


'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging


UpperCamelCase__    					=      logging.get_logger(__name__)

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




class 			lowerCamelCase_   (	snake_case_      ):
      lowerCAmelCase__		     =     'retribert'






      def __init__(					self				:    Optional[int]						,						_A				:    List[Any]=30_522						,						_A				:    Tuple=768						,						_A				:    Union[str, Any]=8						,						_A				:    int=12						,						_A				:    Optional[int]=3_072						,						_A				:    Optional[Any]="gelu"						,						_A				:    Tuple=0.1						,						_A				:    Optional[Any]=0.1						,						_A				:    Optional[Any]=512						,						_A				:    int=2						,						_A				:    Union[str, Any]=0.0_2						,						_A				:    str=1e-12						,						_A				:    Optional[Any]=True						,						_A				:    int=128						,						_A				:    int=0						,						**_A				:    Union[str, Any]						,						):


          '''simple docstring'''


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

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







'''simple docstring'''

from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
      if not (is_transformers_available() and is_torch_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import (
          ImageTextPipelineOutput,
          UniDiffuserPipeline,
      )
else:
      from .modeling_text_decoder import UniDiffuserTextDecoder
      from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
      from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline



