trustformers-mobile 0.1.1

//! Mobile Testing Framework
//!
//! This module contains the main testing framework implementation for mobile ML testing.

use std::collections::HashMap;
use std::sync::{Arc, Mutex};
use std::thread;
use std::time::{Duration, Instant, SystemTime};
use trustformers_core::error::{CoreError, Result};
use trustformers_core::Tensor;
use trustformers_core::TrustformersError;

use crate::{
    battery::MobileBatteryManager, device_info::MobileDeviceDetector,
    inference::MobileInferenceEngine, thermal_power::ThermalPowerManager, MobileConfig,
};

use super::config::*;
use super::results::*;

/// Main mobile testing framework
pub struct MobileTestingFramework {
    config: MobileTestingConfig,
    inference_engine: Option<MobileInferenceEngine>,
    battery_manager: Option<MobileBatteryManager>,
    thermal_manager: Option<ThermalPowerManager>,
    test_state: Arc<Mutex<TestState>>,
}

#[derive(Debug, Default)]
struct TestState {
    is_running: bool,
    current_test: Option<String>,
    start_time: Option<Instant>,
    results: Vec<TestSuiteResults>,
}

impl MobileTestingFramework {
    /// Create a new mobile testing framework
    pub fn new(config: MobileTestingConfig) -> Result<Self> {
        Ok(Self {
            config,
            inference_engine: None,
            battery_manager: None,
            thermal_manager: None,
            test_state: Arc::new(Mutex::new(TestState::default())),
        })
    }

    /// Initialize the testing framework
    pub fn initialize(&mut self, mobile_config: MobileConfig) -> Result<()> {
        // Initialize inference engine
        self.inference_engine = Some(MobileInferenceEngine::new(mobile_config)?);

        // Detect device information for proper manager initialization
        let device_info = MobileDeviceDetector::detect()?;

        // Initialize battery manager with default configuration
        let battery_config = crate::battery::BatteryConfig::default();
        self.battery_manager = Some(MobileBatteryManager::new(battery_config, &device_info)?);

        // Initialize thermal manager with default configuration
        let thermal_config = crate::thermal_power::ThermalPowerConfig::default();
        self.thermal_manager = Some(ThermalPowerManager::new(thermal_config, &device_info)?);

        Ok(())
    }

    /// Run complete test suite
    pub async fn run_test_suite(&mut self) -> Result<TestSuiteResults> {
        let start_time = SystemTime::now();
        let test_start = Instant::now();

        {
            let mut state = self.test_state.lock().expect("Operation failed");
            state.is_running = true;
            state.start_time = Some(test_start);
        }

        let mut results = TestSuiteResults {
            timestamp: start_time,
            duration: Duration::default(),
            benchmark_results: Vec::new(),
            battery_results: Vec::new(),
            stress_results: Vec::new(),
            memory_results: Vec::new(),
            success_rate: 0.0,
        };

        let mut total_tests = 0;
        let mut successful_tests = 0;

        // Run benchmark tests
        if let Ok(benchmark_results) = self.run_benchmark_tests().await {
            total_tests += benchmark_results.len();
            successful_tests += benchmark_results.iter().filter(|r| r.avg_latency_ms > 0.0).count();
            results.benchmark_results = benchmark_results;
        }

        // Run battery tests
        if let Ok(battery_results) = self.run_battery_tests().await {
            total_tests += battery_results.len();
            successful_tests +=
                battery_results.iter().filter(|r| r.energy_consumed_mwh > 0.0).count();
            results.battery_results = battery_results;
        }

        // Run stress tests
        if let Ok(stress_results) = self.run_stress_tests().await {
            total_tests += stress_results.len();
            successful_tests += stress_results.iter().filter(|r| r.success_rate > 0.0).count();
            results.stress_results = stress_results;
        }

        // Run memory tests
        if let Ok(memory_results) = self.run_memory_tests().await {
            total_tests += memory_results.len();
            successful_tests += memory_results.len(); // Memory tests always produce results
            results.memory_results = memory_results;
        }

        results.duration = test_start.elapsed();
        results.success_rate =
            if total_tests > 0 { successful_tests as f32 / total_tests as f32 } else { 0.0 };

        {
            let mut state = self.test_state.lock().expect("Operation failed");
            state.is_running = false;
            state.current_test = None;
            state.results.push(results.clone());
        }

        Ok(results)
    }

    /// Run benchmark tests
    async fn run_benchmark_tests(&mut self) -> Result<Vec<BenchmarkResult>> {
        let config = self.config.benchmark_config.clone();
        let mut results = Vec::new();

        for input_shape in &config.input_sizes {
            for &precision_mode in &config.precision_modes {
                for &power_mode in &config.power_modes {
                    for &thermal_condition in &config.thermal_conditions {
                        if let Ok(result) = self
                            .run_single_benchmark(
                                input_shape.clone(),
                                precision_mode,
                                power_mode,
                                thermal_condition,
                            )
                            .await
                        {
                            results.push(result);
                        }
                    }
                }
            }
        }

        Ok(results)
    }

    /// Run a single benchmark test
    async fn run_single_benchmark(
        &mut self,
        input_shape: Vec<usize>,
        precision_mode: PrecisionMode,
        power_mode: PowerMode,
        thermal_condition: ThermalCondition,
    ) -> Result<BenchmarkResult> {
        let config = &self.config.benchmark_config;

        {
            let mut state = self.test_state.lock().expect("Operation failed");
            state.current_test = Some(format!("Benchmark {:?} {:?}", input_shape, precision_mode));
        }

        let engine = self.inference_engine.as_mut().ok_or_else(|| {
            TrustformersError::tensor_op_error(
                "Inference engine not initialized",
                "run_single_benchmark",
            )
        })?;

        // Create test tensor
        let test_data: Vec<f32> = (0..input_shape.iter().product::<usize>())
            .map(|i| (i as f32) / 1000.0)
            .collect();
        let input_tensor = Tensor::from_vec(test_data, &input_shape)?;

        // Warmup iterations
        for _ in 0..config.warmup_iterations {
            let _ = engine.inference(&input_tensor)?;
        }

        // Benchmark iterations
        let mut latencies = Vec::new();
        let start_time = Instant::now();
        let mut memory_usage = 0;

        for _ in 0..config.benchmark_iterations {
            let iter_start = Instant::now();
            let _output = engine.inference(&input_tensor)?;
            let iter_duration = iter_start.elapsed();
            latencies.push(iter_duration.as_secs_f32() * 1000.0);

            // Estimate memory usage (simplified)
            memory_usage = (input_shape.iter().product::<usize>() * 4) / (1024 * 1024);
        }

        let total_duration = start_time.elapsed();
        let throughput = config.benchmark_iterations as f32 / total_duration.as_secs_f32();

        // Calculate percentiles
        latencies.sort_by(|a, b| a.partial_cmp(b).expect("Operation failed"));
        let avg_latency = latencies.iter().sum::<f32>() / latencies.len() as f32;
        let p95_latency = latencies[(latencies.len() * 95 / 100).min(latencies.len() - 1)];
        let p99_latency = latencies[(latencies.len() * 99 / 100).min(latencies.len() - 1)];

        Ok(BenchmarkResult {
            config_id: format!(
                "{:?}_{:?}_{:?}",
                precision_mode, power_mode, thermal_condition
            ),
            input_shape,
            precision_mode,
            power_mode,
            thermal_condition,
            avg_latency_ms: avg_latency,
            p95_latency_ms: p95_latency,
            p99_latency_ms: p99_latency,
            throughput_fps: throughput,
            memory_usage_mb: memory_usage,
            accuracy_metrics: self.create_mock_accuracy_metrics(),
            power_stats: self.create_mock_power_stats(),
        })
    }

    /// Run battery tests
    async fn run_battery_tests(&mut self) -> Result<Vec<BatteryTestResult>> {
        let config = self.config.battery_test_config.clone();
        let mut results = Vec::new();

        {
            let mut state = self.test_state.lock().expect("Operation failed");
            state.current_test = Some("Battery Test".to_string());
        }

