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};
#[derive(Clone)]
pub struct LossMetric {
name: Arc<String>,
state: NumericMetricState,
}
#[derive(new)]
pub struct LossInput {
tensor: Tensor<1>,
}
impl Default for LossMetric {
fn default() -> Self {
Self::new()
}
}
impl LossMetric {
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()
}
}