network is not learning if not hybridized

[TinkerSteve]

I tried to train the network in its default configuration, which works like expected.

If I set the detault.hybridize parameter in utils/config.py to False, the network does'nt learn anything anymore:

INFO:root:[Epoch 4][Batch 8269], Speed: 5.551862 samples/sec, RPNLogLoss=3.406618, RPNSmoothL1Loss=0.463918, RCNNLogLoss=0.758454, RCNNSmoothL1Loss=0.295339
INFO:root:[Epoch 4] Training cost: 2994.834264, RPNLogLoss=3.406611, RPNSmoothL1Loss=0.463785, RCNNLogLoss=0.758340, RCNNSmoothL1Loss=0.295269
INFO:root:[Epoch 4] Validation:
aeroplane=0.000000
...
sofa=0.000000
train=0.000000
tvmonitor=0.000000
mAP=0.000009

Does someone have an idea, why this is, or wether it is reproducable on other systems ?

I am using mxnet 1.3.0 and cudnn 7.1.2 with cuda 9.0

Best Regards
Stephan

[WalterMa]

Currently, I recommend the GluonCV project more.

To be honest, there are still some minor problems in my project while I don't have too much time to investigate them now. 😣