Enum InitMethod 

pub enum InitMethod {
    XavierUniform {
        gain: f32,
    },
    XavierNormal {
        gain: f32,
    },
    KaimingUniform {
        mode: FanMode,
        nonlinearity: Nonlinearity,
    },
    KaimingNormal {
        mode: FanMode,
        nonlinearity: Nonlinearity,
    },
    Uniform {
        low: f32,
        high: f32,
    },
    Normal {
        mean: f32,
        std: f32,
    },
    Zeros,
    Ones,
    Constant {
        value: f32,
    },
    Orthogonal {
        gain: f32,
    },
    Sparse {
        sparsity: f32,
        std: f32,
    },
    Eye,
    LecunUniform,
    LecunNormal,
    TruncatedNormal {
        mean: f32,
        std: f32,
        a: f32,
        b: f32,
    },
    VarianceScaling {
        scale: f32,
        mode: FanMode,
        distribution: Distribution,
    },
    Dirac,
    SIREN {
        c: f32,
        w0: f32,
    },
}

Enumeration of initialization methods

Variants

XavierUniform

Xavier/Glorot uniform initialization

Fields

gain: f32

XavierNormal

Xavier/Glorot normal initialization

Fields

gain: f32

KaimingUniform

Kaiming/He uniform initialization

Fields

mode: FanMode

nonlinearity: Nonlinearity

KaimingNormal

Kaiming/He normal initialization

Fields

mode: FanMode

nonlinearity: Nonlinearity

Uniform

Uniform random initialization

Fields

low: f32

high: f32

Normal

Normal random initialization

Fields

mean: f32

std: f32

Zeros

Zero initialization

Ones

Ones initialization

Constant

Constant initialization

Fields

value: f32

Orthogonal

Orthogonal initialization

Fields

gain: f32

Sparse

Sparse initialization

Fields

sparsity: f32

std: f32

Eye

Identity/Eye initialization

LecunUniform

Lecun uniform initialization

LecunNormal

Lecun normal initialization

TruncatedNormal

Truncated normal initialization

Fields

mean: f32

std: f32

a: f32

b: f32

VarianceScaling

Variance scaling initialization (generalization of Xavier/Kaiming)

Fields

scale: f32

mode: FanMode

distribution: Distribution

Dirac

Dirac initialization for convolutional layers

SIREN

SIREN initialization for periodic activation functions Recommended for networks using sine activations

Fields

c: f32

w0: f32

Implementations

impl InitMethod

pub fn xavier_uniform() -> Self

Create Xavier/Glorot uniform initialization with default gain (1.0)

pub fn xavier_normal() -> Self

Create Xavier/Glorot normal initialization with default gain (1.0)

pub fn kaiming_uniform() -> Self

Create Kaiming/He uniform initialization for ReLU activations

pub fn kaiming_normal() -> Self

Create Kaiming/He normal initialization for ReLU activations

pub fn uniform_range(low: f32, high: f32) -> Self

Create uniform initialization with specified range

pub fn normal_dist(mean: f32, std: f32) -> Self

Create normal initialization with specified mean and standard deviation

pub fn zeros() -> Self

Create zero initialization

pub fn ones() -> Self

Create ones initialization

pub fn constant(value: f32) -> Self

Create constant initialization with specified value

pub fn orthogonal() -> Self

Create orthogonal initialization with default gain (1.0)

pub fn lecun_uniform() -> Self

Create LeCun uniform initialization

pub fn lecun_normal() -> Self

Create LeCun normal initialization

pub fn dirac() -> Self

Create Dirac initialization for convolutional layers

pub fn siren_first_layer() -> Self

Create SIREN initialization for first layer (w0=30.0, c=1.0)

pub fn siren_hidden_layer() -> Self

Create SIREN initialization for hidden layers (w0=1.0, c=6.0)

pub fn with_gain(self, gain: f32) -> Self

Set the gain for applicable initialization methods

pub fn with_fan_mode(self, mode: FanMode) -> Self

Set the fan mode for applicable initialization methods

pub fn with_nonlinearity(self, nonlinearity: Nonlinearity) -> Self

Set the nonlinearity for applicable initialization methods

pub fn name(&self) -> &str

Get a human-readable name for this initialization method

Trait Implementations

impl Clone for InitMethod

fn clone(&self) -> InitMethod

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for InitMethod

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Initializer for InitMethod

fn initialize(&self, shape: &[usize]) -> Result<Tensor>

Initialize a tensor with the given shape