




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


_snake_case										=       logging.get_logger(__name__)

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







class 						lowercase							(   lowerCAmelCase__		):
     _a							 =						"""swin2sr"""

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

     def __init__(  self		,     _a=64		,     _a=1		,     _a=3		,     _a=180		,     _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		,     )						->							List[str]:
           super().__init__(**__a				)

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





"""simple docstring"""


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			if not isinstance(_UpperCamelCase    , _UpperCamelCase      ):
						raise ValueError("iterations must be defined as integers"      )
			if not isinstance(_UpperCamelCase    , _UpperCamelCase      ) or not number >= 1:
						raise ValueError(
						    "starting number must be\n                         and integer and be more than 0"      )
			if not iterations >= 1:
						raise ValueError("Iterations must be done more than 0 times to play FizzBuzz"      )

			__lowerCAmelCase				    =			""
			while number <= iterations:
						if number % 3 == 0:
									out += "Fizz"
						if number % 5 == 0:
									out += "Buzz"
						if 0 not in (number % 3, number % 5):
									out += str(_UpperCamelCase      )

						# print(out)
						number += 1
						out += " "
			return out


if __name__ == "__main__":
	import doctest

	doctest.testmod()




