


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


__UpperCAmelCase       :       str       	= logging.get_logger(__name__)

__UpperCAmelCase       :       Dict       	= {
    '''tau/splinter-base''': '''https://huggingface.co/tau/splinter-base/resolve/main/config.json''',
    '''tau/splinter-base-qass''': '''https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json''',
    '''tau/splinter-large''': '''https://huggingface.co/tau/splinter-large/resolve/main/config.json''',
    '''tau/splinter-large-qass''': '''https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json''',
    # See all Splinter models at https://huggingface.co/models?filter=splinter
}



class       UpperCAmelCase_		(							a__):
       '''simple docstring'''
       __UpperCamelCase					:   List[Any]							=    "splinter"






       def __init__(   self       ,    __SCREAMING_SNAKE_CASE=30_522       ,    __SCREAMING_SNAKE_CASE=768       ,    __SCREAMING_SNAKE_CASE=12       ,    __SCREAMING_SNAKE_CASE=12       ,    __SCREAMING_SNAKE_CASE=3_072       ,    __SCREAMING_SNAKE_CASE="gelu"       ,    __SCREAMING_SNAKE_CASE=0.1       ,    __SCREAMING_SNAKE_CASE=0.1       ,    __SCREAMING_SNAKE_CASE=512       ,    __SCREAMING_SNAKE_CASE=2       ,    __SCREAMING_SNAKE_CASE=0.02       ,    __SCREAMING_SNAKE_CASE=1e-12       ,    __SCREAMING_SNAKE_CASE=True       ,    __SCREAMING_SNAKE_CASE=0       ,    __SCREAMING_SNAKE_CASE=104       ,    **__SCREAMING_SNAKE_CASE       ,    ):




              """simple docstring"""




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

              UpperCamelCase			:		List[str]      		=						vocab_size
              UpperCamelCase			:		Tuple      		=						max_position_embeddings
              UpperCamelCase			:		List[str]      		=						hidden_size
              UpperCamelCase			:		Dict      		=						num_hidden_layers
              UpperCamelCase			:		Dict      		=						num_attention_heads
              UpperCamelCase			:		str      		=						intermediate_size
              UpperCamelCase			:		Dict      		=						hidden_act
              UpperCamelCase			:		Dict      		=						hidden_dropout_prob
              UpperCamelCase			:		List[str]      		=						attention_probs_dropout_prob
              UpperCamelCase			:		str      		=						initializer_range
              UpperCamelCase			:		Tuple      		=						type_vocab_size
              UpperCamelCase			:		Dict      		=						layer_norm_eps
              UpperCamelCase			:		List[str]      		=						use_cache
              UpperCamelCase			:		Tuple      		=						question_token_id








"""simple docstring"""
from typing import TYPE_CHECKING

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


__UpperCamelCase			:		List[Any]		    =   {'''configuration_yoso''': ['''YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YosoConfig''']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase			:		Dict		    =   [
           '''YOSO_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''YosoForMaskedLM''',
           '''YosoForMultipleChoice''',
           '''YosoForQuestionAnswering''',
           '''YosoForSequenceClassification''',
           '''YosoForTokenClassification''',
           '''YosoLayer''',
           '''YosoModel''',
           '''YosoPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_yoso import (
                  YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
                  YosoForMaskedLM,
                  YosoForMultipleChoice,
                  YosoForQuestionAnswering,
                  YosoForSequenceClassification,
                  YosoForTokenClassification,
                  YosoLayer,
                  YosoModel,
                  YosoPreTrainedModel,
              )


else:
       import sys

       __UpperCamelCase			:		Any		    =   _LazyModule(__name__, globals()['''__file__'''], _import_structure)





