zixuanweeei edited a comment on issue #15741: MKL-DNN LBR-GRU Inference Integration (FP32 LBR-GRU) URL: https://github.com/apache/incubator-mxnet/pull/15741#issuecomment-519739904 @DickJC123 Thanks for your patient. And FYI, it seems that the possible flaky tests become effective with the edited UTs for RNN variants. I have tried to modify the code following the instructions from https://github.com/apache/incubator-mxnet/pull/14476#pullrequestreview-225789440. Specifically, + the `temp_space`, which is renamed to `workspace_`, is allocated along with `reserve_space_` in `Init()` at [#L1485-L1490](https://github.com/zixuanweeei/incubator-mxnet/blob/2b07a5f0c58a8f96621e1e8d1308513c726e09c4/src/operator/rnn-inl.h#L1485-L1490). + then, `host_workspace`, renamed to `seq_len_space_`, is allocated in an `if (!init_cudnn_) {...}` branch at [#L622-L631](https://github.com/zixuanweeei/incubator-mxnet/blob/2b07a5f0c58a8f96621e1e8d1308513c726e09c4/src/operator/rnn-inl.h#L622-L631). And all the spaces above are allocated once only using ` ctx.requested[rnn_enum::kTempSpace]` instead of `Storage`. But it didn't work on *UNIX system (CI has passed on windows-gpu, while it was failed on *UNIX-gpu with `test_gluon_gpu.test_layer_bidirectional_varseqlength`). Though the modifications are **not included in this PR**, you can find the whole source from [this link](https://github.com/zixuanweeei/incubator-mxnet/blob/2b07a5f0c58a8f96621e1e8d1308513c726e09c4/src/operator/rnn-inl.h). I have no idea about whether the `temp_space` and `host_workspace` should be re-initialized for every iteration. Need your help since I'm not familiar with GPU :)
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