Comments (6)
It seems like something changed in how Flux is differentiating, we might need to update the code to work with latest Flux.
from deepqlearning.jl.
Hi, was this bug fixed or is there some known workaround? Thanks.
from deepqlearning.jl.
Sorry, could you provide the versions of Flux you are using?
I updated the CI to latest julia last weekend and it seems like all the tests are working.
from deepqlearning.jl.
Hi, actually itβs working now, maybe @rgCategory needs to update packages. Flux v0.11.6 and Julia 1.6. Thanks.))
from deepqlearning.jl.
I was actually able to reproduce the error with Flux v0.11.6 and Julia 1.6, with Flux v0.12 it seems like it works, with the master branch of this package.
I will tag a new version.
from deepqlearning.jl.
Thanks for fixing this, @MaximeBouton !
from deepqlearning.jl.
Related Issues (20)
- Support last Flux version with Float32 HOT 1
- Logging Training Information HOT 3
- Fix avgR in terminal while training HOT 1
- TensorBoardLogger.jl New Version Compatability HOT 2
- Compilation Error HOT 1
- Type of the discount factor. HOT 1
- Use only RLInterface.jl interface HOT 3
- DQExperience should support AbstractArrays HOT 1
- Dimension Mismatch HOT 6
- Support of AbtractEnvironment HOT 2
- Problem with reading log files HOT 1
- Exploration Policy requires a (PO)MDP
- Automatically convert to Float32
- TagBot trigger issue HOT 10
- Question: How would you make a decay schedule for prioritized replay alpha/beta? HOT 1
- Tests still contain "using RLInterface" HOT 4
- Deprecation of `loadparams!`
- Action masking feature (legal actions) HOT 1
- GPU support HOT 1
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from deepqlearning.jl.