
'''simple docstring'''





from typing import List, Union

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


a__		: Dict  							=							logging.get_logger(__name__)

a__		: Optional[int]  							=							{
    "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__	(     snake_case__):
 UpperCAmelCase__     :     Union[str, Any]    					=       """led"""
 UpperCAmelCase__     :     str    					=       {
     """num_attention_heads""": """encoder_attention_heads""",
     """hidden_size""": """d_model""",
     """attention_probs_dropout_prob""": """attention_dropout""",
     """initializer_range""": """init_std""",
 }






 def __init__(      self	:Union[str, Any]						,					_A	:str=50_265						,					_A	:Tuple=16_384						,					_A	:Dict=1_024						,					_A	:Dict=12						,					_A	:Tuple=4_096						,					_A	:int=16						,					_A	:Dict=12						,					_A	:Tuple=4_096						,					_A	:int=16						,					_A	:str=0.0						,					_A	:List[Any]=0.0						,					_A	:Tuple=True						,					_A	:Any=True						,					_A	:Optional[Any]="gelu"						,					_A	:Optional[Any]=1_024						,					_A	:int=0.1						,					_A	:Optional[int]=0.0						,					_A	:str=0.0						,					_A	:Optional[Any]=0.02						,					_A	:Dict=2						,					_A	:Optional[Any]=0.0						,					_A	:Union[str, Any]=1						,					_A	:List[str]=0						,					_A	:Dict=2						,					_A	:Optional[int] = 512						,					**_A	:Dict						,					)					->      str:







       '''simple docstring'''



       __A													=      vocab_size
       __A													=      max_encoder_position_embeddings
       __A													=      max_decoder_position_embeddings
       __A													=      d_model
       __A													=      encoder_ffn_dim
       __A													=      encoder_layers
       __A													=      encoder_attention_heads
       __A													=      decoder_ffn_dim
       __A													=      decoder_layers
       __A													=      decoder_attention_heads
       __A													=      dropout
       __A													=      attention_dropout
       __A													=      activation_dropout
       __A													=      activation_function
       __A													=      init_std
       __A													=      encoder_layerdrop
       __A													=      decoder_layerdrop
       __A													=      classifier_dropout
       __A													=      use_cache
       __A													=      encoder_layers
       __A													=      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						,					)












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__            =     {
    """configuration_marian""": ["""MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarianConfig""", """MarianOnnxConfig"""],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""MarianTokenizer"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     [
					    """MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MarianForCausalLM""",
					    """MarianModel""",
					    """MarianMTModel""",
					    """MarianPreTrainedModel""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""TFMarianModel""", """TFMarianMTModel""", """TFMarianPreTrainedModel"""]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""FlaxMarianModel""", """FlaxMarianMTModel""", """FlaxMarianPreTrainedModel"""]

if TYPE_CHECKING:
					from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_marian import MarianTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_marian import (
										    MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MarianForCausalLM,
										    MarianModel,
										    MarianMTModel,
										    MarianPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
					import sys

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




