meixitu opened a new issue #15425: in mxnet1.4.1-cuda10.0, depthwise conv training is very very slow URL: https://github.com/apache/incubator-mxnet/issues/15425 Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential information to most of the technical issues and bug reports. For non-technical issues and feature requests, feel free to present the information in what you believe is the best form. For Q & A and discussion, please start a discussion thread at https://discuss.mxnet.io ## Description Depthwise conv is very slow in python3.6, mxnet1.4.1-cuda10.0 version. If I set num_group=1, the training speed can improve 20 times. ## Environment info (Required)   ## Steps to reproduce (Paste the commands you ran that produced the error.) 0, python=3.6.0 1. pip3 install mxnet-cu100==1.4.1 2. use this model, https://github.com/mnikitin/EfficientNet/blob/master/efficientnet_model.py 3. set the batch_size=128, 4GPU, efficientnet-b6, input_size=112x112x3 ## What have you tried to solve it? 1. I try to use mx.sym.Convolution to replace the gluon, the training speed is same
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