a  dl= @sRddlZddlZddlZddlmZddlmZddlmZddlm Z ddl m Z m Z edZedkrdd lmZejeZed ejed d ejed d ejed dgdZn$zddlmZWneyYn0GdddeZGdddeZejZejZGdddejZ Gddde Z!GdddejZ"Gddde"Z#dS)N)nn)Function)once_differentiable) functional)_pair_single BASICSR_JITTrue)load deform_convsrczdeform_conv_ext.cppzdeform_conv_cuda.cppzdeform_conv_cuda_kernel.cu)sources)deform_conv_extc@s6eZdZed ddZeeddZedd Zd S) DeformConvFunctionrr@c Cs@|dur(|dkr(td|dt||_t||_t||_||_||_| |_| |||| t |||j|j|j} | d| dg|_ |jstnt|j|jd} |jd| dksJdt|||| |j d|j d|d|d|jd|jd|jd|jd|jd|jd|j|j| | S) Nz!Expected 4D tensor as input, got zD tensor instead.r!im2col step must divide batchsizer)dim ValueErrorrstridepaddingdilationgroupsdeformable_groups im2col_stepsave_for_backward new_emptyr _output_sizebufs_is_cudaNotImplementedErrorminshaperZdeform_conv_forwardsize) ctxinputoffsetweightrrrrrroutputcur_im2col_stepr-d/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/basicsr/ops/dcn/deform_conv.pyforward#s,     zDeformConvFunction.forwardc Csv|j\}}}d}}}|js&tntz1DeformConvFunction._output_size..z0convolution input is too small (output would be x))r&rangerallmaprjoinstr) r(r*rrrZchannelsZ output_sizedZin_sizepadkernelZstride_r-r-r.r js  zDeformConvFunction._output_sizeN)rrrrrr)__name__ __module__ __qualname__ staticmethodr/rr7r r-r-r-r.r!s % rc@s6eZdZed ddZeeddZedd ZdS) ModulatedDeformConvFunctionNrrc Cs||_||_||_| |_| |_|du|_|js8|d}|jsBt|j sZ|j sZ|j sZ|j rl| ||||||t |||} |d|dg|_ t||||j d||| |j d|jd|jd|j|j|j|j|j|j|j|j|j| S)Nrrrr)rrrrr with_biasrr"r#Z requires_gradrrI _infer_shape_bufsrZmodulated_deform_conv_forwardr%) r'r(r)maskr*biasrrrrrr+r-r-r.r/{s(    z#ModulatedDeformConvFunction.forwardc Cs|js t|j\}}}}}t|}t|}t|} t|} t|} t||||jd|||jd|| | || ||jd|jd|j |j |j |j |j |j |j |j |j|jsd} ||| | | dddddf S)Nrrrr)r"r#r0r1r2rZmodulated_deform_conv_backwardrLr%rrrrrrJ) r'r3r(r)rMr*rNr4r5Z grad_maskr6Z grad_biasr-r-r.r7s"       z$ModulatedDeformConvFunction.backwardc Cs|d}|d}|jdd\}}|jdd\}}|d|j|j|dd|jd} |d|j|j|dd|jd} ||| | fS)Nrrrr)r&r%rrr) r'r(r*nZ channels_outheightwidthZkernel_hZkernel_wZ height_outZ width_outr-r-r.rKs  **z(ModulatedDeformConvFunction._infer_shape)Nrrrrr)rErFrGrHr/rr7rKr-r-r-r.rIys  rIcs.eZdZd fdd ZddZdd ZZS) DeformConvrrFc stt|| rJ||dks6Jd|d|||dksVJd|d|||_||_t||_t||_t||_t||_ ||_ ||_ d|_ t d|_ttj|||j g|jR|_|dS)Nrz in_channels z is not divisible by groups z out_channels F)superrR__init__ in_channels out_channelsr kernel_sizerrrrr transposedroutput_paddingr Parameterr1Tensorr*reset_parameters selfrUrVrWrrrrrrN __class__r-r.rTs        $zDeformConv.__init__cCs>|j}|jD] }||9}q dt|}|jj| |dSNg?)rUrWmathsqrtr*datauniform_r^rOkZstdvr-r-r.r\s   zDeformConv.reset_parametersc Cs|d|jdkp&|d|jdk}|rt|jd|dd}t|jd|dd}t|d|d|fdd}t|d|d|fdd}t|||j|j|j |j |j |j }|r|ddddd|d|d|d|f}|S)NrrrrZconstant) r&rWmaxFrC contiguousr r*rrrrr)r^r;r)Z input_padZpad_hZpad_woutr-r-r.r/s(8zDeformConv.forward)rrrrrF)rErFrGrTr\r/ __classcell__r-r-r_r.rRs rRcs4eZdZdZdZfddZddZddZZS) DeformConvPackaiA Deformable Conv Encapsulation that acts as normal Conv layers. Args: in_channels (int): Same as nn.Conv2d. out_channels (int): Same as nn.Conv2d. kernel_size (int or tuple[int]): Same as nn.Conv2d. stride (int or tuple[int]): Same as nn.Conv2d. padding (int or tuple[int]): Same as nn.Conv2d. dilation (int or tuple[int]): Same as nn.Conv2d. groups (int): Same as nn.Conv2d. bias (bool or str): If specified as `auto`, it will be decided by the norm_cfg. 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Args: in_channels (int): Same as nn.Conv2d. out_channels (int): Same as nn.Conv2d. kernel_size (int or tuple[int]): Same as nn.Conv2d. stride (int or tuple[int]): Same as nn.Conv2d. padding (int or tuple[int]): Same as nn.Conv2d. dilation (int or tuple[int]): Same as nn.Conv2d. groups (int): Same as nn.Conv2d. bias (bool or str): If specified as `auto`, it will be decided by the norm_cfg. 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