


from typing import TYPE_CHECKING

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


__snake_case            =   {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__snake_case            =   [
			    "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "SwinForImageClassification",
			    "SwinForMaskedImageModeling",
			    "SwinModel",
			    "SwinPreTrainedModel",
			    "SwinBackbone",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__snake_case            =   [
			    "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "TFSwinForImageClassification",
			    "TFSwinForMaskedImageModeling",
			    "TFSwinModel",
			    "TFSwinPreTrainedModel",
			]

if TYPE_CHECKING:
			from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swin import (
						    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwinBackbone,
						    SwinForImageClassification,
						    SwinForMaskedImageModeling,
						    SwinModel,
						    SwinPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_swin import (
						    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFSwinForImageClassification,
						    TFSwinForMaskedImageModeling,
						    TFSwinModel,
						    TFSwinPreTrainedModel,
						)

else:
			import sys

			__snake_case            =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








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


__snake_case            =   logging.get_logger(__name__)

__snake_case            =   {
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}




class    UpperCAmelCase					(       __snake_case    ):
			lowercase						= """lilt"""




			def __init__(						self							:		Tuple       ,       __magic_name__							:		Tuple=3_0_5_2_2       ,       __magic_name__							:		List[str]=7_6_8       ,       __magic_name__							:		Optional[Any]=1_2       ,       __magic_name__							:		str=1_2       ,       __magic_name__							:		Tuple=3_0_7_2       ,       __magic_name__							:		List[Any]="gelu"       ,       __magic_name__							:		Dict=0.1       ,       __magic_name__							:		str=0.1       ,       __magic_name__							:		Dict=5_1_2       ,       __magic_name__							:		Any=2       ,       __magic_name__							:		Optional[int]=0.02       ,       __magic_name__							:		Optional[int]=1e-12       ,       __magic_name__							:		Optional[int]=0       ,       __magic_name__							:		List[str]="absolute"       ,       __magic_name__							:		List[Any]=None       ,       __magic_name__							:		str=4       ,       __magic_name__							:		Any=1_0_2_4       ,       **__magic_name__							:		List[str]       ,       ):







						"""simple docstring"""







						super().__init__(pad_token_id=__magic_name__       ,       **__magic_name__						)

						UpperCamelCase         =					vocab_size
						UpperCamelCase         =					hidden_size
						UpperCamelCase         =					num_hidden_layers
						UpperCamelCase         =					num_attention_heads
						UpperCamelCase         =					hidden_act
						UpperCamelCase         =					intermediate_size
						UpperCamelCase         =					hidden_dropout_prob
						UpperCamelCase         =					attention_probs_dropout_prob
						UpperCamelCase         =					max_position_embeddings
						UpperCamelCase         =					type_vocab_size
						UpperCamelCase         =					initializer_range
						UpperCamelCase         =					layer_norm_eps
						UpperCamelCase         =					position_embedding_type
						UpperCamelCase         =					classifier_dropout
						UpperCamelCase         =					channel_shrink_ratio
						UpperCamelCase         =					max_ad_position_embeddings




