






import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowerCamelCase					    =	'''src/transformers'''

# Matches is_xxx_available()
lowerCamelCase					    =	re.compile(r'''is\_([a-z_]*)_available()''')
# Matches from xxx import bla
lowerCamelCase					    =	re.compile(r'''\s+from\s+\S*\s+import\s+([^\(\s].*)\n''')
lowerCamelCase					    =	re.compile(r'''^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)''')


lowerCamelCase					    =	'''
{0} = None
'''

lowerCamelCase					    =	'''
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
'''


lowerCamelCase					    =	'''
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
'''
def 							UpperCAmelCase   ( _lowercase   ):


    '''simple docstring'''



    if _re_test_backend.search(UpperCAmelCase__   ) is None:
        return None
    _lowercase     			=						[b[0] for b in _re_backend.findall(UpperCAmelCase__   )]
    backends.sort()
    return "_and_".join(UpperCAmelCase__   )
def 							UpperCAmelCase   ( ):


    '''simple docstring'''



    with open(os.path.join(UpperCAmelCase__,   '__init__.py'   ),   'r',   encoding='utf-8',   newline='\n'   ) as f:
        _lowercase     			=						f.readlines()

    # Get to the point we do the actual imports for type checking
    _lowercase     			=						0
    while not lines[line_index].startswith('if TYPE_CHECKING'   ):
        line_index += 1

    _lowercase     			=						{}
    # Go through the end of the file
    while line_index < len(UpperCAmelCase__   ):
        # If the line is an if is_backend_available, we grab all objects associated.
        _lowercase     			=						find_backend(lines[line_index]   )
        if backend is not None:
            while not lines[line_index].startswith('    else:'   ):
                line_index += 1
            line_index += 1

            _lowercase     			=						[]
            # Until we unindent, add backend objects to the list
            while len(lines[line_index]   ) <= 1 or lines[line_index].startswith(' ' * 8   ):
                _lowercase     			=						lines[line_index]
                _lowercase     			=						_re_single_line_import.search(UpperCAmelCase__   )
                if single_line_import_search is not None:
                    objects.extend(single_line_import_search.groups()[0].split(', '   )   )
                elif line.startswith(' ' * 12   ):
                    objects.append(line[12:-2]   )
                line_index += 1

            _lowercase     			=						objects
        else:
            line_index += 1

    return backend_specific_objects
def 							UpperCAmelCase   ( _lowercase,   _lowercase   ):


    '''simple docstring'''



    if name.isupper():
        return DUMMY_CONSTANT.format(UpperCAmelCase__   )
    elif name.islower():
        return DUMMY_FUNCTION.format(UpperCAmelCase__,   UpperCAmelCase__   )
    else:
        return DUMMY_CLASS.format(UpperCAmelCase__,   UpperCAmelCase__   )
def 							UpperCAmelCase   ( _lowercase=None   ):


    '''simple docstring'''



    if backend_specific_objects is None:
        _lowercase     			=						read_init()
    # For special correspondence backend to module name as used in the function requires_modulename
    _lowercase     			=						{}

    for backend, objects in backend_specific_objects.items():
        _lowercase     			=						'[' + ', '.join(f'''\"{b}\"''' for b in backend.split('_and_'   )   ) + ']'
        _lowercase     			=						'# This file is autogenerated by the command `make fix-copies`, do not edit.\n'
        dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
        dummy_file += "\n".join([create_dummy_object(UpperCAmelCase__,   UpperCAmelCase__   ) for o in objects]   )
        _lowercase     			=						dummy_file

    return dummy_files
def 							UpperCAmelCase   ( _lowercase=False   ):


    '''simple docstring'''



    _lowercase     			=						create_dummy_files()
    # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
    _lowercase     			=						{'torch': 'pt'}

    # Locate actual dummy modules and read their content.
    _lowercase     			=						os.path.join(UpperCAmelCase__,   'utils'   )
    _lowercase     			=						{
        backend: os.path.join(UpperCAmelCase__,   f'''dummy_{short_names.get(UpperCAmelCase__,   UpperCAmelCase__   )}_objects.py'''   )
        for backend in dummy_files.keys()
    }

