Enum google_api_proto::google::cloud::aiplatform::v1beta1::smooth_grad_config::GradientNoiseSigma

pub enum GradientNoiseSigma {
    NoiseSigma(f32),
    FeatureNoiseSigma(FeatureNoiseSigma),
}

Represents the standard deviation of the gaussian kernel that will be used to add noise to the interpolated inputs prior to computing gradients.

Variants

NoiseSigma(f32)

This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about normalization.

For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1.

If the distribution is different per feature, set [feature_noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.feature_noise_sigma] instead for each feature.

FeatureNoiseSigma(FeatureNoiseSigma)

This is similar to [noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.noise_sigma], but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, [noise_sigma][google.cloud.aiplatform.v1beta1.SmoothGradConfig.noise_sigma] will be used for all features.

Implementations

impl GradientNoiseSigma

pub fn encode<B>(&self, buf: &mut B)

where B: BufMut,

Encodes the message to a buffer.

pub fn merge<B>( field: &mut Option<GradientNoiseSigma>, tag: u32, wire_type: WireType, buf: &mut B, ctx: DecodeContext ) -> Result<(), DecodeError>

where B: Buf,

Decodes an instance of the message from a buffer, and merges it into self.

pub fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

Trait Implementations

impl Clone for GradientNoiseSigma

fn clone(&self) -> GradientNoiseSigma

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for GradientNoiseSigma

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

Formats the value using the given formatter.

impl PartialEq for GradientNoiseSigma

fn eq(&self, other: &GradientNoiseSigma) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for GradientNoiseSigma