




"""simple docstring"""







from ... import PretrainedConfig


a      =							{
    'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}






class       SCREAMING_SNAKE_CASE__					(					_a					):
						_a    						=						NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
						_a    						=						'nezha'


						def __init__(							self				:			Optional[int]						,						lowerCAmelCase				:			Any=2_1128						,						lowerCAmelCase				:			Optional[Any]=768						,						lowerCAmelCase				:			List[str]=12						,						lowerCAmelCase				:			str=12						,						lowerCAmelCase				:			List[Any]=3072						,						lowerCAmelCase				:			List[str]="gelu"						,						lowerCAmelCase				:			List[Any]=0.1						,						lowerCAmelCase				:			List[str]=0.1						,						lowerCAmelCase				:			Optional[int]=512						,						lowerCAmelCase				:			Optional[Any]=64						,						lowerCAmelCase				:			List[Any]=2						,						lowerCAmelCase				:			Optional[Any]=0.02						,						lowerCAmelCase				:			Tuple=1e-12						,						lowerCAmelCase				:			Any=0.1						,						lowerCAmelCase				:			Tuple=0						,						lowerCAmelCase				:			int=2						,						lowerCAmelCase				:			List[Any]=3						,						lowerCAmelCase				:			List[str]=True						,						**lowerCAmelCase				:			Optional[Any]						,						):
										super().__init__(pad_token_id=lowerCAmelCase						,						bos_token_id=lowerCAmelCase						,						eos_token_id=lowerCAmelCase						,						**lowerCAmelCase					)

										lowerCAmelCase  =				vocab_size
										lowerCAmelCase  =				hidden_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  =				max_relative_position
										lowerCAmelCase  =				type_vocab_size
										lowerCAmelCase  =				initializer_range
										lowerCAmelCase  =				layer_norm_eps
										lowerCAmelCase  =				classifier_dropout
										lowerCAmelCase  =				use_cache











"""simple docstring"""







from typing import TYPE_CHECKING

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


a      =							{
    'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
    'tokenization_biogpt': ['BioGptTokenizer'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a      =							[
		    'BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'BioGptForCausalLM',
		    'BioGptForTokenClassification',
		    'BioGptForSequenceClassification',
		    'BioGptModel',
		    'BioGptPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
		from .tokenization_biogpt import BioGptTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_biogpt import (
				    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BioGptForCausalLM,
				    BioGptForSequenceClassification,
				    BioGptForTokenClassification,
				    BioGptModel,
				    BioGptPreTrainedModel,
				)


else:
		import sys

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





