o ߥiw@spddlZddlmZddlmmZGdddejZGdddejZ   dd d Z d d Z dddZ dS)Ncs*eZdZdZdfdd ZddZZS) ResidualBlockNoBNa?Residual block without BN. It has a style of: :: ---Conv-ReLU-Conv-+- |________________| Args: mid_channels (int): Channel number of intermediate features. Default: 64. res_scale (float): Used to scale the residual before addition. Default: 1.0. @?csRt||_tj||ddddd|_tj||ddddd|_tjdd|_dS)NT)bias)inplace) super__init__ res_scalennConv2dconv1conv2ReLUrelu)self mid_channelsr  __class__f/home/ubuntu/.local/lib/python3.10/site-packages/modelscope/models/cv/video_super_resolution/common.pyr s zResidualBlockNoBN.__init__cCs(|}||||}|||jS)zForward function. Args: x (Tensor): Input tensor with shape (n, c, h, w). Returns: Tensor: Forward results. )rrrr )rxidentityoutrrrforwardszResidualBlockNoBN.forward)rr__name__ __module__ __qualname____doc__r r __classcell__rrrrr s rcs(eZdZdZfddZddZZS)PixelShufflePacka=Pixel Shuffle upsample layer. Args: in_channels (int): Number of input channels. out_channels (int): Number of output channels. scale_factor (int): Upsample ratio. upsample_kernel (int): Kernel size of Conv layer to expand channels. Returns: Upsampled feature map. csRt||_||_||_||_tj|j|j|||j|jddd|_dS)Nr)padding) r r in_channels out_channels scale_factorupsample_kernelr r upsample_conv)rr%r&r'r(rrrr 7s    zPixelShufflePack.__init__cCs||}t||j}|S)zForward function for PixelShufflePack. Args: x (Tensor): Input tensor with shape (n, c, h, w). Returns: Tensor: Forward results. )r)F pixel_shuffler')rrrrrrDs zPixelShufflePack.forwardrrrrrr",s  r"bilinearzerosTc Cs@|dd|ddkr'td|ddd|ddd|\}}}}|j}ttjd|||jd tjd|||jd \} } t| | fd } d | _| |} d | dddddddft |ddd } d | dddddddft |ddd }tj| |fdd} t j || |||d}|S)aWarp an image or a feature map with optical flow. Args: x (Tensor): Tensor with size (n, c, h, w). flow (Tensor): Tensor with size (n, h, w, 2). The last dimension is a two-channel, denoting the width and height relative offsets. Note that the values are not normalized to [-1, 1]. interpolation (str): Interpolation mode: 'nearest' or 'bilinear'. Default: 'bilinear'. padding_mode (str): Padding mode: 'zeros' or 'border' or 'reflection'. Default: 'zeros'. align_corners (bool): Whether align corners. Default: True. Returns: Tensor: Warped image or feature map. NrrzThe spatial sizes of input (z ) and flow (z) are not the same.r)devicedtyper#Fg@r)dim)mode padding_mode align_corners) size ValueErrorr/torchmeshgridaranger0stack requires_gradmaxr* grid_sample)rflow interpolationr3r4_hwr/grid_ygrid_xgrid grid_flow grid_flow_x grid_flow_youtputrrr flow_warpPs0  22rJcKs0g}t|D] }||di|qtj|S)zMake layers by stacking the same blocks. Args: block (nn.module): nn.module class for basic block. num_blocks (int): number of blocks. Returns: nn.Sequential: Stacked blocks in nn.Sequential. Nr)rangeappendr Sequential)block num_blockskwarglayersr@rrr make_layer}s  rR-q=cCst||d|S)Nr#)r7sqrt)predtargetepsrrrcharbonnier_losssrX)r,r-T)rS) r7torch.nnr torch.nn.functional functionalr*Modulerr"rJrRrXrrrrs "& -