





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


lowerCAmelCase							:       Tuple					 =	logging.get_logger(__name__)

lowerCAmelCase							:       Tuple					 =	{
    """microsoft/swinv2-tiny-patch4-window8-256""": (
        """https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"""
    ),
}





class 				a			(      __lowercase			):
				SCREAMING_SNAKE_CASE__     :   Union[str, Any]		      =     '''swinv2'''

				SCREAMING_SNAKE_CASE__     :   Optional[int]		      =     {
				    '''num_attention_heads''': '''num_heads''',
				    '''num_hidden_layers''': '''num_layers''',
				}






				def __init__(  self			, _lowerCAmelCase=224			, _lowerCAmelCase=4			, _lowerCAmelCase=3			, _lowerCAmelCase=96			, _lowerCAmelCase=[2, 2, 6, 2]			, _lowerCAmelCase=[3, 6, 12, 24]			, _lowerCAmelCase=7			, _lowerCAmelCase=4.0			, _lowerCAmelCase=True			, _lowerCAmelCase=0.0			, _lowerCAmelCase=0.0			, _lowerCAmelCase=0.1			, _lowerCAmelCase="gelu"			, _lowerCAmelCase=False			, _lowerCAmelCase=0.02			, _lowerCAmelCase=1e-5			, _lowerCAmelCase=32			, **_lowerCAmelCase			, ):

										"""simple docstring"""




										super().__init__(**_lowerCAmelCase					)

										__SCREAMING_SNAKE_CASE:				str           =   image_size
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   patch_size
										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   num_channels
										__SCREAMING_SNAKE_CASE:				Dict           =   embed_dim
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   depths
										__SCREAMING_SNAKE_CASE:				Tuple           =   len(_lowerCAmelCase					)
										__SCREAMING_SNAKE_CASE:				str           =   num_heads
										__SCREAMING_SNAKE_CASE:				str           =   window_size
										__SCREAMING_SNAKE_CASE:				str           =   mlp_ratio
										__SCREAMING_SNAKE_CASE:				List[Any]           =   qkv_bias
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   hidden_dropout_prob
										__SCREAMING_SNAKE_CASE:				Optional[int]           =   attention_probs_dropout_prob
										__SCREAMING_SNAKE_CASE:				Tuple           =   drop_path_rate
										__SCREAMING_SNAKE_CASE:				Optional[int]           =   hidden_act
										__SCREAMING_SNAKE_CASE:				Tuple           =   use_absolute_embeddings
										__SCREAMING_SNAKE_CASE:				Tuple           =   layer_norm_eps
										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   initializer_range
										__SCREAMING_SNAKE_CASE:				str           =   encoder_stride
										# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
										# this indicates the channel dimension after the last stage of the model
										__SCREAMING_SNAKE_CASE:				Any           =   int(embed_dim * 2 ** (len(_lowerCAmelCase					) - 1)					)
										__SCREAMING_SNAKE_CASE:				str           =   (0, 0, 0, 0)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase							:       str					 =	{
    """configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase							:       Optional[Any]					 =	[
							    """PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """PegasusXForConditionalGeneration""",
							    """PegasusXModel""",
							    """PegasusXPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_pegasus_x import (
														    PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
														    PegasusXForConditionalGeneration,
														    PegasusXModel,
														    PegasusXPreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase							:       str					 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



