@ai-on-browser/data-analysis-models
    Preparing search index...

    Class DiffusionModel

    Diffusion model network

    Index

    Constructors

    constructor

    Properties

    _alpha _alphaCumprod _beta _dataShape _epoch _layers _model _peDims _timesteps _ulayers

    Accessors

    epoch

    Methods

    _addNoise _build _positionEncoding fit generate

    Constructors

    • Parameters

      • timesteps: number

        Number of timestep

      • Optionallayers: LayerObject[]

        Layers

      Returns DiffusionModel

    Properties

    _alpha

    _alpha: number[]

    _alphaCumprod

    _alphaCumprod: number[]

    _beta

    _beta: number[]

    _dataShape

    _dataShape: number[]

    _epoch

    _epoch: number

    _layers

    _layers:
        | (
            | {
                activation?: undefined;
                axis?: undefined;
                input?: undefined;
                l2_decay?: undefined;
                name: string;
                out_size?: undefined;
                type: string;
            }
            | {
                activation: string;
                axis?: undefined;
                input?: undefined;
                l2_decay: number;
                name: string;
                out_size: number;
                type: string;
            }
            | {
                activation?: undefined;
                axis: number;
                input: string[];
                l2_decay?: undefined;
                name?: undefined;
                out_size?: undefined;
                type: string;
            }
        )[]
        | (
            | {
                activation?: undefined;
                axis?: undefined;
                input?: undefined;
                l2_decay?: undefined;
                name: string;
                out_size?: undefined;
                size?: undefined;
                type: string;
            }
            | {
                activation: string;
                axis?: undefined;
                input?: undefined;
                l2_decay: number;
                name?: undefined;
                out_size: number;
                size?: undefined;
                type: string;
            }
            | {
                activation?: undefined;
                axis?: undefined;
                input?: undefined;
                l2_decay?: undefined;
                name?: undefined;
                out_size?: undefined;
                size: any[];
                type: string;
            }
            | {
                activation?: undefined;
                axis?: undefined;
                input?: undefined;
                l2_decay?: undefined;
                name: string;
                out_size?: undefined;
                size: number[];
                type: string;
            }
            | {
                activation?: undefined;
                axis: number;
                input: string[];
                l2_decay?: undefined;
                name?: undefined;
                out_size?: undefined;
                size?: undefined;
                type: string;
            }
        )[]

    _model

    _model: NeuralNetwork

    _peDims

    _peDims: number

    _timesteps

    _timesteps: number

    _ulayers

    _ulayers: LayerObject[]

    Accessors

    • get epoch(): number

      Epoch

      Returns number

    Methods

    _addNoise

    • _addNoise(x: any, t: any): any[]

      Parameters

      • x: any
      • t: any

      Returns any[]

    _build

    _positionEncoding

    • _positionEncoding(t: any, embdims: any): Matrix<T>

      Parameters

      • t: any
      • embdims: any

      Returns Matrix<T>

    • Fit model.

      Parameters

      • train_x: number[][]

        Training data

      • iteration: number

        Iteration count

      • rate: number

        Learning rate

      • batch: number

        Batch size

      Returns { labeledLoss: number; unlabeledLoss: number }

      Loss value

    • Returns generated data from the model.

      Parameters

      • n: number

        Number of generated data

      Returns number[][]

      Generated values

    Settings

    Member Visibility

    On This Page

    Constructors
    Properties
    Accessors
    Methods