zixuanweeei edited a comment on issue #16256: [Bug] Failed to evaluate gradient on samples with train_mode=False URL: https://github.com/apache/incubator-mxnet/issues/16256#issuecomment-534925721 Thanks for reporting this issue. Actually, we need a workspace to store the intermediate result of RNN variants, like the output of every gate and the state of every step, which are created only when `is_train=True`. These intermediate results are used in the gradients' calculation. When `train_mode=False` (`is_train=False`), no workspace will be created in `Forward`. So it will raise the error in `Backward`. As to dropout, mxnet-mkl doesn't support it. But you can `export MXNET_USE_MKLDNN_RNN=0` to force MXNet run into the naive CPU-RNN path, where dropout are enabled. If you don't set `MXNET_USE_MKLDNN_RNN=0`, it should be `1` by default, which means that MKL-DNN RNN path without dropout enabled will be executed. For now, we don't have a good solution for your request. RNN operator has a different machnism than other operators. I will look for a solution. Any insights? @ZhiminPeng
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