use crate::neural_architecture_search::{architecture::*, types::*};
use anyhow::Result;
use std::sync::Arc;
use std::time::Duration;
pub struct PerformanceEvaluator {
config: EvaluationConfig,
}
#[derive(Debug, Clone)]
pub struct EvaluationConfig {
pub timeout: Duration,
pub max_epochs: usize,
pub validation_split: f64,
}
impl PerformanceEvaluator {
pub fn new(config: EvaluationConfig) -> Self {
Self { config }
}
pub fn evaluate(&self, architecture: &Architecture) -> Result<PerformanceMetrics> {
Ok(PerformanceMetrics {
embedding_quality: 0.8,
training_loss: 0.1,
validation_loss: 0.15,
inference_latency_ms: 10.0,
model_size_params: architecture.estimate_complexity(),
memory_usage_mb: 100.0,
flops: 1_000_000,
training_time_minutes: 30.0,
energy_consumption: 50.0,
task_metrics: std::collections::HashMap::new(),
})
}
pub fn batch_evaluate(&self, architectures: &[Architecture]) -> Result<Vec<PerformanceMetrics>> {
architectures.iter().map(|arch| self.evaluate(arch)).collect()
}
}
impl Default for EvaluationConfig {
fn default() -> Self {
Self {
timeout: Duration::from_secs(3600), max_epochs: 100,
validation_split: 0.2,
}
}
}