






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


lowercase  :							Union[str, Any]			  =    logging.get_logger(__name__)

lowercase  :							Union[str, Any]			  =    {
    """Visual-Attention-Network/van-base""": (
        """https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"""
    ),
}




class 		UpperCAmelCase_						(	__UpperCAmelCase					):


						'''simple docstring'''




						A     :   Optional[int]						=					'van'






						def __init__(	self		,				_SCREAMING_SNAKE_CASE=224		,				_SCREAMING_SNAKE_CASE=3		,				_SCREAMING_SNAKE_CASE=[7, 3, 3, 3]		,				_SCREAMING_SNAKE_CASE=[4, 2, 2, 2]		,				_SCREAMING_SNAKE_CASE=[64, 128, 320, 512]		,				_SCREAMING_SNAKE_CASE=[3, 3, 12, 3]		,				_SCREAMING_SNAKE_CASE=[8, 8, 4, 4]		,				_SCREAMING_SNAKE_CASE="gelu"		,				_SCREAMING_SNAKE_CASE=0.02		,				_SCREAMING_SNAKE_CASE=1e-6		,				_SCREAMING_SNAKE_CASE=1e-2		,				_SCREAMING_SNAKE_CASE=0.0		,				_SCREAMING_SNAKE_CASE=0.0		,				**_SCREAMING_SNAKE_CASE		,				) ->				Dict:
								super().__init__(**_SCREAMING_SNAKE_CASE				)
								snake_case_				:							Union[str, Any]						 =       image_size
								snake_case_				:							Dict						 =       num_channels
								snake_case_				:							Optional[Any]						 =       patch_sizes
								snake_case_				:							Optional[Any]						 =       strides
								snake_case_				:							Any						 =       hidden_sizes
								snake_case_				:							Union[str, Any]						 =       depths
								snake_case_				:							str						 =       mlp_ratios
								snake_case_				:							List[str]						 =       hidden_act
								snake_case_				:							int						 =       initializer_range
								snake_case_				:							List[Any]						 =       layer_norm_eps
								snake_case_				:							int						 =       layer_scale_init_value
								snake_case_				:							Union[str, Any]						 =       drop_path_rate
								snake_case_				:							Tuple						 =       dropout_rate








from typing import TYPE_CHECKING

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


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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase  :							List[str]			  =    [
							    '''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

							lowercase  :							Tuple			  =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
