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Merged
merged 2 commits into from
Apr 26, 2023
Merged

Remove some allocations #262

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4ea183b
Remove some allocations
rubdos Apr 22, 2023
255127a
Remove some more allocations
rubdos Apr 22, 2023
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20 changes: 20 additions & 0 deletions src/linalg/basic/vector.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,25 @@ pub struct VecView<'a, T: Debug + Display + Copy + Sized> {
ptr: &'a [T],
}

impl<T: Debug + Display + Copy + Sized> Array<T, usize> for &[T] {
fn get(&self, i: usize) -> &T {
&self[i]
}

fn shape(&self) -> usize {
self.len()
}

fn is_empty(&self) -> bool {
self.len() > 0
}

fn iterator<'b>(&'b self, axis: u8) -> Box<dyn Iterator<Item = &'b T> + 'b> {
assert!(axis == 0, "For one dimensional array `axis` should == 0");
Box::new(self.iter())
}
}

impl<T: Debug + Display + Copy + Sized> Array<T, usize> for Vec<T> {
fn get(&self, i: usize) -> &T {
&self[i]
Expand Down Expand Up @@ -46,6 +65,7 @@ impl<T: Debug + Display + Copy + Sized> MutArray<T, usize> for Vec<T> {
}

impl<T: Debug + Display + Copy + Sized> ArrayView1<T> for Vec<T> {}
impl<T: Debug + Display + Copy + Sized> ArrayView1<T> for &[T] {}

impl<T: Debug + Display + Copy + Sized> MutArrayView1<T> for Vec<T> {}

Expand Down
119 changes: 55 additions & 64 deletions src/svm/svc.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -322,19 +322,26 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX> + 'a, Y: Array
let (n, _) = x.shape();
let mut y_hat: Vec<TX> = Array1::zeros(n);

let mut row = Vec::with_capacity(n);
for i in 0..n {
let row_pred: TX =
self.predict_for_row(Vec::from_iterator(x.get_row(i).iterator(0).copied(), n));
row.clear();
row.extend(x.get_row(i).iterator(0).copied());
let row_pred: TX = self.predict_for_row(&row);
y_hat.set(i, row_pred);
}

Ok(y_hat)
}

fn predict_for_row(&self, x: Vec<TX>) -> TX {
fn predict_for_row(&self, x: &[TX]) -> TX {
let mut f = self.b.unwrap();

let xi: Vec<_> = x.iter().map(|e| e.to_f64().unwrap()).collect();
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@morenol morenol Apr 25, 2023

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good catch!

for i in 0..self.instances.as_ref().unwrap().len() {
let xj: Vec<_> = self.instances.as_ref().unwrap()[i]
.iter()
.map(|e| e.to_f64().unwrap())
.collect();
f += self.w.as_ref().unwrap()[i]
* TX::from(
self.parameters
Expand All @@ -343,13 +350,7 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX> + 'a, Y: Array
.kernel
.as_ref()
.unwrap()
.apply(
&x.iter().map(|e| e.to_f64().unwrap()).collect(),
&self.instances.as_ref().unwrap()[i]
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
)
.apply(&xi, &xj)
.unwrap(),
)
.unwrap();
Expand Down Expand Up @@ -472,14 +473,12 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
let tol = self.parameters.tol;
let good_enough = TX::from_i32(1000).unwrap();

let mut x = Vec::with_capacity(n);
for _ in 0..self.parameters.epoch {
for i in self.permutate(n) {
self.process(
i,
Vec::from_iterator(self.x.get_row(i).iterator(0).copied(), n),
*self.y.get(i),
&mut cache,
);
x.clear();
x.extend(self.x.get_row(i).iterator(0).take(n).copied());
self.process(i, &x, *self.y.get(i), &mut cache);
loop {
self.reprocess(tol, &mut cache);
self.find_min_max_gradient();
Expand Down Expand Up @@ -511,24 +510,17 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
let mut cp = 0;
let mut cn = 0;

