use smallvec::smallvec;
use crate::{Element, Recordable, Shape, Tensor};
use super::{Cotangents, Operation, Reads, unary};
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub(crate) struct Sum;
impl Sum {
pub(crate) fn arity(&self) -> usize {
1
}
pub(crate) fn reads(&self) -> Reads {
Reads::NOTHING
}
pub(crate) fn infer_shape(&self, _operands: &[Shape]) -> Shape {
Shape::scalar()
}
}
impl Sum {
pub(crate) fn forward<E: Element>(&self, operands: &[&Tensor<E>]) -> Tensor<E> {
unary(operands).sum()
}
}
impl<Rule: Recordable> Operation<Rule> for Sum {
fn backward(&self, operands: &[&Rule], _output: &Rule, gradient: &Rule) -> Cotangents<Rule> {
let &operand = unary(operands);
smallvec![Some(gradient.broadcast(operand.shape()))]
}
}