"""simple docstring"""





from typing import List, Union

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


_UpperCamelCase       :						Any     =   logging.get_logger(__name__)

_UpperCamelCase       :						Optional[Any]     =   {
    "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/config.json",
    # See all LED models at https://huggingface.co/models?filter=led
}


class 					UpperCAmelCase_     (   _a):
      lowerCamelCase__		:   Optional[Any]			  =  "led"
      lowerCamelCase__		:   int			  =  {
          "num_attention_heads": "encoder_attention_heads",
          "hidden_size": "d_model",
          "attention_probs_dropout_prob": "attention_dropout",
          "initializer_range": "init_std",
      }


      def __init__(       self		,      a=5_0_2_6_5		,      a=1_6_3_8_4		,      a=1_0_2_4		,      a=1_2		,      a=4_0_9_6		,      a=1_6		,      a=1_2		,      a=4_0_9_6		,      a=1_6		,      a=0.0		,      a=0.0		,      a=True		,      a=True		,      a="gelu"		,      a=1_0_2_4		,      a=0.1		,      a=0.0		,      a=0.0		,      a=0.02		,      a=2		,      a=0.0		,      a=1		,      a=0		,      a=2		,      a = 5_1_2		,      **a		,      )	-> Any:
             lowercase__      :		Optional[int]          =     vocab_size
             lowercase__      :		Tuple          =     max_encoder_position_embeddings
             lowercase__      :		List[Any]          =     max_decoder_position_embeddings
             lowercase__      :		int          =     d_model
             lowercase__      :		Tuple          =     encoder_ffn_dim
             lowercase__      :		Optional[int]          =     encoder_layers
             lowercase__      :		Tuple          =     encoder_attention_heads
             lowercase__      :		Any          =     decoder_ffn_dim
             lowercase__      :		Any          =     decoder_layers
             lowercase__      :		Tuple          =     decoder_attention_heads
             lowercase__      :		Tuple          =     dropout
             lowercase__      :		List[Any]          =     attention_dropout
             lowercase__      :		str          =     activation_dropout
             lowercase__      :		Union[str, Any]          =     activation_function
             lowercase__      :		Union[str, Any]          =     init_std
             lowercase__      :		Tuple          =     encoder_layerdrop
             lowercase__      :		Any          =     decoder_layerdrop
             lowercase__      :		List[str]          =     classifier_dropout
             lowercase__      :		str          =     use_cache
             lowercase__      :		Optional[int]          =     encoder_layers
             lowercase__      :		Any          =     attention_window

             super().__init__(
                 pad_token_id=a		,      bos_token_id=a		,      eos_token_id=a		,      is_encoder_decoder=a		,      decoder_start_token_id=a		,      **a		,      )


"""simple docstring"""





from typing import TYPE_CHECKING

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


_UpperCamelCase       :						int     =   {
    "configuration_retribert": ["RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RetriBertConfig"],
    "tokenization_retribert": ["RetriBertTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase       :						Tuple     =   ["RetriBertTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase       :						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       :						Tuple     =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

