


'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_      :		Dict          =		logging.get_logger(__name__)

UpperCAmelCase_      :		List[str]          =		{
    "uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
    "uclanlp/visualbert-vqa-pre": "https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/config.json",
    "uclanlp/visualbert-vqa-coco-pre": (
        "https://huggingface.co/uclanlp/visualbert-vqa-coco-pre/resolve/main/config.json"
    ),
    "uclanlp/visualbert-vcr": "https://huggingface.co/uclanlp/visualbert-vcr/resolve/main/config.json",
    "uclanlp/visualbert-vcr-pre": "https://huggingface.co/uclanlp/visualbert-vcr-pre/resolve/main/config.json",
    "uclanlp/visualbert-vcr-coco-pre": (
        "https://huggingface.co/uclanlp/visualbert-vcr-coco-pre/resolve/main/config.json"
    ),
    "uclanlp/visualbert-nlvr2": "https://huggingface.co/uclanlp/visualbert-nlvr2/resolve/main/config.json",
    "uclanlp/visualbert-nlvr2-pre": "https://huggingface.co/uclanlp/visualbert-nlvr2-pre/resolve/main/config.json",
    "uclanlp/visualbert-nlvr2-coco-pre": (
        "https://huggingface.co/uclanlp/visualbert-nlvr2-coco-pre/resolve/main/config.json"
    )
    # See all VisualBERT models at https://huggingface.co/models?filter=visual_bert
}







class 					a			(				snake_case__  ):
 '''simple docstring'''




 __lowerCAmelCase						: int							  =		"""visual_bert"""




 def __init__(    self		,      lowerCamelCase_=3_0_5_2_2		,      lowerCamelCase_=7_6_8		,      lowerCamelCase_=5_1_2		,      lowerCamelCase_=1_2		,      lowerCamelCase_=1_2		,      lowerCamelCase_=3_0_7_2		,      lowerCamelCase_="gelu"		,      lowerCamelCase_=0.1		,      lowerCamelCase_=0.1		,      lowerCamelCase_=5_1_2		,      lowerCamelCase_=2		,      lowerCamelCase_=0.02		,      lowerCamelCase_=1e-12		,      lowerCamelCase_=False		,      lowerCamelCase_=True		,      lowerCamelCase_=1		,      lowerCamelCase_=0		,      lowerCamelCase_=2		,      **lowerCamelCase_		,      )      ->    Optional[Any]:
    super().__init__(pad_token_id=lowerCamelCase_		,      bos_token_id=lowerCamelCase_		,      eos_token_id=lowerCamelCase_		,      **lowerCamelCase_      )

    _a					:  List[str]						=  vocab_size
    _a					:  Union[str, Any]						=  max_position_embeddings
    _a					:  Tuple						=  hidden_size
    _a					:  Tuple						=  visual_embedding_dim
    _a					:  Optional[Any]						=  num_hidden_layers
    _a					:  str						=  num_attention_heads
    _a					:  Union[str, Any]						=  intermediate_size
    _a					:  List[str]						=  hidden_act
    _a					:  str						=  hidden_dropout_prob
    _a					:  List[Any]						=  attention_probs_dropout_prob
    _a					:  Optional[Any]						=  initializer_range
    _a					:  List[Any]						=  type_vocab_size
    _a					:  Any						=  layer_norm_eps
    _a					:  Tuple						=  bypass_transformer
    _a					:  str						=  special_visual_initialize






'''simple docstring'''




import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


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

UpperCAmelCase_      :		Union[str, Any]          =		{
    "vocab_file": {
        "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt",
    },
    "tokenizer_file": {
        "unc-nlp/lxmert-base-uncased": (
            "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json"
        ),
    },
}

UpperCAmelCase_      :		str          =		{
    "unc-nlp/lxmert-base-uncased": 512,
}

UpperCAmelCase_      :		Optional[int]          =		{
    "unc-nlp/lxmert-base-uncased": {"do_lower_case": True},
}







class 					a			(				snake_case__  ):
 '''simple docstring'''




 __lowerCAmelCase						: Tuple							  =		VOCAB_FILES_NAMES
 __lowerCAmelCase						: Dict							  =		PRETRAINED_VOCAB_FILES_MAP
 __lowerCAmelCase						: Optional[Any]							  =		PRETRAINED_INIT_CONFIGURATION
 __lowerCAmelCase						: str							  =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCAmelCase						: List[Any]							  =		LxmertTokenizer




 def __init__(    self		,      lowerCamelCase_=None		,      lowerCamelCase_=None		,      lowerCamelCase_=True		,      lowerCamelCase_="[UNK]"		,      lowerCamelCase_="[SEP]"		,      lowerCamelCase_="[PAD]"		,      lowerCamelCase_="[CLS]"		,      lowerCamelCase_="[MASK]"		,      lowerCamelCase_=True		,      lowerCamelCase_=None		,      **lowerCamelCase_		,      )      ->    Optional[int]:
    super().__init__(
        lowerCamelCase_		,      tokenizer_file=lowerCamelCase_		,      do_lower_case=lowerCamelCase_		,      unk_token=lowerCamelCase_		,      sep_token=lowerCamelCase_		,      pad_token=lowerCamelCase_		,      cls_token=lowerCamelCase_		,      mask_token=lowerCamelCase_		,      tokenize_chinese_chars=lowerCamelCase_		,      strip_accents=lowerCamelCase_		,      **lowerCamelCase_		,      )

    _a					:  str						=  json.loads(self.backend_tokenizer.normalizer.__getstate__()      )
    if (
        normalizer_state.get('lowercase'		,      lowerCamelCase_      ) != do_lower_case
        or normalizer_state.get('strip_accents'		,      lowerCamelCase_      ) != strip_accents
        or normalizer_state.get('handle_chinese_chars'		,      lowerCamelCase_      ) != tokenize_chinese_chars
    ):
       _a					:  str						=  getattr(lowerCamelCase_		,      normalizer_state.pop('type'      )      )
       _a					:  Tuple						=  do_lower_case
       _a					:  str						=  strip_accents
       _a					:  Optional[Any]						=  tokenize_chinese_chars
       _a					:  Dict						=  normalizer_class(**lowerCamelCase_      )

    _a					:  Optional[int]						=  do_lower_case




 def   __UpperCamelCase   (    self		,      lowerCamelCase_		,      lowerCamelCase_=None      )      ->    Optional[Any]:
    _a					:  List[str]						=  [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		,      lowerCamelCase_		,      lowerCamelCase_ = None      )      ->    List[int]:
    _a					:  Union[str, Any]						=  [self.sep_token_id]
    _a					:  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   __UpperCamelCase   (    self		,      lowerCamelCase_		,      lowerCamelCase_ = None      )      ->    Tuple[str]:
    _a					:  Optional[Any]						=  self._tokenizer.model.save(lowerCamelCase_		,      name=lowerCamelCase_      )
    return tuple(lowerCamelCase_      )


