🔧 Tests and benchmarks #16
@ -1,15 +1,15 @@
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use manifold::*;
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use rand::Rng;
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use criterion::Throughput;
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use criterion::Throughput;
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use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
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use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
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use manifold::*;
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use rand::Rng;
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fn random_tensor_r2_manifold() -> Tensor<f64, 2> {
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fn random_tensor_r2_manifold() -> Tensor<f64, 2> {
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let mut rng = rand::thread_rng();
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let mut rng = rand::thread_rng();
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let mut tensor = tensor!([[0.0; 1000]; 1000]);
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let mut tensor = tensor!([[0.0; 1000]; 1000]);
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for i in 0..tensor.len() {
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for i in 0..tensor.len() {
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tensor[i] = rng.gen();
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tensor[i] = rng.gen();
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}
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}
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tensor
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tensor
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}
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}
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fn random_tensor_r2_ndarray() -> ndarray::Array2<f64> {
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fn random_tensor_r2_ndarray() -> ndarray::Array2<f64> {
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@ -25,37 +25,42 @@ fn random_tensor_r2_ndarray() -> ndarray::Array2<f64> {
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}
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}
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fn tensor_product(c: &mut Criterion) {
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fn tensor_product(c: &mut Criterion) {
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let b = 1000;
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let b = 1000;
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let mut group = c.benchmark_group("element-wise addition");
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let mut group = c.benchmark_group("element-wise addition");
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for (i, size) in [b].iter().enumerate() {
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for (i, size) in [b].iter().enumerate() {
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group.throughput(Throughput::Elements(*size as u64));
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group.throughput(Throughput::Elements(*size as u64));
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group.bench_with_input(BenchmarkId::new("manifold", size), &i, |b, _| {
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group.bench_with_input(
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b.iter(|| {
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BenchmarkId::new("manifold", size),
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let a = random_tensor_r2_manifold();
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&i,
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let b = random_tensor_r2_manifold();
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|b, _| {
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let c = a + b;
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b.iter(|| {
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assert!(c.shape().as_array() == &[1000, 1000]);
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let a = random_tensor_r2_manifold();
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})
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let b = random_tensor_r2_manifold();
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});
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let c = a + b;
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assert!(c.shape().as_array() == &[1000, 1000]);
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})
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},
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);
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group.bench_with_input(BenchmarkId::new("ndarray", size), &i, |b, _| {
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group.bench_with_input(
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b.iter(|| {
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BenchmarkId::new("ndarray", size),
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let a = random_tensor_r2_ndarray();
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&i,
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let b = random_tensor_r2_ndarray();
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|b, _| {
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let c = a + b;
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b.iter(|| {
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assert!(c.shape() == &[1000, 1000]);
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let a = random_tensor_r2_ndarray();
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})
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let b = random_tensor_r2_ndarray();
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});
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let c = a + b;
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}
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assert!(c.shape() == &[1000, 1000]);
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group.finish();
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})
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},
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);
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}
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group.finish();
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}
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}
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criterion_group!(
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criterion_group!(benches, tensor_product);
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benches,
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tensor_product
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);
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criterion_main!(benches);
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criterion_main!(benches);
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@ -1 +1 @@
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mod basic_tests;
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mod basic_tests;
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