


'''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


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

lowerCAmelCase    :     Any					=						"""▁"""

lowerCAmelCase    :     List[Any]					=						{
    """vocab_file""": """vocab.json""",
    """spm_file""": """sentencepiece.bpe.model""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

lowerCAmelCase    :     Dict					=						{
    """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""",
    },
}

lowerCAmelCase    :     Dict					=						{
    """facebook/m2m100_418M""": 10_24,
}

# fmt: off
lowerCAmelCase    :     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__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






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

     __magic_name__    			=    []
     __magic_name__    			=    []







     def __init__( self      ,	snake_case__      ,	snake_case__      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__="<s>"      ,	snake_case__="</s>"      ,	snake_case__="</s>"      ,	snake_case__="<pad>"      ,	snake_case__="<unk>"      ,	snake_case__="m2m100"      ,	snake_case__ = None      ,	snake_case__=8      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							Any   			=       {} if sp_model_kwargs is None else sp_model_kwargs

            _lowerCAmelCase    :							str   			=       language_codes
            _lowerCAmelCase    :							Optional[Any]   			=       FAIRSEQ_LANGUAGE_CODES[language_codes]
            _lowerCAmelCase    :							int   			=       {lang_code: F'__{lang_code}__' for lang_code in fairseq_language_code}

            _lowerCAmelCase    :							Tuple   			=       kwargs.get('additional_special_tokens'      ,	[]   )
            kwargs["additional_special_tokens"] += [
                self.get_lang_token(snake_case__   )
                for lang_code in fairseq_language_code
                if self.get_lang_token(snake_case__   ) not in kwargs["additional_special_tokens"]
            ]

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

            _lowerCAmelCase    :							Optional[Any]   			=       vocab_file
            _lowerCAmelCase    :							Any   			=       load_json(snake_case__   )
            _lowerCAmelCase    :							Any   			=       {v: k for k, v in self.encoder.items()}
            _lowerCAmelCase    :							Any   			=       spm_file
            _lowerCAmelCase    :							int   			=       load_spm(snake_case__      ,	self.sp_model_kwargs   )

            _lowerCAmelCase    :							str   			=       len(self.encoder   )

            _lowerCAmelCase    :							Union[str, Any]   			=       {
                self.get_lang_token(snake_case__   ): self.encoder_size + i for i, lang_code in enumerate(snake_case__   )
            }
            _lowerCAmelCase    :							List[str]   			=       {lang_code: self.encoder_size + i for i, lang_code in enumerate(snake_case__   )}
            _lowerCAmelCase    :							str   			=       {v: k for k, v in self.lang_token_to_id.items()}

            _lowerCAmelCase    :							Any   			=       src_lang if src_lang is not None else 'en'
            _lowerCAmelCase    :							Union[str, Any]   			=       tgt_lang
            _lowerCAmelCase    :							Dict   			=       self.get_lang_id(self._src_lang   )
            self.set_src_lang_special_tokens(self._src_lang   )

            _lowerCAmelCase    :							List[Any]   			=       num_madeup_words







     @property
     def a	( self   ):

            '''simple docstring'''

            return len(self.encoder   ) + len(self.lang_token_to_id   )







     @property
     def a	( self   ):

            '''simple docstring'''

            return self._src_lang







     @src_lang.setter
     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							int   			=       new_src_lang
            self.set_src_lang_special_tokens(self._src_lang   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            return self.sp_model.encode(snake_case__      ,	out_type=snake_case__   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            if token in self.lang_token_to_id:
                   return self.lang_token_to_id[token]
            return self.encoder.get(snake_case__      ,	self.encoder[self.unk_token]   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            if index in self.id_to_lang_token:
                   return self.id_to_lang_token[index]
            return self.decoder.get(snake_case__      ,	self.unk_token   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[int]   			=       []
            _lowerCAmelCase    :							List[str]   			=       ''
            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(snake_case__   ) + token
                          _lowerCAmelCase    :							Tuple   			=       []
                   else:
                          current_sub_tokens.append(snake_case__   )
            out_string += self.sp_model.decode(snake_case__   )
            return out_string.strip()







     def a	( self      ,	snake_case__      ,	snake_case__ = None      ,	snake_case__ = False   ):

            '''simple docstring'''

