     self.original_image				)
     cva.waitKey(5000				)
     cva.destroyAllWindows()


if __name__ == "__main__":
     lowercase__    :  Any							    =	os.path.join(os.path.basename(__file__), '''image_data/input.jpg''')
     lowercase__    :  Any							    =	ConstantStretch()
     stretcher.stretch(file_path)
     stretcher.plot_histogram()
     stretcher.show_image()





