from typing import List, Union

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


lowerCAmelCase__	:  List[Any]						=  logging.get_logger(__name__)

lowerCAmelCase__	:  Dict						=  {
    '''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 					__snake_case    (     _lowerCamelCase      ):
					__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       ,			__UpperCamelCase=50265       ,			__UpperCamelCase=16384       ,			__UpperCamelCase=1024       ,			__UpperCamelCase=12       ,			__UpperCamelCase=4096       ,			__UpperCamelCase=16       ,			__UpperCamelCase=12       ,			__UpperCamelCase=4096       ,			__UpperCamelCase=16       ,			__UpperCamelCase=0.0       ,			__UpperCamelCase=0.0       ,			__UpperCamelCase=True       ,			__UpperCamelCase=True       ,			__UpperCamelCase="gelu"       ,			__UpperCamelCase=1024       ,			__UpperCamelCase=0.1       ,			__UpperCamelCase=0.0       ,			__UpperCamelCase=0.0       ,			__UpperCamelCase=0.0_2       ,			__UpperCamelCase=2       ,			__UpperCamelCase=0.0       ,			__UpperCamelCase=1       ,			__UpperCamelCase=0       ,			__UpperCamelCase=2       ,			__UpperCamelCase = 512       ,			**__UpperCamelCase       ,			)	->    Dict:



									'''simple docstring'''







									snake_case__   :      Tuple   				= vocab_size
									snake_case__   :      int   				= max_encoder_position_embeddings
									snake_case__   :      Dict   				= max_decoder_position_embeddings
									snake_case__   :      List[Any]   				= d_model
									snake_case__   :      Any   				= encoder_ffn_dim
									snake_case__   :      int   				= encoder_layers
									snake_case__   :      List[Any]   				= encoder_attention_heads
									snake_case__   :      Tuple   				= decoder_ffn_dim
									snake_case__   :      Union[str, Any]   				= decoder_layers
									snake_case__   :      str   				= decoder_attention_heads
									snake_case__   :      Optional[Any]   				= dropout
									snake_case__   :      Any   				= attention_dropout
									snake_case__   :      int   				= activation_dropout
									snake_case__   :      List[Any]   				= activation_function
									snake_case__   :      Optional[int]   				= init_std
									snake_case__   :      str   				= encoder_layerdrop
									snake_case__   :      Any   				= decoder_layerdrop
									snake_case__   :      int   				= classifier_dropout
									snake_case__   :      Optional[int]   				= use_cache
									snake_case__   :      int   				= encoder_layers
									snake_case__   :      Optional[int]   				= 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_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase__	:  int						=  {
    '''configuration_switch_transformers''': [
        '''SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SwitchTransformersConfig''',
        '''SwitchTransformersOnnxConfig''',
    ]
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__	:  List[Any]						=  [
				    '''SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''SwitchTransformersEncoderModel''',
				    '''SwitchTransformersForConditionalGeneration''',
				    '''SwitchTransformersModel''',
				    '''SwitchTransformersPreTrainedModel''',
				    '''SwitchTransformersTop1Router''',
				    '''SwitchTransformersSparseMLP''',
				]


if TYPE_CHECKING:
				from .configuration_switch_transformers import (
				    SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    SwitchTransformersConfig,
				    SwitchTransformersOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_switch_transformers import (
								    SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SwitchTransformersEncoderModel,
								    SwitchTransformersForConditionalGeneration,
								    SwitchTransformersModel,
								    SwitchTransformersPreTrainedModel,
								    SwitchTransformersSparseMLP,
								    SwitchTransformersTopaRouter,
								)


else:
				import sys

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