            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    :							Union[str, Any]   			=       [1] * len(self.prefix_tokens   )
            _lowerCAmelCase    :							Optional[int]   			=       [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 a	( self      ,	snake_case__      ,	snake_case__ = 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 a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       {self.convert_ids_to_tokens(snake_case__   ): i for i in range(self.vocab_size   )}
            vocab.update(self.added_tokens_encoder   )
            return vocab







     def __getstate__( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Tuple   			=       self.__dict__.copy()
            _lowerCAmelCase    :							Dict   			=       None
            return state







     def __setstate__( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							str   			=       d

            # for backward compatibility
            if not hasattr(self      ,	'sp_model_kwargs'   ):
                   _lowerCAmelCase    :							List[str]   			=       {}

            _lowerCAmelCase    :							Tuple   			=       load_spm(self.spm_file      ,	self.sp_model_kwargs   )







     def a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Tuple   			=       Path(snake_case__   )
            if not save_dir.is_dir():
                   raise OSError(F'{save_directory} should be a directory'   )
            _lowerCAmelCase    :							int   			=       save_dir / (
                (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
            )
            _lowerCAmelCase    :							str   			=       save_dir / (
                (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
            )

            save_json(self.encoder      ,	snake_case__   )

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

            return (str(snake_case__   ), str(snake_case__   ))







     def a	( self      ,	snake_case__      ,	snake_case__ = "en"      ,	snake_case__ = None      ,	snake_case__ = "ro"      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							Any   			=       src_lang
            _lowerCAmelCase    :							Tuple   			=       tgt_lang
            self.set_src_lang_special_tokens(self.src_lang   )
            return super().prepare_seqaseq_batch(snake_case__      ,	snake_case__      ,	**snake_case__   )







     def a	( self      ,	snake_case__      ,	snake_case__      ,	snake_case__      ,	**snake_case__   ):

            '''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    :							Union[str, Any]   			=       src_lang
            _lowerCAmelCase    :							List[str]   			=       self(snake_case__      ,	add_special_tokens=snake_case__      ,	**snake_case__   )
            _lowerCAmelCase    :							Optional[int]   			=       self.get_lang_id(snake_case__   )
            _lowerCAmelCase    :							Union[str, Any]   			=       tgt_lang_id
            return inputs







     def a	( self   ):

            '''simple docstring'''

            self.set_src_lang_special_tokens(self.src_lang   )







     def a	( self   ):

            '''simple docstring'''

            self.set_tgt_lang_special_tokens(self.tgt_lang   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[Any]   			=       self.get_lang_token(snake_case__   )
            _lowerCAmelCase    :							List[str]   			=       self.lang_token_to_id[lang_token]
            _lowerCAmelCase    :							str   			=       [self.cur_lang_id]
            _lowerCAmelCase    :							Tuple   			=       [self.eos_token_id]







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[Any]   			=       self.get_lang_token(snake_case__   )
            _lowerCAmelCase    :							Optional[int]   			=       self.lang_token_to_id[lang_token]
            _lowerCAmelCase    :							str   			=       [self.cur_lang_id]
            _lowerCAmelCase    :							Dict   			=       [self.eos_token_id]







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            return self.lang_code_to_token[lang]







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[Any]   			=       self.get_lang_token(snake_case__   )
            return self.lang_token_to_id[lang_token]






def 			lowercase				(_A   ,						_A					):







       """simple docstring"""







       _lowerCAmelCase    :							str   			=       sentencepiece.SentencePieceProcessor(**_A					)
       spm.Load(str(_A					)					)
       return spm






def 			lowercase				(_A					):







       """simple docstring"""







       with open(_A   ,						'r'					) as f:
              return json.load(_A					)






def 			lowercase				(_A   ,						_A					):







       """simple docstring"""







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





'''simple docstring'''







import unittest

from knapsack import greedy_knapsack as kp
class 	UpperCamelCase__					( unittest.TestCase	):



     """simple docstring"""






     def a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       [10, 20, 30, 40, 50, 60]
            _lowerCAmelCase    :							Union[str, Any]   			=       [2, 4, 6, 8, 10, 12]
            _lowerCAmelCase    :							Dict   			=       100
            self.assertEqual(kp.calc_profit(snake_case__      ,	snake_case__      ,	snake_case__   )      ,	210   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'max_weight must greater than zero.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'Weight can not be negative.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'Profit can not be negative.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'max_weight must greater than zero.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(
                snake_case__      ,	'The length of profit and weight must be same.'   )


if __name__ == "__main__":
       unittest.main()

