Comments (3)
ExpandingMan
commented on May 5, 2024
For a while I was running into a back! not defined error. Then it went away for a while. Now it's back again (no pun intended).
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ExpandingMan
commented on May 5, 2024
I looked into this again today and I am still getting this error with tensorflow.
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MikeInnes
commented on May 5, 2024
On the latest release, the examples should all work out of the box. I tried to make sure all of Flux's exports were fairly obvious; things like back! are quite generic and better off explicitly imported.
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Related Issues (20)
- No cudnn implementation of Conv((1,) N=>M) HOT 12
- Flux docs missing withgradient() call for multi-objective loss functions HOT 6
- can't use masks in multi-head-attention layer HOT 6
- Adapt saving & loading example to CuArrays HOT 2
- Segmentation fault when doing a forward pass with a model saved with BSON HOT 2
- Flux new explicit API does not work but old implicit API works for a simple RNN HOT 4
- Intel Arc GPU support. HOT 1
- `using Flux, cuDNN` freezes, but `using Flux, CUDA, cuDNN` works HOT 1
- Convolutional network slower than tensorflow on CPU HOT 13
- Problem with RNN and CUDA. HOT 7
- precompilation issue on Julia 1.10 HOT 1
- Android/iOS support HOT 1
- since new version: Flux throws error when for train! / update! even on quick start problem HOT 4
- Illegal Memory Access Error During Gradient Calculation of predefined losses on GPU RTX 4050 HOT 1
- Unnecessarily using shared GPU memory HOT 8
- Flux installation error under Julia 1.10 on Apple Silicon HOT 2
- Given that DataLoader implements `length` shouldn't it also be able to provide size? HOT 4
- The dedicated tutorial on DataLoader is missing HOT 2
- Incorrect link on docs HOT 4
- Hard error using dice loss HOT 2
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