    _lowercase     			=						{}
    for backend, file_path in dummy_file_paths.items():
        if os.path.isfile(UpperCAmelCase__   ):
            with open(UpperCAmelCase__,   'r',   encoding='utf-8',   newline='\n'   ) as f:
                _lowercase     			=						f.read()
        else:
            _lowercase     			=						''

    for backend in dummy_files.keys():
        if dummy_files[backend] != actual_dummies[backend]:
            if overwrite:
                print(
                    f'''Updating transformers.utils.dummy_{short_names.get(UpperCAmelCase__,   UpperCAmelCase__   )}_objects.py as the main '''
                    '__init__ has new objects.'   )
                with open(dummy_file_paths[backend],   'w',   encoding='utf-8',   newline='\n'   ) as f:
                    f.write(dummy_files[backend]   )
            else:
                raise ValueError(
                    'The main __init__ has objects that are not present in '
                    f'''transformers.utils.dummy_{short_names.get(UpperCAmelCase__,   UpperCAmelCase__   )}_objects.py. Run `make fix-copies` '''
                    'to fix this.'   )


if __name__ == "__main__":
   lowerCamelCase					    =	argparse.ArgumentParser()
   parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
   lowerCamelCase					    =	parser.parse_args()

   check_dummies(args.fix_and_overwrite)





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_mbartaa import MBartaaTokenizer
else:
     A_		:  Any										=  None


A_		:  Tuple										=  logging.get_logger(__name__)

A_		:  int										=  {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

A_		:  List[Any]										=  {
    '''vocab_file''': {
        '''facebook/mbart-large-50-one-to-many-mmt''': (
            '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-50-one-to-many-mmt''': (
            '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json'''
        ),
    },
}

A_		:  Optional[Any]										=  {
    '''facebook/mbart-large-50-one-to-many-mmt''': 10_24,
}

# fmt: off
A_		:  List[str]										=  ['''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''', '''af_ZA''', '''az_AZ''', '''bn_IN''', '''fa_IR''', '''he_IL''', '''hr_HR''', '''id_ID''', '''ka_GE''', '''km_KH''', '''mk_MK''', '''ml_IN''', '''mn_MN''', '''mr_IN''', '''pl_PL''', '''ps_AF''', '''pt_XX''', '''sv_SE''', '''sw_KE''', '''ta_IN''', '''te_IN''', '''th_TH''', '''tl_XX''', '''uk_UA''', '''ur_PK''', '''xh_ZA''', '''gl_ES''', '''sl_SI''']



class 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      VOCAB_FILES_NAMES
   _UpperCAmelCase  						=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _UpperCAmelCase  						=      PRETRAINED_VOCAB_FILES_MAP
   _UpperCAmelCase  						=      ['''input_ids''', '''attention_mask''']
   _UpperCAmelCase  						=      MBartaaTokenizer

   _UpperCAmelCase  						=      []
   _UpperCAmelCase  						=      []

   def __init__(   self      :							Dict				, __lowerCAmelCase      :							Tuple=None				, __lowerCAmelCase      :							Optional[Any]=None				, __lowerCAmelCase      :							str=None				, __lowerCAmelCase      :							Union[str, Any]=None				, __lowerCAmelCase      :							Optional[int]="</s>"				, __lowerCAmelCase      :							List[Any]="</s>"				, __lowerCAmelCase      :							Optional[Any]="<s>"				, __lowerCAmelCase      :							Optional[Any]="<unk>"				, __lowerCAmelCase      :							Optional[Any]="<pad>"				, __lowerCAmelCase      :							List[Any]="<mask>"				, **__lowerCAmelCase      :							Dict				, )							->					Optional[int]:


