"""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


__SCREAMING_SNAKE_CASE								=logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE								="▁"

__SCREAMING_SNAKE_CASE								={
    "vocab_file": "vocab.json",
    "spm_file": "sentencepiece.bpe.model",
    "tokenizer_config_file": "tokenizer_config.json",
}

__SCREAMING_SNAKE_CASE								={
    "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",
    },
}

__SCREAMING_SNAKE_CASE								={
    "facebook/m2m100_418M": 1024,
}

# fmt: off
__SCREAMING_SNAKE_CASE								={
    "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	(    lowercase_						):
   lowercase							=						VOCAB_FILES_NAMES
   lowercase							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowercase							=						PRETRAINED_VOCAB_FILES_MAP
   lowercase							=						['input_ids', 'attention_mask']

   lowercase							=						[]
   lowercase							=						[]
   def __init__(    self  ,__UpperCamelCase  ,__UpperCamelCase  ,__UpperCamelCase=None  ,__UpperCamelCase=None  ,__UpperCamelCase="<s>"  ,__UpperCamelCase="</s>"  ,__UpperCamelCase="</s>"  ,__UpperCamelCase="<pad>"  ,__UpperCamelCase="<unk>"  ,__UpperCamelCase="m2m100"  ,__UpperCamelCase = None  ,__UpperCamelCase=8  ,**__UpperCamelCase  ,)			->   None:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			{} if sp_model_kwargs is None else sp_model_kwargs

        lowercase_			:       str									=			language_codes
        lowercase_			:       str									=			FAIRSEQ_LANGUAGE_CODES[language_codes]
        lowercase_			:       Dict									=			{lang_code: f'''__{lang_code}__''' for lang_code in fairseq_language_code}

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

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

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

        lowercase_			:       Any									=			len(self.encoder    )

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

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

        lowercase_			:       str									=			num_madeup_words
   @property
   def     _UpperCAmelCase     (    self    )			->   int:


        '''simple docstring'''


        return len(self.encoder    ) + len(self.lang_token_to_id    )
   @property
   def     _UpperCAmelCase     (    self    )			->   str:


        '''simple docstring'''


        return self._src_lang
   @src_lang.setter
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       Tuple									=			new_src_lang
        self.set_src_lang_special_tokens(self._src_lang    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   List[str]:


        '''simple docstring'''


        return self.sp_model.encode(__UpperCamelCase  ,out_type=__UpperCamelCase    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   List[str]:


        '''simple docstring'''


        if token in self.lang_token_to_id:
             return self.lang_token_to_id[token]
        return self.encoder.get(__UpperCamelCase  ,self.encoder[self.unk_token]    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   str:


        '''simple docstring'''


        if index in self.id_to_lang_token:
             return self.id_to_lang_token[index]
        return self.decoder.get(__UpperCamelCase  ,self.unk_token    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   Tuple:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			[]
        lowercase_			:       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(__UpperCamelCase    ) + token
                  lowercase_			:       List[str]									=			[]
             else:
                  current_sub_tokens.append(__UpperCamelCase    )
        out_string += self.sp_model.decode(__UpperCamelCase    )
        return out_string.strip()
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None  ,__UpperCamelCase = False    )			->   List[int]:


        '''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    )

        lowercase_			:       Any									=			[1] * len(self.prefix_tokens    )
        lowercase_			:       Dict									=			[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    )			->   List[int]:


        '''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    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       Tuple									=			{self.convert_ids_to_tokens(__UpperCamelCase    ): i for i in range(self.vocab_size    )}
        vocab.update(self.added_tokens_encoder    )
        return vocab
   def __getstate__(    self    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			self.__dict__.copy()
        lowercase_			:       List[Any]									=			None
        return state
   def __setstate__(    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			d

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

        lowercase_			:       List[Any]									=			load_spm(self.spm_file  ,self.sp_model_kwargs    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   Tuple[str]:


        '''simple docstring'''


        lowercase_			:       List[str]									=			Path(__UpperCamelCase    )
        if not save_dir.is_dir():
             raise OSError(f'''{save_directory} should be a directory'''    )
        lowercase_			:       Union[str, Any]									=			save_dir / (
            (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
        )
        lowercase_			:       Optional[Any]									=			save_dir / (
            (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
        )

        save_json(self.encoder  ,__UpperCamelCase    )

