@ai-on-browser/data-analysis-models
Version:
Data analysis model package without any dependencies
51 lines (50 loc) • 1.53 kB
TypeScript
/**
* Batch normalization layer
*/
export default class BatchNormalizationLayer extends Layer {
/**
* @param {object} config object
* @param {number | number[] | string} [config.scale] Scale
* @param {number | number[] | string} [config.offset] Offset
* @param {number} [config.epsilon] Epsilon
* @param {number} [config.channel_dim] Dimension of the channel
* @param {number[] | string} [config.input_mean] Input mean
* @param {number[] | string} [config.input_var] Input variance
*/
constructor({ scale, offset, epsilon, channel_dim, input_mean, input_var, ...rest }: {
scale?: number | number[] | string;
offset?: number | number[] | string;
epsilon?: number;
channel_dim?: number;
input_mean?: number[] | string;
input_var?: number[] | string;
});
_scale: number | number[];
_scalename: string;
_offset: number | number[];
_offsetname: string;
_epsilon: number;
_channel_dim: 1 | -1;
_input_mean: string | number[];
_input_var: string | number[];
get mean(): any;
get var(): any;
calc(x: any): any;
_mean: any;
_var: any;
_xc: any;
_xh: any;
grad(bo: any): any;
_bo: any;
update(optimizer: any): void;
toObject(): {
type: string;
scale: any;
offset: any;
epsilon: number;
channel_dim: number;
input_mean: string | number[];
input_var: string | number[];
};
}
import Layer from './base.js';