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Update training.md #2286

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Jul 13, 2023
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Update training.md #2286

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4 changes: 2 additions & 2 deletions docs/src/training/training.md
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Expand Up @@ -61,8 +61,8 @@ then the derivative of the loss with respect to it is `∂f_∂θ = grads[1].lay
It is important that the execution of the model takes place inside the call to `gradient`,
in order for the influence of the model's parameters to be observed by Zygote.

It is also important that every `update!` step receives a newly gradient computed gradient,
as this will be change whenever the model's parameters are changed, and for each new data point.
It is also important that every `update!` step receives a newly computed gradient,
as it will change whenever the model's parameters are changed, and for each new data point.

!!! compat "Implicit gradients"
Flux ≤ 0.14 used Zygote's "implicit" mode, in which `gradient` takes a zero-argument function.
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