



"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_				= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_				= {
    """caidas/swin2sr-classicalsr-x2-64""": (
        """https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"""
    ),
}




class 			snake_case_						(						a_				):
							__lowerCAmelCase    					=					"swin2sr"

							__lowerCAmelCase    					=					{
							    "hidden_size": "embed_dim",
							    "num_attention_heads": "num_heads",
							    "num_hidden_layers": "num_layers",
							}






							def __init__(   self			,     a_=6_4			,     a_=1			,     a_=3			,     a_=1_8_0			,     a_=[6, 6, 6, 6, 6, 6]			,     a_=[6, 6, 6, 6, 6, 6]			,     a_=8			,     a_=2.0			,     a_=True			,     a_=0.0			,     a_=0.0			,     a_=0.1			,     a_="gelu"			,     a_=False			,     a_=0.02			,     a_=1e-5			,     a_=2			,     a_=1.0			,     a_="1conv"			,     a_="pixelshuffle"			,     **a_			,     ):
									super().__init__(**a_      )

									a_     :      int 						=     image_size
									a_     :      Union[str, Any] 						=     patch_size
									a_     :      Tuple 						=     num_channels
									a_     :      int 						=     embed_dim
									a_     :      Dict 						=     depths
									a_     :      Optional[int] 						=     len(a_      )
									a_     :      Union[str, Any] 						=     num_heads
									a_     :      int 						=     window_size
									a_     :      Dict 						=     mlp_ratio
									a_     :      List[str] 						=     qkv_bias
									a_     :      List[Any] 						=     hidden_dropout_prob
									a_     :      Union[str, Any] 						=     attention_probs_dropout_prob
									a_     :      str 						=     drop_path_rate
									a_     :      List[Any] 						=     hidden_act
									a_     :      Optional[Any] 						=     use_absolute_embeddings
									a_     :      Optional[int] 						=     layer_norm_eps
									a_     :      Optional[int] 						=     initializer_range
									a_     :      List[Any] 						=     upscale
									a_     :      List[Any] 						=     img_range
									a_     :      Any 						=     resi_connection
									a_     :      Union[str, Any] 						=     upsampler




"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_				= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_				= {
    """uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}




class 			snake_case_						(						a_				):
							__lowerCAmelCase    					=					"mra"






							def __init__(   self			,     a_=5_0_2_6_5			,     a_=7_6_8			,     a_=1_2			,     a_=1_2			,     a_=3_0_7_2			,     a_="gelu"			,     a_=0.1			,     a_=0.1			,     a_=5_1_2			,     a_=1			,     a_=0.02			,     a_=1e-5			,     a_="absolute"			,     a_=4			,     a_="full"			,     a_=0			,     a_=0			,     a_=1			,     a_=0			,     a_=2			,     **a_			,     ):
									super().__init__(pad_token_id=a_			,     bos_token_id=a_			,     eos_token_id=a_			,     **a_      )

									a_     :      Optional[int] 						=     vocab_size
									a_     :      Dict 						=     max_position_embeddings
									a_     :      str 						=     hidden_size
									a_     :      Optional[int] 						=     num_hidden_layers
									a_     :      List[Any] 						=     num_attention_heads
									a_     :      List[str] 						=     intermediate_size
									a_     :      Tuple 						=     hidden_act
									a_     :      List[Any] 						=     hidden_dropout_prob
									a_     :      List[str] 						=     attention_probs_dropout_prob
									a_     :      List[Any] 						=     initializer_range
									a_     :      Dict 						=     type_vocab_size
									a_     :      Union[str, Any] 						=     layer_norm_eps
									a_     :      List[str] 						=     position_embedding_type
									a_     :      Union[str, Any] 						=     block_per_row
									a_     :      Tuple 						=     approx_mode
									a_     :      Optional[Any] 						=     initial_prior_first_n_blocks
									a_     :      List[str] 						=     initial_prior_diagonal_n_blocks