Flux Models to Lux Models
Accessing these functions require manually loading Flux, i.e., using Flux must be present somewhere in the code for these to be used.
Index
Functions
# Lux.transform —
Function.
```julia
transform(l; preserve_ps_st::Bool=false, force_preserve::Bool=false)
```
Convert a Flux Model to Lux Model.
:::warning
`transform` always ingores the `active` field of some of the Flux layers. This is almost never going to be supported.
:::
**Arguments**
* `l`: Flux l or any generic Julia function / object.
**Keyword Arguments**
* `preserve_ps_st`: Set to `true` to preserve the states and parameters of the l. This attempts the best possible way to preserve the original model. But it might fail. If you need to override possible failures, set `force_preserve` to `true`.
* `force_preserve`: Some of the transformations with state and parameters preservation haven't been implemented yet, in these cases, if `force_transform` is `false` a warning will be printed and a core Lux layer will be returned. Else, it will create a [`FluxLayer`](flux_to_lux#Lux.FluxLayer).
**Examples**
```julia
import Flux
using Lux, Metalhead, Random
m = ResNet(18)
m2 = transform(m.layers)
x = randn(Float32, 224, 224, 3, 1);
ps, st = Lux.setup(Random.default_rng(), m2);
m2(x, ps, st)
```
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Layers
# Lux.FluxLayer —
Type.
```julia
FluxLayer(layer)
```
Serves as a compatibility layer between Flux and Lux. This uses `Optimisers.destructure` API internally.
:::warning
Lux was written to overcome the limitations of `destructure` + `Flux`. It is recommended to rewrite your l in Lux instead of using this layer.
:::
:::warning
Introducing this Layer in your model will lead to type instabilities, given the way `Optimisers.destructure` works.
:::
**Arguments**
* `layer`: Flux layer
**Parameters**
* `p`: Flattened parameters of the `layer`
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