burn-nn 0.20.1

Neural network building blocks for the Burn deep learning framework
Documentation 
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mod interpolate1d;
mod interpolate2d;

pub use interpolate1d::*;
pub use interpolate2d::*;

use burn_core as burn;

use burn::config::Config;
use burn::tensor::ops::InterpolateMode as OpsInterpolateMode;

/// Algorithm used for downsampling and upsampling
///
/// This enum defines different interpolation modes for resampling data.
#[derive(Config, Debug)]
pub enum InterpolateMode {
    /// Nearest-neighbor interpolation
    ///
    /// This mode selects the value of the nearest sample point for each output pixel.
    /// It is applicable for both temporal and spatial data.
    Nearest,

    /// Linear interpolation
    ///
    /// This mode calculates the output value using linear
    /// interpolation between nearby sample points.
    ///
    /// It is applicable for both temporal and spatial data.
    Linear,

    /// Cubic interpolation
    ///
    /// This mode uses cubic interpolation to calculate the output value
    /// based on surrounding sample points.
    ///
    /// It is applicable for both temporal and spatial data and generally
    /// provides smoother results than linear interpolation.
    Cubic,
}

impl From<InterpolateMode> for OpsInterpolateMode {
    fn from(mode: InterpolateMode) -> Self {
        match mode {
            InterpolateMode::Nearest => OpsInterpolateMode::Nearest,
            InterpolateMode::Linear => OpsInterpolateMode::Bilinear,
            InterpolateMode::Cubic => OpsInterpolateMode::Bicubic,
        }
    }
}