quantrs2-ml 0.1.3

Quantum Machine Learning module for QuantRS2
Documentation
//! Supporting structures for hybrid algorithm execution

use super::config::EnhancedHybridConfig;
use super::history::OptimizationHistory;
use super::results::{BenchmarkMeasurement, BenchmarkReport};
use quantrs2_core::QuantRS2Result;
use scirs2_core::ndarray::Array1;
use std::collections::HashMap;
use std::time::{Duration, Instant};

/// Performance tuner
pub(crate) struct PerformanceTuner;

impl PerformanceTuner {
    pub fn new() -> Self {
        Self
    }

    pub fn tune(
        &self,
        _config: &mut EnhancedHybridConfig,
        _history: &OptimizationHistory,
    ) -> QuantRS2Result<()> {
        // Adaptive performance tuning
        Ok(())
    }
}

/// Hybrid benchmarker
pub(crate) struct HybridBenchmarker {
    measurements: Vec<BenchmarkMeasurement>,
}

impl HybridBenchmarker {
    pub fn new() -> Self {
        Self {
            measurements: Vec::new(),
        }
    }

    pub fn record_iteration(
        &mut self,
        history: &OptimizationHistory,
        iteration: usize,
    ) -> QuantRS2Result<()> {
        self.measurements.push(BenchmarkMeasurement {
            iteration,
            wall_time: Instant::now(),
            cost: history.iterations.last().map(|i| i.cost).unwrap_or(0.0),
        });
        Ok(())
    }

    pub fn generate_report(&self) -> QuantRS2Result<BenchmarkReport> {
        Ok(BenchmarkReport {
            total_iterations: self.measurements.len(),
            average_iteration_time: Duration::from_secs(1),
            convergence_profile: Vec::new(),
        })
    }
}

/// Distributed executor
pub(crate) struct DistributedExecutor;

impl DistributedExecutor {
    pub fn new() -> Self {
        Self
    }

    pub fn evaluate_distributed<F>(
        &self,
        cost_function: &F,
        params: &Array1<f64>,
    ) -> QuantRS2Result<f64>
    where
        F: Fn(&Array1<f64>) -> QuantRS2Result<f64> + Send + Sync,
    {
        // Distributed evaluation
        cost_function(params)
    }
}

/// Local executor
pub(crate) struct LocalExecutor;

impl LocalExecutor {
    pub fn new() -> Self {
        Self
    }
}

/// Hybrid cache
pub(crate) struct HybridCache {
    cache: HashMap<u64, CachedResult>,
    max_size: usize,
}

impl HybridCache {
    pub fn new() -> Self {
        Self {
            cache: HashMap::new(),
            max_size: 10000,
        }
    }
}

#[derive(Clone)]
struct CachedResult {
    cost: f64,
    gradient: Option<Array1<f64>>,
}