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typo 

Co-Authored-By: Mike J Innes <mike.j.innes@gmail.com>
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Dhairya Gandhi 2019-10-10 20:16:00 +05:30 committed by GitHub
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docs/src/training/optimisers.md
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@ -88,7 +88,7 @@ This is the basic definition of a Momentum update rule given by:
$v = ρ * v - η * Δ$
$w = w - v$
The `apply!` defines the update rules for an optimsier `opt`, given the parameters and gradients. It returns the updated gradients usually. Here, every parameter `x` is retrieved from the running state `v` and subsequently updates the state of the optimiser.
The `apply!` defines the update rules for an optimiser `opt`, given the parameters and gradients. It returns the updated gradients usually. Here, every parameter `x` is retrieved from the running state `v` and subsequently updates the state of the optimiser.
Flux internally calls on this function via the `update!` function. It shares the API with `apply!` but ensures that multiple parameters are handled gracefully. In the future, it will also be delegating immutable update operations.