




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


UpperCAmelCase_    :					Optional[Any]					      =						logging.get_logger(__name__)

UpperCAmelCase_    :					Union[str, Any]					      =						{
    '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json''',
}





class       lowerCAmelCase				(	lowerCAmelCase__):
       __lowercase					: Optional[Any]	    =     '''mpnet'''


       def __init__(				self      ,					__SCREAMING_SNAKE_CASE=3_0527      ,					__SCREAMING_SNAKE_CASE=768      ,					__SCREAMING_SNAKE_CASE=12      ,					__SCREAMING_SNAKE_CASE=12      ,					__SCREAMING_SNAKE_CASE=3072      ,					__SCREAMING_SNAKE_CASE="gelu"      ,					__SCREAMING_SNAKE_CASE=0.1      ,					__SCREAMING_SNAKE_CASE=0.1      ,					__SCREAMING_SNAKE_CASE=512      ,					__SCREAMING_SNAKE_CASE=0.02      ,					__SCREAMING_SNAKE_CASE=1E-12      ,					__SCREAMING_SNAKE_CASE=32      ,					__SCREAMING_SNAKE_CASE=1      ,					__SCREAMING_SNAKE_CASE=0      ,					__SCREAMING_SNAKE_CASE=2      ,					**__SCREAMING_SNAKE_CASE      ,					) ->					Optional[Any]:



            '''simple docstring'''




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

            __snake_case         =					vocab_size
            __snake_case         =					hidden_size
            __snake_case         =					num_hidden_layers
            __snake_case         =					num_attention_heads
            __snake_case         =					hidden_act
            __snake_case         =					intermediate_size
            __snake_case         =					hidden_dropout_prob
            __snake_case         =					attention_probs_dropout_prob
            __snake_case         =					max_position_embeddings
            __snake_case         =					initializer_range
            __snake_case         =					layer_norm_eps
            __snake_case         =					relative_attention_num_buckets












'''simple docstring'''



from typing import TYPE_CHECKING

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


UpperCAmelCase_    :					Any					      =						{
    '''configuration_retribert''': ['''RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RetriBertConfig'''],
    '''tokenization_retribert''': ['''RetriBertTokenizer'''],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_    :					str					      =						['''RetriBertTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_    :					Optional[int]					      =						[
         '''RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''RetriBertModel''',
         '''RetriBertPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_retribert import RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RetriBertConfig
     from .tokenization_retribert import RetriBertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_retribert_fast import RetriBertTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_retribert import (
              RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              RetriBertModel,
              RetriBertPreTrainedModel,
          )

else:
     import sys

     UpperCAmelCase_    :					Any					      =						_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






