Comments (1)
Yeah, you need to pass them as a tuple. All layers follow a consistent API of (inputs, parameters, states)
so input can be of any arbitrary type.
from lux.jl.
Related Issues (20)
- 404 many Tutorial links are invalid
- uninitiated tutorial replicate part shows different numbers but should show the same
- uninitiated tutorial - Code Font confusing for pipe |> HOT 1
- Documentation Request: Standardize the handling of the state `st`
- Let @compact return the updated state HOT 7
- Documentation Request: Have a section about Loss Functions HOT 6
- Documentation Request: Also list GeometricML.jl and SciML.ai under Ecosystem HOT 2
- Should `replicate` be part of LuxCore? HOT 2
- pad=SamePad() does not work as intended in ConvTranspose. HOT 2
- Array of Structs to Struct of Array transformation for some AD backends
- Documentation on main is broken
- Lux.AMDGPU: type cast throws error HOT 5
- `l` should be clarified. Maybe a typo? HOT 2
- Externalize gradient computations to DifferentiationInterface.jl? HOT 9
- Bug when converting model with single layer to SimpleChains HOT 1
- Improve broadcasting via `FastBroadcast,jl`
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from lux.jl.