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use traits;
use std::ops::Mul;
pub struct Rank1Tensor<T: traits::TensorTrait<T>> {
dim: i32,
components: Vec<T>,
}
pub struct Rank2Tensor<T: traits::TensorTrait<T>> {
dim: i32,
components: Vec<Vec<T>>,
}
pub struct Rank3Tensor<T: traits::TensorTrait<T>> {
dim: i32,
components: Vec<Vec<Vec<T>>>,
}
pub struct Tensor<T: traits::TensorTrait<T>> {
dim: i32,
rank: i32,
components: Vec<T>,
}
impl<T: traits::TensorTrait<T>> Tensor<T> {
pub fn build(d: i32, r: i32, v: Vec<T>) -> Self {
Tensor {
dim: d,
rank: r,
components: v,
}
}
pub fn clone(&self) -> Self {
Tensor::build(self.dim.clone(), self.rank.clone(), self.components.clone())
}
pub fn get(&self, indices: &[i32]) -> T {
let mut i: i32 = 0;
for x in 0..self.rank {
i = i + scalar_power(self.dim, x as i32) * indices[x as usize];
}
self.components[i as usize].clone()
}
pub fn set(&mut self, indices: &[i32], value: T) {
let mut i: i32 = 0;
for x in 0..self.rank {
i = i + scalar_power(self.dim, x as i32) * indices[x as usize];
}
self.components[i as usize] = value;
}
pub fn inner_product(&self, other: &Tensor<T>) -> Self {
assert_eq!(self.rank, (*other).rank);
assert_eq!(self.dim, (*other).dim);
let mut args: Vec<i32> = Vec::new();
for _ in 0..(self.rank + other.rank - 2) {
args.push(self.dim);
}
let new_rank: i32 = self.rank + other.rank - 2;
let len = scalar_power(self.dim, new_rank) as usize;
let mut new_tensor = &mut Tensor::build(self.dim, new_rank, vec![T::zero(); len]);
inner_product_loop(args, Tensor::print_inner_product, &self, &other, new_tensor);
(*new_tensor).clone()
}
fn print_inner_product(&mut self, t1: &Tensor<T>, t2: &Tensor<T>, indices: &[i32]) {
let i: usize = (t1.rank - 1) as usize;
let j: usize = (t1.rank - 1) as usize;
let mut v1 = indices[0..i].to_vec();
let mut v2 = indices[j..].to_vec();
v1.push(0);
v2.insert(0, 0);
let mut total: T = T::zero();
for x in 0..t1.dim {
v1[(t1.rank - 1) as usize] = x;
v2[0] = x;
total = total + t1.get(&v1) * t2.get(&v2);
}
self.set(indices, total);
}
pub fn print(&self) {
let mut v: Vec<i32> = Vec::new();
for _ in 0..self.rank {
v.push(self.dim.clone());
}
print_loop(v, Tensor::print_element, &self);
}
fn print_element(&self, v: Vec<i32>) {
println!( "T{:?} : {:?}", v, self.get(&v) );
}
}
pub fn scalar_power(n: i32, p: i32) -> i32 {
let mut a: i32 = 1;
for _ in 0..p { a = a*n; }
a
}
pub fn inner_product_loop<T: traits::TensorTrait<T>>(max_indices: Vec<i32>, f: fn(&mut Tensor<T>, &Tensor<T>, &Tensor<T>, &[i32]),
t1: &Tensor<T>, t2: &Tensor<T>, t3: &mut Tensor<T>) {
inner_product_loop_many(max_indices.clone(), f, t1, t2, t3, Vec::new(), 0);
}
pub fn inner_product_loop_many<T: traits::TensorTrait<T>>(max_indices: Vec<i32>, f: fn(&mut Tensor<T>, &Tensor<T>, &Tensor<T>, &[i32]),
t1: &Tensor<T>, t2: &Tensor<T>, t3: &mut Tensor<T>, pargs: Vec<i32>, index: i32) {