        // Use actual battery manager if available, otherwise fall back to mock data
        let (initial_battery, use_real_battery_manager) =
            if let Some(ref battery_manager) = self.battery_manager {
                // Get actual battery level from battery manager using the newly implemented API
                (battery_manager.get_current_battery_level(), true)
            } else {
                (0.85f32, false) // Mock initial battery level
            };

        let start_time = Instant::now();
        let mut total_inferences = 0;
        let mut power_samples = Vec::new();

        // Run inferences at specified frequency
        let test_duration = config.test_duration;
        let inference_interval = config.inference_frequency;

        while start_time.elapsed() < test_duration {
            // Perform inference
            let test_input = self.create_test_input();
            if let Some(engine) = &mut self.inference_engine {
                if let Ok(_) = engine.inference(&test_input) {
                    total_inferences += 1;
                }
            }

            // Sample power consumption - use thermal/power manager if available
            let power_sample = if let Some(ref thermal_manager) = self.thermal_manager {
                // Use actual power consumption from thermal manager using the newly implemented API
                thermal_manager
                    .get_current_power()
                    .unwrap_or_else(|| self.estimate_power_consumption())
            } else {
                self.estimate_power_consumption()
            };
            power_samples.push(power_sample);

            // Wait for next inference
            tokio::time::sleep(inference_interval).await;
        }

        let final_battery = if use_real_battery_manager {
            // Get actual final battery level from battery manager using the newly implemented API
            if let Some(ref battery_manager) = self.battery_manager {
                battery_manager.get_current_battery_level()
            } else {
                initial_battery - 0.02f32 // Fallback
            }
        } else {
            initial_battery - 0.02f32 // Mock battery drain
        };

        let duration = start_time.elapsed();

        let avg_power = power_samples.iter().sum::<f32>() / power_samples.len() as f32;
        let peak_power = power_samples.iter().fold(0.0f32, |acc, &x| acc.max(x));
        let energy_consumed = avg_power * duration.as_secs_f32() / 3600.0; // Convert to mWh
        let energy_per_inference = if total_inferences > 0 {
            energy_consumed * 3.6 / total_inferences as f32 // Convert to mJ
        } else {
            0.0
        };

        let battery_drain_rate =
            (initial_battery - final_battery) * 100.0 / duration.as_secs_f32() * 3600.0;

        results.push(BatteryTestResult {
            duration,
            initial_battery_level: initial_battery,
            final_battery_level: final_battery,
            energy_consumed_mwh: energy_consumed,
            avg_power_consumption_mw: avg_power,
            peak_power_consumption_mw: peak_power,
            total_inferences,
            energy_per_inference_mj: energy_per_inference,
            battery_drain_rate_percent_per_hour: battery_drain_rate,
        });

        Ok(results)
    }

    /// Run stress tests
    async fn run_stress_tests(&mut self) -> Result<Vec<StressTestResult>> {
        let config = self.config.stress_test_config.clone();
        let mut results = Vec::new();

        let stress_types = vec![StressType::CPU, StressType::Memory, StressType::Thermal];

        for stress_type in stress_types {
            if let Ok(result) = self.run_single_stress_test(stress_type, &config).await {
                results.push(result);
            }
        }

        Ok(results)
    }

    /// Run a single stress test
    async fn run_single_stress_test(
        &mut self,
        stress_type: StressType,
        config: &StressTestConfig,
    ) -> Result<StressTestResult> {
        {
            let mut state = self.test_state.lock().expect("Operation failed");
            state.current_test = Some(format!("Stress Test {:?}", stress_type));
        }

        let start_time = Instant::now();
        let mut successful_inferences = 0;
        let mut total_attempts = 0;
        let mut latencies = Vec::new();
        let mut error_count = 0;

        // Apply stress based on type
        let stress_threads = match stress_type {
            StressType::CPU => Some(self.apply_cpu_stress(config.cpu_stress_level)),
            StressType::Memory => Some(self.apply_memory_stress(config.memory_stress_level)),
            StressType::Thermal => {
                // For thermal stress, we'll monitor thermal conditions using the thermal manager
                if let Some(ref thermal_manager) = self.thermal_manager {
                    // Start thermal monitoring using the implemented API
                    tracing::info!("Starting enhanced thermal stress monitoring");

