Comments (3)
Give a shot to:
https://github.com/PhilipVinc/TensorBoardLogger.jl/blob/master/src/TensorBoardLogger.jl
from deepqlearning.jl.
implemented in #12
It could be nice to be able to log environment specific information as well using the info
output of the step!
function.
from deepqlearning.jl.
Perhaps not as important, but logging the eval_reward along with eps, avgR, loss, and Grad in the terminal during training would be cool as well.
48500 / 1000000 eps 0.904 | avgR -1.004 | Loss 6.049e-01 | Grad 5.596e-01
49000 / 1000000 eps 0.903 | avgR -1.004 | Loss 6.760e-01 | Grad 3.692e-01
from deepqlearning.jl.
Related Issues (20)
- Support last Flux version with Float32 HOT 1
- 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
- Error: Can't differentiate loopinfo expression HOT 6
- 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.