
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


SCREAMING_SNAKE_CASE       :		int         =				logging.get_logger(__name__)

SCREAMING_SNAKE_CASE       :		Optional[int]         =				{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

SCREAMING_SNAKE_CASE       :		Tuple         =				{
    "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"
        ),
    },
}

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


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






class      UpperCamelCase					(		lowercase__     ):


   '''simple docstring'''







   lowercase					:	Tuple									=VOCAB_FILES_NAMES
   lowercase					:	Tuple									=PRETRAINED_VOCAB_FILES_MAP
   lowercase					:	Any									=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowercase					:	List[str]									=PRETRAINED_INIT_CONFIGURATION
   lowercase					:	List[Any]									=RetriBertTokenizer
   lowercase					:	List[Any]									=["""input_ids""", """attention_mask"""]
   def __init__(     self   ,							UpperCamelCase_=None   ,							UpperCamelCase_=None   ,							UpperCamelCase_=True   ,							UpperCamelCase_="[UNK]"   ,							UpperCamelCase_="[SEP]"   ,							UpperCamelCase_="[PAD]"   ,							UpperCamelCase_="[CLS]"   ,							UpperCamelCase_="[MASK]"   ,							UpperCamelCase_=True   ,							UpperCamelCase_=None   ,							**UpperCamelCase_   ,							):
        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_   ,							)

        lowercase_       :int     =       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
        ):
             lowercase_       :List[Any]     =       getattr(UpperCamelCase_   ,							normalizer_state.pop('''type'''		)		)
             lowercase_       :Any     =       do_lower_case
             lowercase_       :List[Any]     =       strip_accents
             lowercase_       :Union[str, Any]     =       tokenize_chinese_chars
             lowercase_       :int     =       normalizer_class(**UpperCamelCase_		)

        lowercase_       :Union[str, Any]     =       do_lower_case
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_=None		):
        lowercase_       :Optional[int]     =       [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 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_ = None		):
        lowercase_       :Tuple     =       [self.sep_token_id]
        lowercase_       :str     =       [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 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_ = None		):
        lowercase_       :Union[str, Any]     =       self._tokenizer.model.save(UpperCamelCase_   ,							name=UpperCamelCase_		)
        return tuple(UpperCamelCase_		)





from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
SCREAMING_SNAKE_CASE       :		List[str]         =				HfArgumentParser(InitializationArguments)
SCREAMING_SNAKE_CASE       :		List[Any]         =				parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
SCREAMING_SNAKE_CASE       :		Union[str, Any]         =				AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
SCREAMING_SNAKE_CASE       :		Optional[Any]         =				{
    "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)
SCREAMING_SNAKE_CASE       :		Any         =				AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
SCREAMING_SNAKE_CASE       :		Dict         =				AutoModelForCausalLM.from_config(config)

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

