ChengpengChen
commented
3 months ago you should use the 'state_dict' or 'state_dict_ema' in the pth file to initialize the model, that is
load_state_dict(torch.load(/mypath/repghostnet_1_0x_142M_74.22.pth.tar')['state_dict_ema']), or load_state_dict(torch.load(/mypath/repghostnet_1_0x_142M_74.22.pth.tar')['state_dict'])
LiYufengzz
When use load_state_dict(torch.load(/mypath/repghostnet_1_0x_142M_74.22.pth.tar'))，It shows Missing key(s) in state_dict:"conv_stem.weight", "bn1.weight", "bn1.bias", "bn1.running_mean", "bn1.running_var", "blocks.0.0.ghost1.primary_conv.0.weight", "blocks.0.0.ghost1.primary_conv.1.weight", "blocks.0.0.ghost1.primary_conv.1.bias", "blocks.0.0.ghost1.primary_conv.1.running_mean", "blocks.0.0.ghost1.primary_conv.1.running_var", "blocks.0.0.ghost1.cheap_operation.0.weight", "blocks.0.0.ghost1.cheap_operation.1.weight", "blocks.0.0.ghost1.cheap_operation.1.bias", "blocks.0.0.ghost1.cheap_operation.1.running_mean", "blocks.0.0.ghost1.cheap_operation.1.running_var", "blocks.0.0.ghost2.primary_conv.0.weight", "blocks.0.0.ghost2.primary_conv.1.weight", "blocks.0.0.ghost2.primary_conv.1.bias", "blocks.0.0.ghost2.primary_conv.1.running_mean", "blocks.0.0.ghost2.primary_conv.1.running_var", "blocks.0.0.ghost2.cheap_operation.0.weight", "blocks.0.0.ghost2.cheap_operation.1.weight", 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"blocks.1.0.ghost2.cheap_operation.0.weight", "blocks.1.0.ghost2.cheap_operation.1.weight", "blocks.1.0.ghost2.cheap_operation.1.bias", "blocks.1.0.ghost2.cheap_operation.1.running_mean", "blocks.1.0.ghost2.cheap_operation.1.running_var", "blocks.1.0.shortcut.0.weight", "blocks.1.0.shortcut.1.weight", "blocks.1.0.shortcut.1.bias", "blocks.1.0.shortcut.1.running_mean", "blocks.1.0.shortcut.1.running_var", "blocks.1.0.shortcut.2.weight", "blocks.1.0.shortcut.3.weight", "blocks.1.0.shortcut.3.bias", "blocks.1.0.shortcut.3.running_mean", "blocks.1.0.shortcut.3.running_var", "blocks.2.0.ghost1.primary_conv.0.weight", "blocks.2.0.ghost1.primary_conv.1.weight", "blocks.2.0.ghost1.primary_conv.1.bias", "blocks.2.0.ghost1.primary_conv.1.running_mean", "blocks.2.0.ghost1.primary_conv.1.running_var", "blocks.2.0.ghost1.cheap_operation.0.weight", "blocks.2.0.ghost1.cheap_operation.1.weight", "blocks.2.0.ghost1.cheap_operation.1.bias", "blocks.2.0.ghost1.cheap_operation.1.running_mean", 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"blocks.8.2.ghost2.primary_conv.0.weight", "blocks.8.2.ghost2.primary_conv.1.weight", "blocks.8.2.ghost2.primary_conv.1.bias", "blocks.8.2.ghost2.primary_conv.1.running_mean", "blocks.8.2.ghost2.primary_conv.1.running_var", "blocks.8.2.ghost2.cheap_operation.0.weight", "blocks.8.2.ghost2.cheap_operation.1.weight", "blocks.8.2.ghost2.cheap_operation.1.bias", "blocks.8.2.ghost2.cheap_operation.1.running_mean", "blocks.8.2.ghost2.cheap_operation.1.running_var", "blocks.8.3.ghost1.primary_conv.0.weight", "blocks.8.3.ghost1.primary_conv.1.weight", "blocks.8.3.ghost1.primary_conv.1.bias", "blocks.8.3.ghost1.primary_conv.1.running_mean", "blocks.8.3.ghost1.primary_conv.1.running_var", "blocks.8.3.ghost1.cheap_operation.0.weight", "blocks.8.3.ghost1.cheap_operation.1.weight", "blocks.8.3.ghost1.cheap_operation.1.bias", "blocks.8.3.ghost1.cheap_operation.1.running_mean", "blocks.8.3.ghost1.cheap_operation.1.running_var", "blocks.8.3.se.conv_reduce.weight", "blocks.8.3.se.conv_reduce.bias", "blocks.8.3.se.conv_expand.weight", "blocks.8.3.se.conv_expand.bias", "blocks.8.3.ghost2.primary_conv.0.weight", "blocks.8.3.ghost2.primary_conv.1.weight", "blocks.8.3.ghost2.primary_conv.1.bias", "blocks.8.3.ghost2.primary_conv.1.running_mean", "blocks.8.3.ghost2.primary_conv.1.running_var", "blocks.8.3.ghost2.cheap_operation.0.weight", "blocks.8.3.ghost2.cheap_operation.1.weight", "blocks.8.3.ghost2.cheap_operation.1.bias", "blocks.8.3.ghost2.cheap_operation.1.running_mean", "blocks.8.3.ghost2.cheap_operation.1.running_var", "blocks.9.0.conv.weight", "blocks.9.0.bn1.weight", "blocks.9.0.bn1.bias", "blocks.9.0.bn1.running_mean", "blocks.9.0.bn1.running_var", "conv_head.weight", "conv_head.bias", "classifier.weight", "classifier.bias". Unexpected key(s) in state_dict: "epoch", "arch", "state_dict", "optimizer", "version", "args", "amp_scaler", "state_dict_ema", "metric".