Update types because change in shape as_array
Signed-off-by: Julius Koskela <julius.koskela@unikie.com>
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23
src/index.rs
23
src/index.rs
@ -1,8 +1,8 @@
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use super::*;
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use getset::{Getters, MutGetters};
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use std::{
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ops::{Index, IndexMut, Add, Sub},
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cmp::Ordering,
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ops::{Add, Index, IndexMut, Sub},
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};
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#[derive(Clone, Copy, Debug, Getters, MutGetters)]
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@ -16,7 +16,6 @@ pub struct TensorIndex<const R: usize> {
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// ---- Construction and Initialization ---------------------------------------
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impl<const R: usize> TensorIndex<R> {
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pub fn new(shape: TensorShape<R>, indices: [usize; R]) -> Self {
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if !shape.check_indices(indices) {
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panic!("indices out of bounds");
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@ -67,9 +66,7 @@ impl<const R: usize> TensorIndex<R> {
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}
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let shape = self.shape().as_array().clone();
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let mut carry = 1;
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for (i, &dim_size) in
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self.indices.iter_mut().zip(&shape).rev()
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{
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for (i, &dim_size) in self.indices.iter_mut().zip(&shape).rev() {
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if carry == 1 {
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*i += 1;
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if *i >= dim_size {
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@ -160,9 +157,7 @@ impl<const R: usize> TensorIndex<R> {
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let mut borrow = true;
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let shape = self.shape().as_array().clone();
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for (i, &dim_size) in
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self.indices_mut().iter_mut().zip(&shape).rev()
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{
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for (i, &dim_size) in self.indices_mut().iter_mut().zip(&shape).rev() {
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if borrow {
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if *i == 0 {
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*i = dim_size - 1; // Wrap around to the maximum index of
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@ -346,18 +341,14 @@ impl<const R: usize> IndexMut<usize> for TensorIndex<R> {
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}
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}
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impl<const R: usize> From<(TensorShape<R>, [usize; R])>
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for TensorIndex<R>
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{
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impl<const R: usize> From<(TensorShape<R>, [usize; R])> for TensorIndex<R> {
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fn from((shape, indices): (TensorShape<R>, [usize; R])) -> Self {
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assert!(shape.check_indices(indices));
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Self::new(shape, indices)
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}
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}
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impl<const R: usize> From<(TensorShape<R>, usize)>
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for TensorIndex<R>
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{
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impl<const R: usize> From<(TensorShape<R>, usize)> for TensorIndex<R> {
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fn from((shape, flat_index): (TensorShape<R>, usize)) -> Self {
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let indices = shape.index_from_flat(flat_index).indices;
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Self::new(shape, indices)
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@ -370,9 +361,7 @@ impl<const R: usize> From<TensorShape<R>> for TensorIndex<R> {
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}
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}
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impl<T: Value, const R: usize> From<Tensor<T, R>>
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for TensorIndex<R>
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{
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impl<T: Value, const R: usize> From<Tensor<T, R>> for TensorIndex<R> {
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fn from(tensor: Tensor<T, R>) -> Self {
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Self::zero(tensor.shape().clone())
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}
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@ -9,7 +9,7 @@ pub mod shape;
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pub mod tensor;
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pub mod value;
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pub use {value::*, axis::*, error::*, index::*, shape::*, tensor::*};
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pub use {axis::*, error::*, index::*, shape::*, tensor::*, value::*};
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#[macro_export]
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macro_rules! tensor {
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@ -1,8 +1,8 @@
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use super::*;
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use core::result::Result as SerdeResult;
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use serde::de::{self, Deserialize, Deserializer, SeqAccess, Visitor};
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use serde::ser::{Serialize, SerializeTuple, Serializer};
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use std::fmt::{Result as FmtResult, Formatter};
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use core::result::Result as SerdeResult;
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use std::fmt::{Formatter, Result as FmtResult};
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#[derive(Clone, Copy, Debug)]
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pub struct TensorShape<const R: usize>([usize; R]);
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@ -632,7 +632,12 @@ where
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T: Display + Clone,
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{
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fn fmt(&self, f: &mut Formatter<'_>) -> FmtResult {
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Tensor::<T, R>::fmt_helper(&self.buffer, &self.shape().as_array().clone(), f, 1)
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Tensor::<T, R>::fmt_helper(
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&self.buffer,
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&self.shape().as_array().clone(),
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f,
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1,
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)
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}
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}
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@ -1,9 +1,6 @@
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use num::{Num, One, Zero};
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use serde::{Deserialize, Serialize};
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use std::{
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fmt::Display,
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iter::Sum,
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};
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use std::{fmt::Display, iter::Sum};
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/// A trait for types that can be used as values in a tensor.
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pub trait Value:
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