burn-train 0.22.0

Training crate for the Burn framework
Documentation
use std::sync::Arc;

use super::MetricMetadata;
use super::SerializedEntry;
use super::state::FormatOptions;
use super::state::NumericMetricState;
use crate::metric::MetricName;
use crate::metric::{Metric, MetricAttributes, Numeric, NumericAttributes, NumericEntry};
use burn_core::tensor::{Tensor, TensorReadError};

/// The loss metric.
#[derive(Clone)]
pub struct LossMetric {
    name: Arc<String>,
    state: NumericMetricState,
}

/// The [loss metric](LossMetric) input type.
#[derive(new)]
pub struct LossInput {
    tensor: Tensor<1>,
}

impl Default for LossMetric {
    fn default() -> Self {
        Self::new()
    }
}

impl LossMetric {
    /// Create the metric.
    pub fn new() -> Self {
        Self {
            name: Arc::new("Loss".to_string()),
            state: NumericMetricState::default(),
        }
    }
}

impl Metric for LossMetric {
    type Input = LossInput;

    fn update(
        &mut self,
        loss: &Self::Input,
        _metadata: &MetricMetadata,
    ) -> Result<SerializedEntry, TensorReadError> {
        let [batch_size] = loss.tensor.dims();
        let loss = loss.tensor.clone().mean().try_into_scalar::<f64>()?;

        self.state.update(loss, batch_size);
        Ok(self
            .state
            .compute_update(FormatOptions::new(self.name()).precision(2)))
    }

    fn compute(&mut self) -> Result<SerializedEntry, TensorReadError> {
        Ok(self
            .state
            .compute_final(FormatOptions::new(self.name()).precision(2)))
    }

    fn clear(&mut self) {
        self.state.reset()
    }

    fn name(&self) -> MetricName {
        self.name.clone()
    }

    fn attributes(&self) -> MetricAttributes {
        NumericAttributes {
            unit: None,
            higher_is_better: false,
        }
        .into()
    }
}

impl Numeric for LossMetric {
    fn value(&self) -> Option<NumericEntry> {
        Some(self.state.current_value())
    }

    fn running_value(&self) -> Option<NumericEntry> {
        Some(self.state.running_value())
    }

    fn final_value(&self) -> NumericEntry {
        self.state.final_value()
    }
}