Comments (2)
I would report the LoadError from CUDA.jl error there since Flux has no control over it, but the more immediate issue is that something else in your global environment is forcing Flux to be downgraded. My recommendation would be to create a new environment for Flux + other non-global packages as is good practice, but if you must have it globally then try force ] add
ing the latest version of Flux and see what Pkg says about compat conflicts.
from flux.jl.
I cannot reproduce this
from flux.jl.
Related Issues (20)
- The dedicated tutorial on DataLoader is missing HOT 2
- Incorrect link on docs HOT 4
- Hard error using dice loss HOT 2
- Compilation time of Flux models HOT 1
- Flux.setup buggy and broken in latest v.0.13.17 HOT 3
- example for using apple GPU with flux HOT 4
- Dimensions check for `Conv` is incomplete, leading to confusing error HOT 1
- 2x performance regression due to 5e80211c3302b5e7b79b4f670498f5a68af6659b HOT 2
- Why is Flux.destructure type unstable? HOT 3
- bad formatting for PairwiseFusion docstring HOT 1
- Zero-sized arrays cannot be applied to Dense layers. HOT 4
- Adding Simple Recurrent Unit as a recurrent layer
- Collecting PyTorch -> Flux migration notes HOT 1
- tests are failing due to ComponentArrays HOT 2
- deprecate Flux.params HOT 7
- Significant time spent moving medium-size arrays to GPU, type instability HOT 10
- ConvTranspose errors with symmetric non-constant pad
- SamePad() for even sized filters.
- Dense layers with shared parameters HOT 5
- Implementation of `AdamW` differs from PyTorch HOT 10
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