Struct OptimizerBenchmarks 

pub struct OptimizerBenchmarks { /* private fields */ }

Optimizer benchmark suite

Implementations

impl OptimizerBenchmarks

pub fn new() -> Self

Create a new benchmark suite

pub fn with_config(config: BenchmarkConfig) -> Self

Create a new benchmark suite with custom configuration

pub fn benchmark_step_performance<O: Optimizer>( &self, optimizer: O, problem_size: usize, ) -> OptimizerResult<BenchmarkResult>

Benchmark optimizer step performance

pub fn benchmark_quadratic_convergence<O: Optimizer>( &self, optimizer: O, dimension: usize, ) -> OptimizerResult<BenchmarkResult>

Benchmark convergence on quadratic function

pub fn benchmark_memory_scaling<O: Optimizer + Clone>( &self, optimizer_factory: impl Fn(Vec<Tensor>) -> OptimizerResult<O>, ) -> OptimizerResult<Vec<BenchmarkResult>>

Benchmark memory usage scaling

pub fn benchmark_sparse_gradients<O: Optimizer>( &self, optimizer: O, total_params: usize, sparsity: f32, ) -> OptimizerResult<BenchmarkResult>

Benchmark sparse gradient handling

pub fn run_comprehensive_benchmarks<O: Optimizer + Clone>( &self, optimizer: O, ) -> OptimizerResult<Vec<BenchmarkResult>>

Run comprehensive benchmark suite

pub fn print_results(&self, results: &[BenchmarkResult])

Print benchmark results in a formatted table

pub fn benchmark_noisy_quadratic_convergence<O: Optimizer>( &self, optimizer: O, dimension: usize, noise_level: f32, ) -> OptimizerResult<BenchmarkResult>

Benchmark noisy quadratic convergence (more realistic optimization scenario)

pub fn benchmark_rosenbrock_optimization<O: Optimizer>( &self, optimizer: O, dimension: usize, ) -> OptimizerResult<BenchmarkResult>

Benchmark Rosenbrock function optimization (classic non-convex benchmark)

Trait Implementations

impl Default for OptimizerBenchmarks

fn default() -> Self

Returns the “default value” for a type.