






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


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

_a    :   int        =			{
    """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 	_UpperCAmelCase  (  _A		):




      """simple docstring"""



      A          =    '''visual_bert'''
      def __init__(   self    ,	_lowerCAmelCase=30_522    ,	_lowerCAmelCase=768    ,	_lowerCAmelCase=512    ,	_lowerCAmelCase=12    ,	_lowerCAmelCase=12    ,	_lowerCAmelCase=3_072    ,	_lowerCAmelCase="gelu"    ,	_lowerCAmelCase=0.1    ,	_lowerCAmelCase=0.1    ,	_lowerCAmelCase=512    ,	_lowerCAmelCase=2    ,	_lowerCAmelCase=0.02    ,	_lowerCAmelCase=1e-12    ,	_lowerCAmelCase=False    ,	_lowerCAmelCase=True    ,	_lowerCAmelCase=1    ,	_lowerCAmelCase=0    ,	_lowerCAmelCase=2    ,	**_lowerCAmelCase    ,	):



          '''simple docstring'''
          super().__init__(pad_token_id=_lowerCAmelCase    ,	bos_token_id=_lowerCAmelCase    ,	eos_token_id=_lowerCAmelCase    ,	**_lowerCAmelCase		)

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











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a    :   str        =			{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _a    :   Optional[Any]        =			[
     """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """WavLMForAudioFrameClassification""",
     """WavLMForCTC""",
     """WavLMForSequenceClassification""",
     """WavLMForXVector""",
     """WavLMModel""",
     """WavLMPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_wavlm import (
      WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      WavLMForAudioFrameClassification,
      WavLMForCTC,
      WavLMForSequenceClassification,
      WavLMForXVector,
      WavLMModel,
      WavLMPreTrainedModel,
  )

else:
 import sys

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



