



from typing import List, Union

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


_lowerCamelCase         =	logging.get_logger(__name__)

_lowerCamelCase         =	{
    """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    _SCREAMING_SNAKE_CASE						(UpperCamelCase			):
     lowerCAmelCase       =      """led"""
     lowerCAmelCase       =      {
         """num_attention_heads""": """encoder_attention_heads""",
         """hidden_size""": """d_model""",
         """attention_probs_dropout_prob""": """attention_dropout""",
         """initializer_range""": """init_std""",
     }





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

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













from typing import TYPE_CHECKING

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


UpperCamelCase__ :			Any       	=			{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__ :			Any       	=			["""SplinterTokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__ :			Union[str, Any]       	=			[
				    """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """SplinterForQuestionAnswering""",
				    """SplinterForPreTraining""",
				    """SplinterLayer""",
				    """SplinterModel""",
				    """SplinterPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
				from .tokenization_splinter import SplinterTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_splinter_fast import SplinterTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_splinter import (
								    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SplinterForPreTraining,
								    SplinterForQuestionAnswering,
								    SplinterLayer,
								    SplinterModel,
								    SplinterPreTrainedModel,
								)


else:
				import sys

				UpperCamelCase__ :			List[str]       	=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


