Trait ha_ndarray::NDArray
source · pub trait NDArray: Send + Sync {
type DType: CDatatype;
// Required methods
fn context(&self) -> &Context;
fn shape(&self) -> &[usize];
// Provided methods
fn ndim(&self) -> usize { ... }
fn size(&self) -> usize { ... }
}Expand description
An n-dimensional array
Required Associated Types§
Required Methods§
Provided Methods§
sourcefn size(&self) -> usize
fn size(&self) -> usize
Return the number of elements in this array.
Examples found in repository?
examples/benchmarks.rs (line 65)
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fn matmul(context: &Context) -> Result<(), Error> {
for m in 1..16usize {
let dim = 2usize.pow(m as u32);
let l = ArrayBase::<Vec<_>>::with_context(
context.clone(),
vec![16 * m, dim],
vec![1.0f32; 16 * m * dim],
)?;
let r = ArrayBase::<Vec<_>>::with_context(
context.clone(),
vec![dim, m * 32],
vec![1.0f32; dim * m * 32],
)?;
let num_ops = 16 * 32 * dim;
println!("matmul {:?} with {:?} ({} ops)", l, r, num_ops);
let x = l.matmul(r)?;
let queue = Queue::new(context.clone(), x.size())?;
for _ in 0..ITERATIONS {
let start = Instant::now();
let _output = x.read(&queue)?;
let duration = start.elapsed();
let rate = num_ops as f32 / duration.as_secs_f32();
println!("{:?} us @ {} M/s", duration.as_micros(), rate / 1_000_000.);
}
}
Ok(())
}
fn reduce_sum_axis(context: &Context) -> Result<(), Error> {
let shape = vec![10, 20, 30, 40, 50];
let size = shape.iter().product();
let queue = Queue::new(context.clone(), size)?;
let x = ArrayBase::<Vec<_>>::with_context(context.clone(), shape, vec![1; size])?;
println!("reduce axis {} of {:?} (size {})", 2, x, x.size());
let reduced = x.sum(vec![2], false)?;
for _ in 0..ITERATIONS {
let start = Instant::now();
let _output = reduced.read(&queue)?;
let duration = start.elapsed();
println!("{:?} ms", duration.as_millis());
}
Ok(())
}
fn reduce_sum_all(context: &Context) -> Result<(), Error> {
for m in 2..8 {
let shape = (1..m).map(|dim| dim * 10).collect::<Vec<usize>>();
let size = shape.iter().product();
let x = ArrayBase::<Arc<Vec<_>>>::with_context(
context.clone(),
shape,
Arc::new(vec![1; size]),
)?;
println!("reduce {:?} (size {})...", x, x.size());
for _ in 0..ITERATIONS {
let start = Instant::now();
let _x = x.clone().sum_all()?;
let duration = start.elapsed();
println!("{:?} us", duration.as_micros());
}
}
Ok(())
}