
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase  :					int						    =							{
    """configuration_mobilebert""": [
        """MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileBertConfig""",
        """MobileBertOnnxConfig""",
    ],
    """tokenization_mobilebert""": ["""MobileBertTokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  :					Optional[int]						    =							["""MobileBertTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  :					Optional[Any]						    =							[
      """MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """MobileBertForMaskedLM""",
      """MobileBertForMultipleChoice""",
      """MobileBertForNextSentencePrediction""",
      """MobileBertForPreTraining""",
      """MobileBertForQuestionAnswering""",
      """MobileBertForSequenceClassification""",
      """MobileBertForTokenClassification""",
      """MobileBertLayer""",
      """MobileBertModel""",
      """MobileBertPreTrainedModel""",
      """load_tf_weights_in_mobilebert""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase  :					int						    =							[
      """TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFMobileBertForMaskedLM""",
      """TFMobileBertForMultipleChoice""",
      """TFMobileBertForNextSentencePrediction""",
      """TFMobileBertForPreTraining""",
      """TFMobileBertForQuestionAnswering""",
      """TFMobileBertForSequenceClassification""",
      """TFMobileBertForTokenClassification""",
      """TFMobileBertMainLayer""",
      """TFMobileBertModel""",
      """TFMobileBertPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_mobilebert import (
      MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      MobileBertConfig,
      MobileBertOnnxConfig,
  )
  from .tokenization_mobilebert import MobileBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_mobilebert_fast import MobileBertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mobilebert import (
        MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        MobileBertForMaskedLM,
        MobileBertForMultipleChoice,
        MobileBertForNextSentencePrediction,
        MobileBertForPreTraining,
        MobileBertForQuestionAnswering,
        MobileBertForSequenceClassification,
        MobileBertForTokenClassification,
        MobileBertLayer,
        MobileBertModel,
        MobileBertPreTrainedModel,
        load_tf_weights_in_mobilebert,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_mobilebert import (
        TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFMobileBertForMaskedLM,
        TFMobileBertForMultipleChoice,
        TFMobileBertForNextSentencePrediction,
        TFMobileBertForPreTraining,
        TFMobileBertForQuestionAnswering,
        TFMobileBertForSequenceClassification,
        TFMobileBertForTokenClassification,
        TFMobileBertMainLayer,
        TFMobileBertModel,
        TFMobileBertPreTrainedModel,
    )

else:
  import sys

  lowercase  :					Union[str, Any]						    =							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


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


lowercase  :					List[str]						    =							logging.get_logger(__name__)

lowercase  :					Any						    =							{
    """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 __snake_case		(      lowerCAmelCase     ):
    _a		:						Union[str, Any]=				"visual_bert"
    def __init__(  self		,snake_case=30522		,snake_case=768		,snake_case=512		,snake_case=12		,snake_case=12		,snake_case=3072		,snake_case="gelu"		,snake_case=0.1		,snake_case=0.1		,snake_case=512		,snake_case=2		,snake_case=0.02		,snake_case=1e-12		,snake_case=False		,snake_case=True		,snake_case=1		,snake_case=0		,snake_case=2		,**snake_case		,):



           '''simple docstring'''







           super().__init__(pad_token_id=snake_case		,bos_token_id=snake_case		,eos_token_id=snake_case		,**snake_case      )

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