    """simple docstring"""






    a							=		AddedToken(__lowerCAmelCase				, lstrip=__lowerCAmelCase				, rstrip=__lowerCAmelCase				) if isinstance(__lowerCAmelCase				, __lowerCAmelCase				) else mask_token

    a							=		kwargs.get("additional_special_tokens"				, []				)
    kwargs["additional_special_tokens"] += [
        code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
    ]

    super().__init__(
        __lowerCAmelCase				, src_lang=__lowerCAmelCase				, tgt_lang=__lowerCAmelCase				, tokenizer_file=__lowerCAmelCase				, eos_token=__lowerCAmelCase				, sep_token=__lowerCAmelCase				, cls_token=__lowerCAmelCase				, unk_token=__lowerCAmelCase				, pad_token=__lowerCAmelCase				, mask_token=__lowerCAmelCase				, **__lowerCAmelCase				, )

    a							=		vocab_file
    a							=		False if not self.vocab_file else True

    a							=		{
        lang_code: self.convert_tokens_to_ids(__lowerCAmelCase				) for lang_code in FAIRSEQ_LANGUAGE_CODES
    }

    a							=		src_lang if src_lang is not None else "en_XX"
    a							=		tgt_lang
    a							=		self.lang_code_to_id[self._src_lang]
    self.set_src_lang_special_tokens(self._src_lang				)

   @property
   def 		A				(   self      :							Dict				)							->					str:


    """simple docstring"""






    return self._src_lang

   @src_lang.setter
   def 		A				(   self      :							Dict				, __lowerCAmelCase      :							str				)							->					None:


    """simple docstring"""






    a							=		new_src_lang
    self.set_src_lang_special_tokens(self._src_lang				)

   def 		A				(   self      :							Dict				, __lowerCAmelCase      :							List[int]				, __lowerCAmelCase      :							Optional[List[int]] = 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 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							List[str]				, __lowerCAmelCase      :							str = "en_XX"				, __lowerCAmelCase      :							Optional[List[str]] = None				, __lowerCAmelCase      :							str = "ro_RO"				, **__lowerCAmelCase      :							Dict				, )							->					BatchEncoding:


    """simple docstring"""






    a							=		src_lang
    a							=		tgt_lang
    return super().prepare_seqaseq_batch(__lowerCAmelCase				, __lowerCAmelCase				, **__lowerCAmelCase				)

   def 		A				(   self      :							List[str]				)							->					List[str]:


    """simple docstring"""






    return self.set_src_lang_special_tokens(self.src_lang				)

   def 		A				(   self      :							str				)							->					int:


    """simple docstring"""






    return self.set_tgt_lang_special_tokens(self.tgt_lang				)

   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							str				)							->					None:


    """simple docstring"""






    a							=		self.convert_tokens_to_ids(__lowerCAmelCase				)
    a							=		[self.cur_lang_code_id]
    a							=		[self.eos_token_id]

    a							=		self.convert_ids_to_tokens(self.prefix_tokens				)
    a							=		self.convert_ids_to_tokens(self.suffix_tokens				)

    a							=		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      :							List[str]				, __lowerCAmelCase      :							str				)							->					None:


    """simple docstring"""






    a							=		self.convert_tokens_to_ids(__lowerCAmelCase				)
    a							=		[self.cur_lang_code_id]
    a							=		[self.eos_token_id]

    a							=		self.convert_ids_to_tokens(self.prefix_tokens				)
    a							=		self.convert_ids_to_tokens(self.suffix_tokens				)

    a							=		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      :							Union[str, Any]				, __lowerCAmelCase      :							Dict				, __lowerCAmelCase      :							str				, __lowerCAmelCase      :							Optional[str]				, __lowerCAmelCase      :							Optional[str]				, **__lowerCAmelCase      :							Any				)							->					Union[str, Any]:


    """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"				)
    a							=		src_lang
    a							=		self(__lowerCAmelCase				, add_special_tokens=__lowerCAmelCase				, return_tensors=__lowerCAmelCase				, **__lowerCAmelCase				)
    a							=		self.convert_tokens_to_ids(__lowerCAmelCase				)
    a							=		tgt_lang_id
    return inputs




   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							str				, __lowerCAmelCase      :							Optional[str] = None				)							->					Tuple[str]:


    """simple docstring"""






    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(__lowerCAmelCase				):
     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
     return
    a							=		os.path.join(
        __lowerCAmelCase				, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)

    if os.path.abspath(self.vocab_file				) != os.path.abspath(__lowerCAmelCase				):
     copyfile(self.vocab_file				, __lowerCAmelCase				)

    return (out_vocab_file,)