let mut x = Vec::with_capacity(n);
for i in self.permutate(n) {
x.clear();
x.extend(self.x.get_row(i).iterator(0).take(n).copied());
if *self.y.get(i) == TY::one() && cp < few {
if self.process(
i,
Vec::from_iterator(self.x.get_row(i).iterator(0).copied(), n),
*self.y.get(i),
cache,
) {
if self.process(i, &x, *self.y.get(i), cache) {
cp += 1;
}
} else if *self.y.get(i) == TY::from(-1).unwrap()
&& cn < few
&& self.process(
i,
Vec::from_iterator(self.x.get_row(i).iterator(0).copied(), n),
*self.y.get(i),
cache,
)
&& self.process(i, &x, *self.y.get(i), cache)
{
cn += 1;
}
Expand All @@ -539,7 +531,7 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
}
}

fn process(&mut self, i: usize, x: Vec<TX>, y: TY, cache: &mut Cache<TX, TY, X, Y>) -> bool {
fn process(&mut self, i: usize, x: &[TX], y: TY, cache: &mut Cache<TX, TY, X, Y>) -> bool {
for j in 0..self.sv.len() {
if self.sv[j].index == i {
return true;
Expand All @@ -551,15 +543,14 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
let mut cache_values: Vec<((usize, usize), TX)> = Vec::new();

for v in self.sv.iter() {
let xi: Vec<_> = v.x.iter().map(|e| e.to_f64().unwrap()).collect();
let xj: Vec<_> = x.iter().map(|e| e.to_f64().unwrap()).collect();
let k = self
.parameters
.kernel
.as_ref()
.unwrap()
.apply(
&v.x.iter().map(|e| e.to_f64().unwrap()).collect(),
&x.iter().map(|e| e.to_f64().unwrap()).collect(),
)
.apply(&xi, &xj)
.unwrap();
cache_values.push(((i, v.index), TX::from(k).unwrap()));
g -= v.alpha * k;
Expand All @@ -578,7 +569,7 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
cache.insert(v.0, v.1.to_f64().unwrap());
}

let x_f64 = x.iter().map(|e| e.to_f64().unwrap()).collect();
let x_f64: Vec<_> = x.iter().map(|e| e.to_f64().unwrap()).collect();
let k_v = self
.parameters
.kernel
Expand Down Expand Up @@ -701,8 +692,10 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
let km = sv1.k;
let gm = sv1.grad;
let mut best = 0f64;
let xi: Vec<_> = sv1.x.iter().map(|e| e.to_f64().unwrap()).collect();
for i in 0..self.sv.len() {
let v = &self.sv[i];
let xj: Vec<_> = v.x.iter().map(|e| e.to_f64().unwrap()).collect();
let z = v.grad - gm;
let k = cache.get(
sv1,
Expand All @@ -711,10 +704,7 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
.kernel
.as_ref()
.unwrap()
.apply(
&sv1.x.iter().map(|e| e.to_f64().unwrap()).collect(),
&v.x.iter().map(|e| e.to_f64().unwrap()).collect(),
)
.apply(&xi, &xj)
.unwrap(),
);
let mut curv = km + v.k - 2f64 * k;
Expand All @@ -732,6 +722,12 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
}
}

let xi: Vec<_> = self.sv[idx_1]
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect::<Vec<_>>();

idx_2.map(|idx_2| {
(
idx_1,
Expand All @@ -742,16 +738,12 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
.as_ref()
.unwrap()
.apply(
&self.sv[idx_1]
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
&xi,
&self.sv[idx_2]
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
.collect::<Vec<_>>(),
)
.unwrap()
}),
Expand All @@ -765,8 +757,11 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
let km = sv2.k;
let gm = sv2.grad;
let mut best = 0f64;

let xi: Vec<_> = sv2.x.iter().map(|e| e.to_f64().unwrap()).collect();
for i in 0..self.sv.len() {
let v = &self.sv[i];
let xj: Vec<_> = v.x.iter().map(|e| e.to_f64().unwrap()).collect();
let z = gm - v.grad;
let k = cache.get(
sv2,
Expand All @@ -775,10 +770,7 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
.kernel
.as_ref()
.unwrap()
.apply(
&sv2.x.iter().map(|e| e.to_f64().unwrap()).collect(),
&v.x.iter().map(|e| e.to_f64().unwrap()).collect(),
)
.apply(&xi, &xj)
.unwrap(),
);
let mut curv = km + v.k - 2f64 * k;
Expand All @@ -797,6 +789,12 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
}
}

