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


__A				=logging.get_logger(__name__)

__A				={
    '''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json''',
    '''studio-ousia/luke-large''': '''https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json''',
}




class     _SCREAMING_SNAKE_CASE     (      snake_case_						):
	lowerCAmelCase__         = 'luke'



	def __init__(    self						,  lowercase=50267						,  lowercase=500000						,  lowercase=768						,  lowercase=256						,  lowercase=12						,  lowercase=12						,  lowercase=3072						,  lowercase="gelu"						,  lowercase=0.1						,  lowercase=0.1						,  lowercase=512						,  lowercase=2						,  lowercase=0.0_2						,  lowercase=1e-12						,  lowercase=True						,  lowercase=None						,  lowercase=1						,  lowercase=0						,  lowercase=2						,  **lowercase						,  )				->       Any:
					super().__init__(pad_token_id=lowercase						,  bos_token_id=lowercase						,  eos_token_id=lowercase						,  **lowercase )

					lowerCamelCase_						=			vocab_size
					lowerCamelCase_						=			entity_vocab_size
					lowerCamelCase_						=			hidden_size
					lowerCamelCase_						=			entity_emb_size
					lowerCamelCase_						=			num_hidden_layers
					lowerCamelCase_						=			num_attention_heads
					lowerCamelCase_						=			hidden_act
					lowerCamelCase_						=			intermediate_size
					lowerCamelCase_						=			hidden_dropout_prob
					lowerCamelCase_						=			attention_probs_dropout_prob
					lowerCamelCase_						=			max_position_embeddings
					lowerCamelCase_						=			type_vocab_size
					lowerCamelCase_						=			initializer_range
					lowerCamelCase_						=			layer_norm_eps
					lowerCamelCase_						=			use_entity_aware_attention
					lowerCamelCase_						=			classifier_dropout




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A				={'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A				=[
			    '''WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''WavLMForAudioFrameClassification''',
			    '''WavLMForCTC''',
			    '''WavLMForSequenceClassification''',
			    '''WavLMForXVector''',
			    '''WavLMModel''',
			    '''WavLMPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_wavlm import (
						    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    WavLMForAudioFrameClassification,
						    WavLMForCTC,
						    WavLMForSequenceClassification,
						    WavLMForXVector,
						    WavLMModel,
						    WavLMPreTrainedModel,
						)

else:
			import sys

			__A				=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


