


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


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

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






class _lowerCamelCase(		_a  ):
       lowercase_					:      Optional[int]       					=     """swin2sr"""

       lowercase_					:      List[Any]       					=     {
           """hidden_size""": """embed_dim""",
           """num_attention_heads""": """num_heads""",
           """num_hidden_layers""": """num_layers""",
       }
       def __init__(   self, lowerCamelCase=64, lowerCamelCase=1, lowerCamelCase=3, lowerCamelCase=1_80, lowerCamelCase=[6, 6, 6, 6, 6, 6], lowerCamelCase=[6, 6, 6, 6, 6, 6], lowerCamelCase=8, lowerCamelCase=2.0, lowerCamelCase=True, lowerCamelCase=0.0, lowerCamelCase=0.0, lowerCamelCase=0.1, lowerCamelCase="gelu", lowerCamelCase=False, lowerCamelCase=0.0_2, lowerCamelCase=1E-5, lowerCamelCase=2, lowerCamelCase=1.0, lowerCamelCase="1conv", lowerCamelCase="pixelshuffle", **lowerCamelCase, )			->  List[Any]:




           """simple docstring"""

           super().__init__(**lowerCamelCase)

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






from __future__ import annotations

import numpy as np



def 							UpperCamelCase_( lowerCamelCase_					)       ->		Optional[int]:
    return np.maximum(0				,					lowerCamelCase_					)


if __name__ == "__main__":
 print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]