                    // Monitor thermal conditions and log current readings
                    if let Ok(thermal_reading) = thermal_manager.get_current_reading() {
                        tracing::info!(
                            "Current thermal state: {}°C, State: {:?}",
                            thermal_reading.temperature_celsius,
                            thermal_reading.thermal_state
                        );
                    }

                    // Get current power consumption for thermal stress analysis
                    if let Some(current_power) = thermal_manager.get_current_power() {
                        tracing::info!(
                            "Current power consumption during thermal stress: {:.2}mW",
                            current_power
                        );
                    }
                }
                None // No additional stress threads needed for thermal monitoring
            },
            _ => None,
        };

        // Run test under stress
        while start_time.elapsed() < config.test_duration {
            let test_input = self.create_test_input();
            if let Some(engine) = &mut self.inference_engine {
                let inference_start = Instant::now();

                match engine.inference(&test_input) {
                    Ok(_) => {
                        successful_inferences += 1;
                        latencies.push(inference_start.elapsed().as_secs_f32() * 1000.0);
                    },
                    Err(_) => {
                        error_count += 1;
                    },
                }
                total_attempts += 1;
            }

            tokio::time::sleep(Duration::from_millis(10)).await;
        }

        // Stop stress threads
        if let Some(handles) = stress_threads {
            for handle in handles {
                handle.join().unwrap_or(());
            }
        }

        let success_rate = if total_attempts > 0 {
            successful_inferences as f32 / total_attempts as f32
        } else {
            0.0
        };

        let avg_latency = if !latencies.is_empty() {
            latencies.iter().sum::<f32>() / latencies.len() as f32
        } else {
            0.0
        };

        let error_rate = if total_attempts > 0 {
            error_count as f32 / total_attempts as f32
        } else {
            0.0
        };

        Ok(StressTestResult {
            duration: start_time.elapsed(),
            stress_type,
            success_rate,
            avg_latency_ms: avg_latency,
            memory_pressure_level: config.memory_stress_level,
            cpu_utilization: config.cpu_stress_level,
            gpu_utilization: 0.5, // Estimated
            thermal_throttling_events: 0,
            memory_allocation_failures: error_count,
            error_rate,
        })
    }

    /// Run memory tests
    async fn run_memory_tests(&mut self) -> Result<Vec<MemoryTestResult>> {
        let config = self.config.memory_test_config.clone();
        let mut results = Vec::new();

        let test_types = vec![
            MemoryTestType::LeakDetection,
            MemoryTestType::PressureTesting,
            MemoryTestType::AllocationStress,
        ];

        for test_type in test_types {
            if let Ok(result) = self.run_single_memory_test(test_type, &config).await {
                results.push(result);
            }
        }

        Ok(results)
    }

    /// Run a single memory test
    async fn run_single_memory_test(
        &mut self,
        test_type: MemoryTestType,
        config: &MemoryTestConfig,
    ) -> Result<MemoryTestResult> {
        {
            let mut state = self.test_state.lock().expect("Operation failed");
            state.current_test = Some(format!("Memory Test {:?}", test_type));
        }

        let start_time = Instant::now();
        let mut peak_memory = 0;
        let mut memory_samples = Vec::new();
        let mut leak_count = 0;

        // Monitor memory during test
        while start_time.elapsed() < config.memory_stress_duration {
            // Simulate memory operations based on test type
            match test_type {
                MemoryTestType::LeakDetection
                    // Simulate potential memory leaks
                    if start_time.elapsed().as_secs().is_multiple_of(10) => {
                        leak_count += self.detect_memory_leaks();
                    },
                MemoryTestType::PressureTesting => {
                    // Apply memory pressure
                    let _pressure_data = self.apply_memory_pressure();
                },
                MemoryTestType::AllocationStress => {
                    // Stress allocation system
                    let _allocations = self.stress_memory_allocation();
                },
                _ => {},
            }

            let current_memory = self.estimate_memory_usage();
            memory_samples.push(current_memory);
            peak_memory = peak_memory.max(current_memory);

            tokio::time::sleep(Duration::from_millis(100)).await;
        }

        let avg_memory = if !memory_samples.is_empty() {
            memory_samples.iter().sum::<usize>() / memory_samples.len()
        } else {
            0
        };

