a d @slUddlmZmZddlZddlmZddlmZiZee e fe d<ded<ded<Gd d d ej Z dS) )CallableDictN)KORNIA_CHECK_SHAPEurlszVhttps://github.com/yuruntian/SOSNet/raw/master/sosnet-weights/sosnet_32x32_liberty.pthlibzYhttps://github.com/yuruntian/SOSNet/raw/master/sosnet-weights/sosnet_32x32_hpatches_a.pthZhp_acsFeZdZdZdZd eddfdd Zd eje ejd d d Z Z S)SOSNeta128-dimensional SOSNet model definition for 32x32 patches. This is based on the original code from paper "SOSNet:Second Order Similarity Regularization for Local Descriptor Learning". Args: pretrained: Download and set pretrained weights to the model. Shape: - Input: :math:`(B, 1, 32, 32)` - Output: :math:`(B, 128)` Examples: >>> input = torch.rand(8, 1, 32, 32) >>> sosnet = SOSNet() >>> descs = sosnet(input) # 8x128 FN) pretrainedreturncsvtttjdddtjddddddtjdddttjddddddtjdddttjddddddd tjdddttjddddddtjdddttjdd ddddd tjd ddttjd d ddddtjd ddttd tjd d d dd tjd dd|_ ttj ddddd|_ |rjdd}t j jtd|d}|j|dd|dS)NF)Zaffiner) kernel_sizepaddingbias@)r Zstriderrg?)r rgp@g?g)alphabetakcSs|S)N)Zstoragelocrr^/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/kornia/feature/sosnet.py>z!SOSNet.__init__..r)Z map_locationT)strict)super__init__nnZ SequentialZInstanceNorm2dZConv2dZ BatchNorm2dZReLUZDropoutlayersZLocalResponseNorm desc_normtorchZhubZload_state_dict_from_urlrZload_state_dicteval)selfr Z storage_fcnZpretrained_dict __class__rrr!s@         zSOSNet.__init__绽|=)inputepsr cCs8t|gd||||}||dd}|S)N)B132r-r)rr"r!viewsize)r%r)r*descrrrrforwardDszSOSNet.forward)F)r() __name__ __module__ __qualname____doc__Z patch_sizeboolrr#ZTensorfloatr2 __classcell__rrr&rr s#r) typingrrr#Ztorch.nnr Zkornia.testingrrstr__annotations__Modulerrrrrs