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| # loss = flow.mul(log_prob * -1, onehot_label).sum(dim=-1).mean() | ||
| loss = flow._C.softmax_cross_entropy(input, onehot_label.to(dtype=input.dtype)) | ||
| #loss = flow._C.softmax_cross_entropy(input, onehot_label.to(dtype=input.dtype)) | ||
| loss = flow._C.cross_entropy(input, onehot_label.to(dtype=input.dtype), reduction='none') |
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loss这块确定要改吗😂（cross_entropy内部貌似包含2个oplog_softmax和nll，可能效率不一定有softmax_cross_entropy好)
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临时改的，为了能跑通，等志鹏那个开发好了，就改回来。
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