



"""simple docstring"""

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


lowercase__    :  str							    =	logging.get_logger(__name__)

lowercase__    :  Optional[Any]							    =	{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__    :  List[str]							    =	{
    '''vocab_file''': {
        '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt''',
        '''distilbert-base-uncased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt'''
        ),
        '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt''',
        '''distilbert-base-cased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt'''
        ),
        '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt''',
        '''distilbert-base-multilingual-cased''': (
            '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json''',
        '''distilbert-base-uncased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json''',
        '''distilbert-base-cased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-german-cased''': (
            '''https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-multilingual-cased''': (
            '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json'''
        ),
    },
}

lowercase__    :  Optional[int]							    =	{
    '''distilbert-base-uncased''': 5_12,
    '''distilbert-base-uncased-distilled-squad''': 5_12,
    '''distilbert-base-cased''': 5_12,
    '''distilbert-base-cased-distilled-squad''': 5_12,
    '''distilbert-base-german-cased''': 5_12,
    '''distilbert-base-multilingual-cased''': 5_12,
}


lowercase__    :  Tuple							    =	{
    '''distilbert-base-uncased''': {'''do_lower_case''': True},
    '''distilbert-base-uncased-distilled-squad''': {'''do_lower_case''': True},
    '''distilbert-base-cased''': {'''do_lower_case''': False},
    '''distilbert-base-cased-distilled-squad''': {'''do_lower_case''': False},
    '''distilbert-base-german-cased''': {'''do_lower_case''': False},
    '''distilbert-base-multilingual-cased''': {'''do_lower_case''': False},
}




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

 def __init__(     self		:       str  ,     lowercase_		:       int=None  ,     lowercase_		:       int=None  ,     lowercase_		:       int=True  ,     lowercase_		:       List[str]="[UNK]"  ,     lowercase_		:       int="[SEP]"  ,     lowercase_		:       Tuple="[PAD]"  ,     lowercase_		:       Optional[int]="[CLS]"  ,     lowercase_		:       Optional[Any]="[MASK]"  ,     lowercase_		:       List[Any]=True  ,     lowercase_		:       List[Any]=None  ,     **lowercase_		:       Union[str, Any]  ,     ):
     super().__init__(
         lowercase_  ,     tokenizer_file=lowercase_  ,     do_lower_case=lowercase_  ,     unk_token=lowercase_  ,     sep_token=lowercase_  ,     pad_token=lowercase_  ,     cls_token=lowercase_  ,     mask_token=lowercase_  ,     tokenize_chinese_chars=lowercase_  ,     strip_accents=lowercase_  ,     **lowercase_  ,     )

     snake_case_ :     int				=	json.loads(self.backend_tokenizer.normalizer.__getstate__()				)
     if (
         normalizer_state.get('''lowercase'''  ,     lowercase_				) != do_lower_case
         or normalizer_state.get('''strip_accents'''  ,     lowercase_				) != strip_accents
         or normalizer_state.get('''handle_chinese_chars'''  ,     lowercase_				) != tokenize_chinese_chars
     ):
         snake_case_ :     List[str]				=	getattr(lowercase_  ,     normalizer_state.pop('''type'''				)				)
         snake_case_ :     Tuple				=	do_lower_case
         snake_case_ :     str				=	strip_accents
         snake_case_ :     Union[str, Any]				=	tokenize_chinese_chars
         snake_case_ :     str				=	normalizer_class(**lowercase_				)

     snake_case_ :     List[Any]				=	do_lower_case

 def 						_snake_case					(     self		:       Union[str, Any]  ,     lowercase_		:       int  ,     lowercase_		:       Union[str, Any]=None				):
     snake_case_ :     List[Any]				=	[self.cls_token_id] + token_ids_a + [self.sep_token_id]

     if token_ids_a:
         output += token_ids_a + [self.sep_token_id]

     return output

 def 						_snake_case					(     self		:       Any  ,     lowercase_		:       List[int]  ,     lowercase_		:       Optional[List[int]] = None				):
     snake_case_ :     str				=	[self.sep_token_id]
     snake_case_ :     Dict				=	[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				) * [0] + len(token_ids_a + sep				) * [1]






 def 						_snake_case					(     self		:       str  ,     lowercase_		:       str  ,     lowercase_		:       Optional[str] = None				):
     snake_case_ :     Union[str, Any]				=	self._tokenizer.model.save(lowercase_  ,     name=lowercase_				)
     return tuple(lowercase_				)










"""simple docstring"""

import argparse
import json

import numpy
import torch

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()




def __lowercase			(							_a		,			_a    ):
    # Load checkpoint
    snake_case_ :     Optional[Any]				=	torch.load(_a		,			map_location='''cpu'''    )

    snake_case_ :     Union[str, Any]				=	chkpt['''model''']

    # We have the base model one level deeper than the original XLM repository
    snake_case_ :     Dict				=	{}
    for k, v in state_dict.items():
        if "pred_layer" in k:
            snake_case_ :     Union[str, Any]				=	v
        else:
            snake_case_ :     Dict				=	v

    snake_case_ :     Union[str, Any]				=	chkpt['''params''']
    snake_case_ :     int				=	{n: v for n, v in config.items() if not isinstance(_a		,			(torch.FloatTensor, numpy.ndarray)    )}

    snake_case_ :     int				=	chkpt['''dico_word2id''']
    snake_case_ :     str				=	{s + '''</w>''' if s.find('''@@'''    ) == -1 and i > 13 else s.replace('''@@'''		,			''''''    ): i for s, i in vocab.items()}

    # Save pytorch-model
    snake_case_ :     Union[str, Any]				=	pytorch_dump_folder_path + '''/''' + WEIGHTS_NAME
    snake_case_ :     Union[str, Any]				=	pytorch_dump_folder_path + '''/''' + CONFIG_NAME
    snake_case_ :     Any				=	pytorch_dump_folder_path + '''/''' + VOCAB_FILES_NAMES['''vocab_file''']

    print(f"Save PyTorch model to {pytorch_weights_dump_path}"    )
    torch.save(_a		,			_a    )

    print(f"Save configuration file to {pytorch_config_dump_path}"    )
    with open(_a		,			'''w'''		,			encoding='''utf-8'''    ) as f:
        f.write(json.dumps(_a		,			indent=2    ) + '''\n'''    )

    print(f"Save vocab file to {pytorch_config_dump_path}"    )
    with open(_a		,			'''w'''		,			encoding='''utf-8'''    ) as f:
        f.write(json.dumps(_a		,			indent=2    ) + '''\n'''    )


if __name__ == "__main__":
     lowercase__    :  Optional[Any]							    =	argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         '''--xlm_checkpoint_path''', default=None, type=str, required=True, help='''Path the official PyTorch dump.'''
     )
     parser.add_argument(
         '''--pytorch_dump_folder_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
     )
     lowercase__    :  List[str]							    =	parser.parse_args()
     convert_xlm_checkpoint_to_pytorch(args.xlm_checkpoint_path, args.pytorch_dump_folder_path)





