---
title: "init(learning_rate:alpha:epsilon:centered:momentum:gradient_scale:regularization_scale:clip_gradients:clip_gradients_min:clip_gradients_max:regularization_func:)"
framework: accelerate
role: symbol
role_heading: Initializer
path: "accelerate/bnnsoptimizerrmspropfields/init(learning_rate:alpha:epsilon:centered:momentum:gradient_scale:regularization_scale:clip_gradients:clip_gradients_min:clip_gradients_max:regularization_func:)"
---

# init(learning_rate:alpha:epsilon:centered:momentum:gradient_scale:regularization_scale:clip_gradients:clip_gradients_min:clip_gradients_max:regularization_func:)

Returns a new RMSProp optimizer fields structure from the specified parameters.

## Declaration

```swift
init(learning_rate: Float, alpha: Float, epsilon: Float, centered: Bool, momentum: Float, gradient_scale: Float, regularization_scale: Float, clip_gradients: Bool, clip_gradients_min: Float, clip_gradients_max: Float, regularization_func: BNNSOptimizerRegularizationFunction)
```

## Parameters

- `learning_rate`: A value that specifies the learning rate.
- `alpha`: A constant that specifies smoothing, in the range 0 to 1.
- `epsilon`: A term that the optimizer adds to the denominator.
- `centered`: A Boolean value that specifies whether to use the centered variant.
- `momentum`: The rate of momentum decay.
- `gradient_scale`: A value that specifies the gradient scaling factor.
- `regularization_scale`: A value that specifies the regularization scaling factor.
- `clip_gradients`: A Boolean value that specifies whether to clip the gradient between minimum and maximum values.
- `clip_gradients_min`: The values for the minimum gradient.
- `clip_gradients_max`: The values for the maximum gradient.
- `regularization_func`: The variable that specifies the regularization function.

## See Also

### Initializers

- [init()](accelerate/bnnsoptimizerrmspropfields/init().md)