Comments (4)
from fold.
Do you have a full example of its use with an RNN with labels at every timestep? The documentation is helpful, but still doesn't provide an entire picture for me.
Thanks :)
from fold.
You might find the sentiment example useful since it shows how to use td.Metric to compute a loss for the recursive case. The sequence case is the same except you don't need to worry about recursion and just apply the metric at every position in the sequence.
from fold.
Thanks!
from fold.
Related Issues (20)
- NEAT Algorithm implementation HOT 1
- How do I get the root embedding tensors after training the model? HOT 1
- Is it still live?
- Compatability with Tensorflow 2.4+ HOT 3
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- can current fold work with tensorflow 1.3? Is it tested? HOT 8
- How to use fold in serving? HOT 2
- Fold & Eager HOT 3
- "undefined symbol" caused by building fold from source HOT 3
- Not compiled to use: SSE4.1 SSE4.2
- Is Fold not compatible with tensorflow-1.4.0? HOT 1
- Typos in sample
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- "import tensorflow_fold" problem HOT 7
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- How to print intermediate outputs in recursion in TF Fold? HOT 4
- Printing predictions HOT 7
- Making Windows compatible HOT 2
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- fold incompatible with TF-gpu 1.10.1 HOT 1
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from fold.