U Mh @sddlmZddlZddlmZmZmZddlZddddgZedd d Z ed d d Z ddddddddZ ddddddddddd ddZ d dd dddZ dddddddddddZdS)) annotationsN)OptionalTupleTypeVarfuse_conv_bn_evalfuse_conv_bn_weightsfuse_linear_bn_evalfuse_linear_bn_weightsConvTztorch.nn.modules.conv._ConvNd)boundLinearTztorch.nn.LinearFz%torch.nn.modules.batchnorm._BatchNormbool)convbn transposereturnc Csf|js |jrtdt|}|jdk r2|jdk s6tt|j|j|j|j|j |j|j|\|_|_|S)a+Fuse a convolutional module and a BatchNorm module into a single, new convolutional module. Args: conv (torch.nn.modules.conv._ConvNd): A convolutional module. bn (torch.nn.modules.batchnorm._BatchNorm): A BatchNorm module. transpose (bool, optional): If True, transpose the convolutional weight. Defaults to False. Returns: torch.nn.modules.conv._ConvNd: The fused convolutional module. .. note:: Both ``conv`` and ``bn`` must be in eval mode, and ``bn`` must have its running buffers computed. Fusion only for eval!N) trainingAssertionErrorcopydeepcopy running_mean running_varrweightbiaseps)rrrZ fused_convrG/var/www/html/venv/lib/python3.8/site-packages/torch/nn/utils/fusion.pyr s  z torch.TensorzOptional[torch.Tensor]floatz-Tuple[torch.nn.Parameter, torch.nn.Parameter]) conv_wconv_bbn_rmbn_rvbn_epsbn_wbn_brrcCs|j}|dk r|jn|} |dkr*t|}|dkrs     /%