Comments (1)
You can convert parameters to 128 bit Floats (BigFloat
) using Lux.LuxEltypeAdaptor{BigFloat}
, and use it similar to how f64
/f32
/f16
are used
from lux.jl.
Related Issues (20)
- Error in `compute_gradients` when loss already has a `Zygote.gradient` HOT 6
- NCCL Complex wrapper HOT 2
- Drop `Tracker.jl` support for SimpleChains
- Feature request: TimeDistributed Layer HOT 1
- Feature Request: Allow recurrent layers with 2D input (features * seq_length), even if the order is BatchLastIndex HOT 2
- DifferentiationInterface testing HOT 10
- Missing statistics tracking in normalization layers
- unexpected parameter type for AbstractExplicitContainer with single trainable field HOT 3
- Test with DispatchDoctor error mode
- `BFloat16` Support
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from lux.jl.