        Ok(MemoryTestResult {
            duration: start_time.elapsed(),
            test_type,
            peak_memory_usage_mb: peak_memory,
            avg_memory_usage_mb: avg_memory,
            memory_leaks_detected: leak_count,
            memory_stats: MemoryUsageStats {
                total_allocated_mb: avg_memory,
                peak_allocated_mb: peak_memory,
                fragmentation_percent: 15.0, // Estimated
                large_allocations: 10,
                small_allocations: 100,
            },
            gc_stats: Some(HashMap::from([
                ("gc_cycles".to_string(), 5.0),
                ("gc_time_ms".to_string(), 50.0),
            ])),
            allocation_success_rate: 0.95,
        })
    }

    // Helper methods
    fn create_test_input(&self) -> Tensor {
        let test_data = vec![0.5f32; 224 * 224 * 3];
        Tensor::from_vec(test_data, &[1, 224, 224, 3]).expect("Operation failed")
    }

    fn create_mock_accuracy_metrics(&self) -> AccuracyMetrics {
        AccuracyMetrics {
            top1_accuracy: 92.5,
            top5_accuracy: 98.2,
            f1_score: 0.925,
            precision: 0.930,
            recall: 0.920,
            mean_average_precision: 0.890,
        }
    }

    fn create_mock_power_stats(&self) -> PowerConsumptionStats {
        PowerConsumptionStats {
            cpu_power_mw: 300.0,
            gpu_power_mw: 500.0,
            memory_power_mw: 100.0,
            total_power_mw: 900.0,
            efficiency_score: 0.85,
        }
    }

    fn estimate_power_consumption(&self) -> f32 {
        // Simplified power estimation
        450.0 + (rand::random::<f32>() - 0.5) * 100.0
    }

    fn estimate_memory_usage(&self) -> usize {
        // Simplified memory usage estimation in MB
        256 + ((rand::random::<f32>() * 256.0) as usize)
    }

    fn apply_cpu_stress(&self, stress_level: f32) -> Vec<thread::JoinHandle<()>> {
        let num_threads = (num_cpus::get() as f32 * stress_level) as usize;
        (0..num_threads)
            .map(|_| {
                thread::spawn(move || {
                    let start = Instant::now();
                    while start.elapsed() < Duration::from_secs(60) {
                        // CPU intensive work
                        let _result: f64 = (0..1000).map(|i| (i as f64).sin()).sum();
                    }
                })
            })
            .collect()
    }

    fn apply_memory_stress(&self, stress_level: f32) -> Vec<thread::JoinHandle<()>> {
        let num_threads = 2;
        (0..num_threads)
            .map(|_| {
                let stress = stress_level;
                thread::spawn(move || {
                    let allocation_size = ((1024 * 1024) as f32 * stress) as usize;
                    let mut allocations = Vec::new();

                    for _ in 0..10 {
                        let data = vec![0u8; allocation_size];
                        allocations.push(data);
                        thread::sleep(Duration::from_millis(100));
                    }
                })
            })
            .collect()
    }

    fn detect_memory_leaks(&self) -> usize {
        // Simplified leak detection
        if rand::random::<f32>() < 0.1 {
            1
        } else {
            0
        }
    }

    fn apply_memory_pressure(&self) -> Vec<Vec<u8>> {
        // Apply memory pressure by allocating large chunks
        (0..5).map(|_| vec![0u8; 1024 * 1024]).collect()
    }

    fn stress_memory_allocation(&self) -> Vec<Vec<u8>> {
        // Stress the allocation system with many small allocations
        (0..1000).map(|i| vec![i as u8; 1024]).collect()
    }
}

// Add simple random number generation for mock data
mod rand {
    use std::sync::atomic::{AtomicU32, Ordering};

    static SEED: AtomicU32 = AtomicU32::new(42);

    pub fn random<T>() -> T
    where
        T: From<f32>,
    {
        let current = SEED.load(Ordering::Relaxed);
        let next = current.wrapping_mul(1664525).wrapping_add(1013904223);
        SEED.store(next, Ordering::Relaxed);
        T::from((next as f32) / (u32::MAX as f32))
    }
}

// Add num_cpus mock
mod num_cpus {
    pub fn get() -> usize {
        4 // Mock CPU count
    }
}