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Update docs/src/models/basics.md

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Co-Authored-By: Carlo Lucibello <carlo.lucibello@gmail.com>
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Dhairya Gandhi 2020-02-12 11:25:50 +05:30 committed by GitHub
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@ -228,7 +228,7 @@ The first way of achieving this is through overloading the `trainable` function.
Flux.trainable(a::Affine) = (a.W, a.b,) Flux.trainable(a::Affine) = (a.W, a.b,)
``` ```
To add other fields is simply to add them to the tuple. Only the fields returned by `trainable` will be collected as trainable parameters of the layer when calling `Flux.params`.
Another way of achieving this is through the `@functor` macro. Here, wee can mark the fields we are interested in like so: Another way of achieving this is through the `@functor` macro. Here, wee can mark the fields we are interested in like so: