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style: apply rustfmt across all crates and demos

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Consistent formatting pass: line wrapping, import sorting, trailing
whitespace removal, let-chain indentation, merged derive attributes,
and unsafe block reformatting.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
This commit is contained in:
osobh
2026-04-12 07:01:58 -07:00
co-authored by Claude Opus 4.6
parent bc88a14fa1
commit 02d382d5f6
302 changed files with 1805 additions and 1590 deletions
Download Patch File Download Diff File Expand all files Collapse all files
demos/rtx-neural-operator-demo/src/benchmark.rs
+34 -31
View File
@@ -59,7 +59,7 @@ impl Default for BenchmarkConfig {
impl BenchmarkConfig {
/// Create config for quick benchmarking (fewer problems, lower resolutions)
#[must_use]
#[must_use]
pub fn quick() -> Self {
Self {
resolutions: vec![32, 64],
@@ -71,7 +71,7 @@ impl BenchmarkConfig {
}
/// Create config for comprehensive benchmarking
#[must_use]
#[must_use]
pub fn comprehensive() -> Self {
Self {
resolutions: vec![32, 64, 128, 256],
@@ -83,7 +83,7 @@ impl BenchmarkConfig {
}
/// Set PDE type
#[must_use]
#[must_use]
pub fn with_pde_type(mut self, pde_type: PDEType) -> Self {
self.pde_type = pde_type;
self
@@ -103,7 +103,7 @@ pub enum PDEType {
impl PDEType {
/// Get human-readable name
#[must_use]
#[must_use]
pub fn name(&self) -> &'static str {
match self {
Self::Poisson => "Poisson",
@@ -154,35 +154,35 @@ impl BenchmarkResult {
}
/// Set solve time
#[must_use]
#[must_use]
pub fn with_time(mut self, time_ms: f64) -> Self {
self.solve_time_ms = time_ms;
self
}
/// Set L2 error
#[must_use]
#[must_use]
pub fn with_l2_error(mut self, error: f64) -> Self {
self.l2_error = Some(error);
self
}
/// Set max error
#[must_use]
#[must_use]
pub fn with_max_error(mut self, error: f64) -> Self {
self.max_error = Some(error);
self
}
/// Set memory usage
#[must_use]
#[must_use]
pub fn with_memory(mut self, memory_mb: f64) -> Self {
self.memory_mb = memory_mb;
self
}
/// Set iterations
#[must_use]
#[must_use]
pub fn with_iterations(mut self, iterations: usize) -> Self {
self.iterations = Some(iterations);
self
@@ -253,7 +253,7 @@ impl BenchmarkSummary {
}
/// Compute speedup factor vs another solver
#[must_use]
#[must_use]
pub fn speedup_vs(&self, other: &Self) -> f64 {
other.avg_time_ms / self.avg_time_ms
}
@@ -290,7 +290,7 @@ pub struct FdmSolver {
impl FdmSolver {
/// Create a new FDM solver
#[must_use]
#[must_use]
pub fn new(resolution: usize) -> Self {
let h = 1.0 / (resolution - 1) as f64;
Self {
@@ -302,14 +302,14 @@ impl FdmSolver {
}
/// Set maximum iterations
#[must_use]
#[must_use]
pub fn with_max_iterations(mut self, max_iter: usize) -> Self {
self.max_iterations = max_iter;
self
}
/// Set convergence tolerance
#[must_use]
#[must_use]
pub fn with_tolerance(mut self, tol: f64) -> Self {
self.tolerance = tol;
self
@@ -322,7 +322,7 @@ impl FdmSolver {
///
/// # Returns
/// Tuple of (solution, iterations)
#[must_use]
#[must_use]
pub fn solve_jacobi(&self, rhs: &[f64]) -> (Vec<f64>, usize) {
let n = self.resolution;
let h2 = self.h * self.h;
@@ -367,7 +367,7 @@ impl FdmSolver {
}
/// Solve using Gauss-Seidel iteration (faster convergence than Jacobi).
#[must_use]
#[must_use]
pub fn solve_gauss_seidel(&self, rhs: &[f64]) -> (Vec<f64>, usize) {
let n = self.resolution;
let h2 = self.h * self.h;
@@ -410,7 +410,7 @@ impl FdmSolver {
/// Solve using Successive Over-Relaxation (SOR) - even faster convergence.
///
/// Optimal omega for Poisson on unit square: ω = 2 / (1 + sin(π*h))
#[must_use]
#[must_use]
pub fn solve_sor(&self, rhs: &[f64], omega: Option<f64>) -> (Vec<f64>, usize) {
let n = self.resolution;
let h2 = self.h * self.h;
@@ -462,7 +462,7 @@ impl FdmSolver {
}
/// Estimate memory usage in MB
#[must_use]
#[must_use]
pub fn memory_usage_mb(&self) -> f64 {
// Two N×N arrays of f64 (8 bytes each)
2.0 * (self.resolution * self.resolution * 8) as f64 / (1024.0 * 1024.0)
@@ -492,7 +492,7 @@ pub struct FemSolver {
impl FemSolver {
/// Create a new FEM solver
#[must_use]
#[must_use]
pub fn new(resolution: usize) -> Self {
let h = 1.0 / (resolution - 1) as f64;
Self {
@@ -504,14 +504,14 @@ impl FemSolver {
}
/// Set maximum iterations
#[must_use]
#[must_use]
pub fn with_max_iterations(mut self, max_iter: usize) -> Self {
self.max_iterations = max_iter;
self
}
/// Set convergence tolerance
#[must_use]
#[must_use]
pub fn with_tolerance(mut self, tol: f64) -> Self {
self.tolerance = tol;
self
@@ -527,7 +527,7 @@ impl FemSolver {
///
/// # Returns
/// Tuple of (solution, iterations)
#[must_use]
#[must_use]
pub fn solve_cg(&self, rhs: &[f64]) -> (Vec<f64>, usize) {
let n = self.resolution;
@@ -649,7 +649,7 @@ impl FemSolver {
}
/// Estimate memory usage in MB
#[must_use]
#[must_use]
pub fn memory_usage_mb(&self) -> f64 {
// Four N×N arrays of f64: x, r, p, ap
4.0 * (self.resolution * self.resolution * 8) as f64 / (1024.0 * 1024.0)
@@ -668,7 +668,7 @@ pub struct BenchmarkRunner {
impl BenchmarkRunner {
/// Create a new benchmark runner
#[must_use]
#[must_use]
pub fn new(config: BenchmarkConfig) -> Self {
Self { config }
}
@@ -676,7 +676,7 @@ impl BenchmarkRunner {
/// Run benchmarks for FDM and FEM solvers
///
/// Note: FNO benchmarks require a trained model and are run separately.
#[must_use]
#[must_use]
pub fn run_classical_benchmarks(&self) -> Vec<BenchmarkResult> {
let mut results = Vec::new();
@@ -792,7 +792,7 @@ impl BenchmarkRunner {
}
/// Run multiple benchmark iterations and compute summary statistics
#[must_use]
#[must_use]
pub fn run_with_statistics(&self, n_runs: usize) -> Vec<BenchmarkSummary> {
let mut all_results: Vec<Vec<BenchmarkResult>> = Vec::new();
@@ -833,9 +833,11 @@ impl BenchmarkRunner {
for result in results {
let l2_str = result
.l2_error.map_or_else(|| "N/A".to_string(), |e| format!("{e:.2e}"));
.l2_error
.map_or_else(|| "N/A".to_string(), |e| format!("{e:.2e}"));
let iter_str = result
.iterations.map_or_else(|| "N/A".to_string(), |i| i.to_string());
.iterations
.map_or_else(|| "N/A".to_string(), |i| i.to_string());
println!(
"{:<12} {:>10} {:>12.2} {:>12} {:>12.2} {:>10}",
@@ -865,7 +867,8 @@ impl BenchmarkRunner {
for summary in summaries {
let l2_str = summary
.avg_l2_error.map_or_else(|| "N/A".to_string(), |e| format!("{e:.2e}"));
.avg_l2_error
.map_or_else(|| "N/A".to_string(), |e| format!("{e:.2e}"));
println!(
"{:<12} {:>10} {:>10.2}ms {:>10.2}ms {:>12}",
@@ -891,7 +894,7 @@ impl BenchmarkRunner {
///
/// # Returns
/// Benchmark result with timing and error metrics
#[must_use]
#[must_use]
pub fn benchmark_fno(&self, model: &FNO2d<CpuBackend>, resolution: usize) -> BenchmarkResult {
let device = CpuDevice::default();
@@ -991,7 +994,7 @@ impl BenchmarkRunner {
///
/// # Returns
/// Vector of benchmark results for all methods and resolutions
#[must_use]
#[must_use]
pub fn run_all_benchmarks(&self, model: Option<&FNO2d<CpuBackend>>) -> Vec<BenchmarkResult> {
let mut results = Vec::new();
@@ -1019,7 +1022,7 @@ impl BenchmarkRunner {
/// Compute speedup factors comparing FNO to classical methods
///
/// Returns a formatted string summarizing speedup results.
#[must_use]
#[must_use]
pub fn compute_speedup_report(results: &[BenchmarkResult]) -> String {
let mut report = String::new();
report.push('\n');