






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


lowerCamelCase__							=     logging.get_logger(__name__)

# TODO: upload to AWS
lowerCamelCase__							=     {
    """yjernite/retribert-base-uncased""": (
        """https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"""
    ),
}




class 			snake_case__   (							lowercase_):

       '''simple docstring'''
       lowerCamelCase							:				Any 				= "retribert"



       def __init__(							self			,						a__=3_05_22			,						a__=7_68			,						a__=8			,						a__=12			,						a__=30_72			,						a__="gelu"			,						a__=0.1			,						a__=0.1			,						a__=5_12			,						a__=2			,						a__=0.02			,						a__=1e-12			,						a__=True			,						a__=1_28			,						a__=0			,						**a__			,						) ->      Any:






            '''simple docstring'''





            super().__init__(pad_token_id=a__			,						**a__    )

            __snake_case			:str          =						vocab_size
            __snake_case			:List[str]          =						hidden_size
            __snake_case			:str          =						num_hidden_layers
            __snake_case			:Tuple          =						num_attention_heads
            __snake_case			:Optional[int]          =						hidden_act
            __snake_case			:Dict          =						intermediate_size
            __snake_case			:Tuple          =						hidden_dropout_prob
            __snake_case			:Any          =						attention_probs_dropout_prob
            __snake_case			:Union[str, Any]          =						max_position_embeddings
            __snake_case			:Optional[int]          =						type_vocab_size
            __snake_case			:List[Any]          =						initializer_range
            __snake_case			:List[Any]          =						layer_norm_eps
            __snake_case			:Tuple          =						share_encoders
            __snake_case			:Any          =						projection_dim










from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowerCamelCase__							=     {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     ["""DPTFeatureExtractor"""]
     lowerCamelCase__							=     ["""DPTImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     [
         """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """DPTForDepthEstimation""",
         """DPTForSemanticSegmentation""",
         """DPTModel""",
         """DPTPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_dpt import DPTFeatureExtractor
          from .image_processing_dpt import DPTImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_dpt import (
              DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
              DPTForDepthEstimation,
              DPTForSemanticSegmentation,
              DPTModel,
              DPTPreTrainedModel,
          )


else:
     import sys

     lowerCamelCase__							=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