if max_indices.len() == 0 {
f(t3, t1, t2, &pargs);
} else {
let mut args = pargs.clone();
let rest: Vec<i32> = max_indices[1..].to_vec();
for _ in 0..max_indices[0] {
if args.len() == index as usize { args.push(0); }
if args[index as usize] < max_indices[0] {
inner_product_loop_many(rest.clone(), f, t1, t2, t3, args.clone(), index + 1);
args[index as usize] = args[index as usize] + 1;
}
}
}
}
pub fn print_loop<T: traits::TensorTrait<T>>(max_indices: Vec<i32>, f: fn(&Tensor<T>, Vec<i32>), t: &Tensor<T>) {
print_loop_many(max_indices.clone(), f, t, Vec::new(), 0);
}
pub fn print_loop_many<T: traits::TensorTrait<T>>(max_indices: Vec<i32>, f: fn(&Tensor<T>, Vec<i32>),
t: &Tensor<T>, pargs: Vec<i32>, index: i32) {
if max_indices.len() == 0 {
f(t, pargs);
} else {
let mut args = pargs.clone();
let rest: Vec<i32> = max_indices[1..].to_vec();
for _ in 0..max_indices[0] {
if args.len() == index as usize { args.push(0); }
if args[index as usize] < max_indices[0] {
print_loop_many(rest.clone(), f, t, args.clone(), index + 1);
args[index as usize] = args[index as usize] + 1;
}
}
}
}
impl<T: traits::TensorTrait<T>> Rank1Tensor<T> {
pub fn new(d: i32) -> Self {
Rank1Tensor {
dim: d,
components: Vec::new(),
}
}
pub fn build(d: i32, c: Vec<T>) -> Self {
Rank1Tensor {
dim: d,
components: c,
}
}
pub fn get(&self, i: i32) -> T {
self.components[i as usize].clone()
}
pub fn dim(&self) -> i32 {
self.dim.clone()
}
}
impl<T: traits::TensorTrait<T>> Rank2Tensor<T> {
pub fn new(d: i32) -> Self {
let mut temp_vec = Vec::new();
for _ in 0..d {
temp_vec.push(Vec::new());
}
Rank2Tensor {
dim: d,
components: temp_vec,
}
}
pub fn build(d: i32, c: Vec<Vec<T>>) -> Self {
Rank2Tensor {
dim: d,
components: c,
}
}
pub fn get(&self, i: i32, j: i32) -> T {
self.components[i as usize][j as usize].clone()
}
pub fn dim(&self) -> i32 {
self.dim.clone()
}
pub fn print(&self) {
for i in 0..self.dim() {
for j in 0..self.dim() {
print!{ "T[{},{}]: {}\n", i, j, self.get(i, j) };
}
}
}
}
impl<T: traits::TensorTrait<T>> Rank3Tensor<T> {
pub fn new(d: i32) -> Self {
let mut temp_vec = Vec::new();
for _ in 0..d {
let mut temp_vec_2 = Vec::new();
for _ in 0..d {
temp_vec_2.push(Vec::new());
}
temp_vec.push(temp_vec_2);
}
Rank3Tensor {
dim: d,
components: temp_vec,
}
}
pub fn build(d: i32, c: Vec<Vec<Vec<T>>>) -> Self {
Rank3Tensor {
dim: d,
components: c,
}
}
pub fn get(&self, i: i32, j: i32, k: i32) -> T {
self.components[i as usize][j as usize][k as usize].clone()
}
pub fn dim(&self) -> i32 {
self.dim.clone()
}
}
impl<T: traits::TensorTrait<T>> Mul<Rank1Tensor<T>> for Rank1Tensor<T> {
type Output = Rank2Tensor<T>;
fn mul(self, other: Rank1Tensor<T>) -> Rank2Tensor<T> {
let mut vec = Vec::new();
for i in 0..self.dim() {
let mut temp_vec = Vec::new();
for j in 0..other.dim() {
temp_vec.push(self.get(i) * other.get(j))
}
vec.push(temp_vec)
}
Rank2Tensor::build(self.dim(), vec)
}
}