


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


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

UpperCamelCase			:					Tuple         =							{
    'uw-madison/yoso-4096': 'https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json',
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}

class      __snake_case				(   _lowerCamelCase):
					SCREAMING_SNAKE_CASE_		:       Any								=			"yoso"
					def __init__(						self       :						Union[str, Any]	,      _lowerCAmelCase       :						Optional[int]=5_0_2_6_5	,      _lowerCAmelCase       :						int=7_6_8	,      _lowerCAmelCase       :						Union[str, Any]=1_2	,      _lowerCAmelCase       :						Any=1_2	,      _lowerCAmelCase       :						int=3_0_7_2	,      _lowerCAmelCase       :						Dict="gelu"	,      _lowerCAmelCase       :						Dict=0.1	,      _lowerCAmelCase       :						List[Any]=0.1	,      _lowerCAmelCase       :						List[str]=4_0_9_6	,      _lowerCAmelCase       :						Optional[Any]=1	,      _lowerCAmelCase       :						Optional[Any]=0.02	,      _lowerCAmelCase       :						str=1E-1_2	,      _lowerCAmelCase       :						Any="absolute"	,      _lowerCAmelCase       :						str=True	,      _lowerCAmelCase       :						int=9	,      _lowerCAmelCase       :						Tuple=6_4	,      _lowerCAmelCase       :						Any=None	,      _lowerCAmelCase       :						int=True	,      _lowerCAmelCase       :						str=True	,      _lowerCAmelCase       :						Optional[Any]=1	,      _lowerCAmelCase       :						Optional[Any]=0	,      _lowerCAmelCase       :						List[Any]=2	,      **_lowerCAmelCase       :						List[str]	,      )							->					List[str]:



											'''simple docstring'''





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

											__magic_name__					=      vocab_size
											__magic_name__					=      max_position_embeddings
											__magic_name__					=      hidden_size
											__magic_name__					=      num_hidden_layers
											__magic_name__					=      num_attention_heads
											__magic_name__					=      intermediate_size
											__magic_name__					=      hidden_act
											__magic_name__					=      hidden_dropout_prob
											__magic_name__					=      attention_probs_dropout_prob
											__magic_name__					=      initializer_range
											__magic_name__					=      type_vocab_size
											__magic_name__					=      layer_norm_eps
											__magic_name__					=      position_embedding_type
											__magic_name__					=      use_expectation
											__magic_name__					=      hash_code_len
											__magic_name__					=      num_hash
											__magic_name__					=      conv_window
											__magic_name__					=      use_fast_hash
											__magic_name__					=      lsh_backward








from typing import TYPE_CHECKING

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


snake_case__   :				Tuple						=	{
    'configuration_realm': ['REALM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RealmConfig'],
    'tokenization_realm': ['RealmTokenizer'],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case__   :				Tuple						=	['RealmTokenizerFast']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case__   :				str						=	[
           'REALM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'RealmEmbedder',
           'RealmForOpenQA',
           'RealmKnowledgeAugEncoder',
           'RealmPreTrainedModel',
           'RealmReader',
           'RealmScorer',
           'load_tf_weights_in_realm',
       ]
       snake_case__   :				Any						=	['RealmRetriever']


if TYPE_CHECKING:
       from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
       from .tokenization_realm import RealmTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_realm import RealmTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_realm import (
                  REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  RealmEmbedder,
                  RealmForOpenQA,
                  RealmKnowledgeAugEncoder,
                  RealmPreTrainedModel,
                  RealmReader,
                  RealmScorer,
                  load_tf_weights_in_realm,
              )
              from .retrieval_realm import RealmRetriever


else:
       import sys

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





