Struct SupervisedDataset 

pub struct SupervisedDataset { /* private fields */ }

Supervised dataset with aligned input/target sample axis at position 0.

Implementations

impl SupervisedDataset

pub fn augment_nhwc( &self, pipeline: &ImageAugmentationPipeline, seed: u64, ) -> Result<Self, ModelError>

Returns a new dataset with NHWC image augmentations applied to inputs.

impl SupervisedDataset

pub fn new(inputs: Tensor, targets: Tensor) -> Result<Self, ModelError>

pub fn len(&self) -> usize

pub fn is_empty(&self) -> bool

pub fn inputs(&self) -> &Tensor

pub fn targets(&self) -> &Tensor

pub fn batches( &self, batch_size: usize, ) -> Result<MiniBatchIter<'_>, ModelError>

pub fn batches_with_options( &self, batch_size: usize, options: BatchIterOptions, ) -> Result<MiniBatchIter<'_>, ModelError>

pub fn split_by_counts( &self, train_count: usize, validation_count: usize, shuffle: bool, seed: u64, ) -> Result<DatasetSplit, ModelError>

pub fn split_by_ratio( &self, train_ratio: f32, validation_ratio: f32, shuffle: bool, seed: u64, ) -> Result<DatasetSplit, ModelError>

pub fn split_by_class_ratio( &self, train_ratio: f32, validation_ratio: f32, shuffle: bool, seed: u64, ) -> Result<DatasetSplit, ModelError>

Trait Implementations

impl Clone for SupervisedDataset

fn clone(&self) -> SupervisedDataset

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SupervisedDataset

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

Formats the value using the given formatter.

impl PartialEq for SupervisedDataset

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for SupervisedDataset