





from ... import PretrainedConfig


snake_case_							=			{
    '''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class        snake_case_		(			_a):
		lowerCamelCase    :Optional[int]						=     NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
		lowerCamelCase    :Union[str, Any]						=     "nezha"







		def __init__(		self			,     __lowercase=2_1_1_2_8			,     __lowercase=7_6_8			,     __lowercase=1_2			,     __lowercase=1_2			,     __lowercase=3_0_7_2			,     __lowercase="gelu"			,     __lowercase=0.1			,     __lowercase=0.1			,     __lowercase=5_1_2			,     __lowercase=6_4			,     __lowercase=2			,     __lowercase=0.0_2			,     __lowercase=1e-12			,     __lowercase=0.1			,     __lowercase=0			,     __lowercase=2			,     __lowercase=3			,     __lowercase=True			,     **__lowercase			,     )				->   Optional[int]:
				super().__init__(pad_token_id=_A			,     bos_token_id=_A			,     eos_token_id=_A			,     **_A   )

				lowerCamelCase   : Optional[Any]								=vocab_size
				lowerCamelCase   : Any								=hidden_size
				lowerCamelCase   : Optional[Any]								=num_hidden_layers
				lowerCamelCase   : Tuple								=num_attention_heads
				lowerCamelCase   : Any								=hidden_act
				lowerCamelCase   : str								=intermediate_size
				lowerCamelCase   : str								=hidden_dropout_prob
				lowerCamelCase   : Optional[Any]								=attention_probs_dropout_prob
				lowerCamelCase   : int								=max_position_embeddings
				lowerCamelCase   : Optional[Any]								=max_relative_position
				lowerCamelCase   : Tuple								=type_vocab_size
				lowerCamelCase   : Tuple								=initializer_range
				lowerCamelCase   : str								=layer_norm_eps
				lowerCamelCase   : Optional[int]								=classifier_dropout
				lowerCamelCase   : Any								=use_cache








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case_							=			{
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_							=			[
				    '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''InstructBlipQFormerModel''',
				    '''InstructBlipPreTrainedModel''',
				    '''InstructBlipForConditionalGeneration''',
				    '''InstructBlipVisionModel''',
				]

if TYPE_CHECKING:
				from .configuration_instructblip import (
				    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    InstructBlipConfig,
				    InstructBlipQFormerConfig,
				    InstructBlipVisionConfig,
				)
				from .processing_instructblip import InstructBlipProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_instructblip import (
								    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    InstructBlipForConditionalGeneration,
								    InstructBlipPreTrainedModel,
								    InstructBlipQFormerModel,
								    InstructBlipVisionModel,
								)

else:
				import sys

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

