ContrastivePredictiveCoding

Struct ContrastivePredictiveCoding 

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pub struct ContrastivePredictiveCoding {
    pub embedding_dim: usize,
    pub hidden_dim: usize,
    pub context_length: usize,
    pub prediction_steps: usize,
    pub temperature: f64,
    pub learning_rate: f64,
    pub batch_size: usize,
    pub max_epochs: usize,
    pub negative_samples: usize,
    pub random_state: Option<u64>,
}
Expand description

Contrastive Predictive Coding (CPC) for semi-supervised learning

CPC learns representations by predicting future observations from past contexts in a contrastive manner. It maximizes mutual information between contexts and positive samples while minimizing it for negative samples.

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§embedding_dim: usize

embedding_dim

§hidden_dim: usize

hidden_dim

§context_length: usize

context_length

§prediction_steps: usize

prediction_steps

§temperature: f64

temperature

§learning_rate: f64

learning_rate

§batch_size: usize

batch_size

§max_epochs: usize

max_epochs

§negative_samples: usize

negative_samples

§random_state: Option<u64>

random_state

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impl ContrastivePredictiveCoding

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pub fn new() -> Self

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pub fn embedding_dim(self, embedding_dim: usize) -> Self

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pub fn hidden_dim(self, hidden_dim: usize) -> Self

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pub fn context_length(self, context_length: usize) -> Self

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pub fn prediction_steps(self, prediction_steps: usize) -> Self

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pub fn temperature(self, temperature: f64) -> Result<Self>

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pub fn learning_rate(self, learning_rate: f64) -> Self

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pub fn batch_size(self, batch_size: usize) -> Result<Self>

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pub fn max_epochs(self, max_epochs: usize) -> Self

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pub fn negative_samples(self, negative_samples: usize) -> Self

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pub fn random_state(self, random_state: u64) -> Self

Trait Implementations§

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impl Clone for ContrastivePredictiveCoding

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fn clone(&self) -> ContrastivePredictiveCoding

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for ContrastivePredictiveCoding

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

Formats the value using the given formatter. Read more
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impl Default for ContrastivePredictiveCoding

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fn default() -> Self

Returns the “default value” for a type. Read more
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impl Estimator for ContrastivePredictiveCoding

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type Config = ContrastivePredictiveCoding

Configuration type for the estimator
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type Error = ContrastiveLearningError

Error type for the estimator
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type Float = f64

The numeric type used by this estimator
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fn config(&self) -> &Self::Config

Get estimator configuration
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fn validate_config(&self) -> Result<(), SklearsError>

Validate estimator configuration with detailed error context
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fn check_compatibility( &self, n_samples: usize, n_features: usize, ) -> Result<(), SklearsError>

Check if estimator is compatible with given data dimensions
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fn metadata(&self) -> EstimatorMetadata

Get estimator metadata
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impl Fit<ArrayBase<ViewRepr<&f64>, Dim<[usize; 2]>>, ArrayBase<ViewRepr<&i32>, Dim<[usize; 1]>>> for ContrastivePredictiveCoding

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type Fitted = FittedContrastivePredictiveCoding

The fitted model type
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fn fit( self, X: &ArrayView2<'_, f64>, y: &ArrayView1<'_, i32>, ) -> Result<Self::Fitted>

Fit the model to the provided data with validation
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fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>
where Self: Sized,

Fit with custom validation and early stopping

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impl<T> Any for T
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🔬This is a nightly-only experimental API. (clone_to_uninit)
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const ALIGN: usize

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type Init = T

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