let xj: Vec<_> = self.sv[idx_2]
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect();

idx_1.map(|idx_1| {
(
idx_1,
Expand All @@ -811,12 +809,8 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
&self.sv[idx_2]
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
.collect::<Vec<_>>(),
&xj,
)
.unwrap()
}),
Expand All @@ -835,12 +829,12 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
.collect::<Vec<_>>(),
&self.sv[idx_2]
.x
.iter()
.map(|e| e.to_f64().unwrap())
.collect(),
.collect::<Vec<_>>(),
)
.unwrap(),
)),
Expand Down Expand Up @@ -895,18 +889,18 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
self.sv[v1].alpha -= step.to_f64().unwrap();
self.sv[v2].alpha += step.to_f64().unwrap();

let xi_v1: Vec<_> = self.sv[v1].x.iter().map(|e| e.to_f64().unwrap()).collect();
let xi_v2: Vec<_> = self.sv[v2].x.iter().map(|e| e.to_f64().unwrap()).collect();
for i in 0..self.sv.len() {
let xj: Vec<_> = self.sv[i].x.iter().map(|e| e.to_f64().unwrap()).collect();
let k2 = cache.get(
&self.sv[v2],
&self.sv[i],
self.parameters
.kernel
.as_ref()
.unwrap()
.apply(
&self.sv[v2].x.iter().map(|e| e.to_f64().unwrap()).collect(),
&self.sv[i].x.iter().map(|e| e.to_f64().unwrap()).collect(),
)
.apply(&xi_v2, &xj)
.unwrap(),
);
let k1 = cache.get(
Expand All @@ -916,10 +910,7 @@ impl<'a, TX: Number + RealNumber, TY: Number + Ord, X: Array2<TX>, Y: Array1<TY>
.kernel
.as_ref()
.unwrap()
.apply(
&self.sv[v1].x.iter().map(|e| e.to_f64().unwrap()).collect(),
&self.sv[i].x.iter().map(|e| e.to_f64().unwrap()).collect(),
)
.apply(&xi_v1, &xj)
.unwrap(),
);
self.sv[i].grad -= step.to_f64().unwrap() * (k2 - k1);
Expand Down
16 changes: 7 additions & 9 deletions src/svm/svr.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -248,19 +248,20 @@ impl<'a, T: Number + FloatNumber + PartialOrd, X: Array2<T>, Y: Array1<T>> SVR<'

let mut y_hat: Vec<T> = Vec::<T>::zeros(n);

let mut x_i = Vec::with_capacity(n);
for i in 0..n {
y_hat.set(
i,
self.predict_for_row(Vec::from_iterator(x.get_row(i).iterator(0).copied(), n)),
);
x_i.clear();
x_i.extend(x.get_row(i).iterator(0).copied());
y_hat.set(i, self.predict_for_row(&x_i));
}

Ok(y_hat)
}

pub(crate) fn predict_for_row(&self, x: Vec<T>) -> T {
pub(crate) fn predict_for_row(&self, x: &[T]) -> T {
let mut f = self.b;

let xi: Vec<_> = x.iter().map(|e| e.to_f64().unwrap()).collect();
for i in 0..self.instances.as_ref().unwrap().len() {
f += self.w.as_ref().unwrap()[i]
* T::from(
Expand All @@ -270,10 +271,7 @@ impl<'a, T: Number + FloatNumber + PartialOrd, X: Array2<T>, Y: Array1<T>> SVR<'
.kernel
.as_ref()
.unwrap()
.apply(
&x.iter().map(|e| e.to_f64().unwrap()).collect(),
&self.instances.as_ref().unwrap()[i],
)
.apply(&xi, &self.instances.as_ref().unwrap()[i])
.unwrap(),
)
.unwrap()
Expand Down