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

        return (str(__UpperCamelCase    ), str(__UpperCamelCase    ))
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = "en"  ,__UpperCamelCase = None  ,__UpperCamelCase = "ro"  ,**__UpperCamelCase  ,)			->   BatchEncoding:


        '''simple docstring'''


        lowercase_			:       Optional[int]									=			src_lang
        lowercase_			:       List[str]									=			tgt_lang
        self.set_src_lang_special_tokens(self.src_lang    )
        return super().prepare_seqaseq_batch(__UpperCamelCase  ,__UpperCamelCase  ,**__UpperCamelCase    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase  ,__UpperCamelCase  ,**__UpperCamelCase    )			->   Tuple:


        '''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'    )
        lowercase_			:       Optional[Any]									=			src_lang
        lowercase_			:       List[Any]									=			self(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase  ,**__UpperCamelCase    )
        lowercase_			:       List[str]									=			self.get_lang_id(__UpperCamelCase    )
        lowercase_			:       Tuple									=			tgt_lang_id
        return inputs
   def     _UpperCAmelCase     (    self    )			->   str:


        '''simple docstring'''


        self.set_src_lang_special_tokens(self.src_lang    )
   def     _UpperCAmelCase     (    self    )			->   Union[str, Any]:


        '''simple docstring'''


        self.set_tgt_lang_special_tokens(self.tgt_lang    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			self.get_lang_token(__UpperCamelCase    )
        lowercase_			:       List[str]									=			self.lang_token_to_id[lang_token]
        lowercase_			:       List[str]									=			[self.cur_lang_id]
        lowercase_			:       int									=			[self.eos_token_id]
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       str									=			self.get_lang_token(__UpperCamelCase    )
        lowercase_			:       Dict									=			self.lang_token_to_id[lang_token]
        lowercase_			:       Optional[Any]									=			[self.cur_lang_id]
        lowercase_			:       Any									=			[self.eos_token_id]
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   str:


        '''simple docstring'''


        return self.lang_code_to_token[lang]







   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   int:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			self.get_lang_token(__UpperCamelCase    )
        return self.lang_token_to_id[lang_token]






def     lowercase__( __SCREAMING_SNAKE_CASE							:  str  ,    __SCREAMING_SNAKE_CASE							:  Dict[str, Any]   ):
     lowercase_			:       Union[str, Any]									=			sentencepiece.SentencePieceProcessor(**__SCREAMING_SNAKE_CASE   )
     spm.Load(str(__SCREAMING_SNAKE_CASE   )   )
     return spm



def     lowercase__( __SCREAMING_SNAKE_CASE							:  str   ):
     with open(__SCREAMING_SNAKE_CASE  ,    'r'   ) as f:
          return json.load(__SCREAMING_SNAKE_CASE   )







def     lowercase__( __SCREAMING_SNAKE_CASE							:  Dict  ,    __SCREAMING_SNAKE_CASE							:  str   ):
     with open(__SCREAMING_SNAKE_CASE  ,    'w'   ) as f:
          json.dump(__SCREAMING_SNAKE_CASE  ,    __SCREAMING_SNAKE_CASE  ,    indent=2   )


"""simple docstring"""







from argparse import ArgumentParser

from .env import EnvironmentCommand



def     lowercase__( ):
     lowercase_			:       List[Any]									=			ArgumentParser('Diffusers CLI tool'  ,    usage='diffusers-cli <command> [<args>]'   )
     lowercase_			:       int									=			parser.add_subparsers(help='diffusers-cli command helpers'   )

     # Register commands
     EnvironmentCommand.register_subcommand(__SCREAMING_SNAKE_CASE   )

     # Let's go
     lowercase_			:       str									=			parser.parse_args()

     if not hasattr(__SCREAMING_SNAKE_CASE  ,    'func'   ):
          parser.print_help()
          exit(1   )

     # Run
     lowercase_			:       Optional[Any]									=			args.func(__SCREAMING_SNAKE_CASE   )
     service.run()


if __name__ == "__main__":
       main()

