





from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
__A									=				HfArgumentParser(InitializationArguments)
__A									=				parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
__A									=				AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
__A									=				{
    "vocab_size": len(tokenizer),
    "scale_attn_by_inverse_layer_idx": True,
    "reorder_and_upcast_attn": True,
}

# Load model config (GPT-2 large in this case)
__A									=				AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
__A									=				AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)








import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


__A									=				logging.get_logger(__name__)

__A									=				{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__A									=				{
    "vocab_file": {
        "yjernite/retribert-base-uncased": (
            "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "yjernite/retribert-base-uncased": (
            "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json"
        ),
    },
}

__A									=				{
    "yjernite/retribert-base-uncased": 512,
}


__A									=				{
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}



class    _SCREAMING_SNAKE_CASE						(	__SCREAMING_SNAKE_CASE    ):







 '''simple docstring'''
 lowercase_		=			VOCAB_FILES_NAMES
 lowercase_		=			PRETRAINED_VOCAB_FILES_MAP
 lowercase_		=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_		=			PRETRAINED_INIT_CONFIGURATION
 lowercase_		=			RetriBertTokenizer
 lowercase_		=			["input_ids", "attention_mask"]

 def __init__(self				:   int       , UpperCAmelCase_				:   List[str]=None       , UpperCAmelCase_				:   str=None       , UpperCAmelCase_				:   Optional[Any]=True       , UpperCAmelCase_				:   Union[str, Any]="[UNK]"       , UpperCAmelCase_				:   Any="[SEP]"       , UpperCAmelCase_				:   List[str]="[PAD]"       , UpperCAmelCase_				:   Optional[Any]="[CLS]"       , UpperCAmelCase_				:   Optional[Any]="[MASK]"       , UpperCAmelCase_				:   Dict=True       , UpperCAmelCase_				:   str=None       , **UpperCAmelCase_				:   str       , )       ->List[Any]:



   '''simple docstring'''



   super().__init__(
       UpperCAmelCase_       , tokenizer_file=UpperCAmelCase_       , do_lower_case=UpperCAmelCase_       , unk_token=UpperCAmelCase_       , sep_token=UpperCAmelCase_       , pad_token=UpperCAmelCase_       , cls_token=UpperCAmelCase_       , mask_token=UpperCAmelCase_       , tokenize_chinese_chars=UpperCAmelCase_       , strip_accents=UpperCAmelCase_       , **UpperCAmelCase_       , )

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

   lowerCamelCase__:      Any			  =do_lower_case

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[str]       , UpperCAmelCase_				:   Dict       , UpperCAmelCase_				:   Optional[Any]=None)       ->List[str]:



   '''simple docstring'''



   lowerCamelCase__:      Optional[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 							SCREAMING_SNAKE_CASE_					(self				:   Dict       , UpperCAmelCase_				:   List[int]       , UpperCAmelCase_				:   Optional[List[int]] = None)       ->List[int]:



   '''simple docstring'''



   lowerCamelCase__:      Tuple			  =[self.sep_token_id]
   lowerCamelCase__:      Optional[int]			  =[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 							SCREAMING_SNAKE_CASE_					(self				:   Tuple       , UpperCAmelCase_				:   str       , UpperCAmelCase_				:   Optional[str] = None)       ->Tuple[str]:



   '''simple docstring'''



   lowerCamelCase__:      Tuple			  =self._tokenizer.model.save(UpperCAmelCase_       , name=UpperCAmelCase_)
   return tuple(UpperCAmelCase_)

