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作者你好,我使用你的vitb_256_mae_ce_32x4_got10k_ep100.yaml模型训练got10k,我的配置是单卡3090,训练过程中报出警告,UserWarning: An output with one or more elements was resized since it had shape [6291456], which does not match the required output shape [1, 32, 3, 256, 256]. This behavior is deprecated, and in a future PyTorch release outputs will not be resized unless they have zero elements. You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0). (Triggered internally at ../aten/src/ATen/native/Resize.cpp:17.) return torch.stack(batch, 1, out=out);同样的数据我用vitb_256_mae_32x4_ep300.yaml,屏蔽其他几个数据集,只使用got10k,可以正常训练,作者这两个数据集有什么差别吗,- GOT10K_train_full和 - GOT10K_vottrain的区别吗
The text was updated successfully, but these errors were encountered:
作者你好,我使用你的vitb_256_mae_ce_32x4_got10k_ep100.yaml模型训练got10k,我的配置是单卡3090,训练过程中报出警告,UserWarning: An output with one or more elements was resized since it had shape [6291456], which does not match the required output shape [1, 32, 3, 256, 256]. This behavior is deprecated, and in a future PyTorch release outputs will not be resized unless they have zero elements. You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0). (Triggered internally at ../aten/src/ATen/native/Resize.cpp:17.) return torch.stack(batch, 1, out=out);同样的数据我用vitb_256_mae_32x4_ep300.yaml,屏蔽其他几个数据集,只使用got10k,可以正常训练,作者这两个数据集有什么差别吗,- GOT10K_train_full和 - GOT10K_vottrain的区别吗
The text was updated successfully, but these errors were encountered: