Comments (3)
I agree, we should do the same as Keras.
If I recall correctly the reasoning behind not including relu if inlcude_top=False
was that if you want to add more binary layers after the network it might not be desired to have the relu included. This is not a problem for full precision networks as there should always be non-linearity between layers.
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Hey @nixingyang, thank you for your interest in Larq and Larq Zoo!
It does indeed look like our behaviour in this regard differs from that of keras-applications
. @lgeiger / @koenhelwegen thoughts on moving the activation out of the if statement?
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I see no reason to deviate from keras here, so would be happy to change it (but I think @lgeiger knows these models best, perhaps he knows why it's currently like this).
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Related Issues (20)
- Unexpected behavior of the "preprocess_input" function HOT 1
- Make ordering of docstring constistent
- Snapshot tests of model summaries HOT 2
- RFC: structure change HOT 3
- Add model accuracies to docstrings
- QuickNet(Large) models don't match released h5 files
- Support TensorFlow 2.2 HOT 3
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- Update weights and parameters in docstrings
- QuickNet no-top models pretrained weights are not working as expected HOT 1
- No 'sota' module HOT 2
- Speech Models HOT 2
- About RealToBinaryNet model HOT 14
- Intermediate results of training R2B model HOT 5
- Data directory HOT 1
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- Help, no logs are printed! HOT 2
- The usage of data.cache() causes the run out of memory. HOT 5
- Drop Python 3.6 support
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