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use crate::{Error, Tensor};
use std::ops::{
Bound, Range, RangeBounds, RangeFrom, RangeFull, RangeInclusive, RangeTo, RangeToInclusive,
};
impl Tensor {
/// Intended to be use by the trait `.i()`
///
/// ```
/// # use candle_core::{Tensor, DType, Device, IndexOp};
/// let a = Tensor::zeros((2, 3), DType::F32, &Device::Cpu)?;
///
/// let c = a.i(0..1)?;
/// assert_eq!(c.shape().dims(), &[1, 3]);
///
/// let c = a.i(0)?;
/// assert_eq!(c.shape().dims(), &[3]);
///
/// let c = a.i((.., ..2) )?;
/// assert_eq!(c.shape().dims(), &[2, 2]);
///
/// let c = a.i((.., ..=2))?;
/// assert_eq!(c.shape().dims(), &[2, 3]);
///
/// # Ok::<(), candle_core::Error>(())
/// ```
fn index(&self, indexers: &[TensorIndexer]) -> Result<Self, Error> {
let mut x = self.clone();
let dims = self.shape().dims();
let mut current_dim = 0;
for (i, indexer) in indexers.iter().enumerate() {
x = match indexer {
TensorIndexer::Select(n) => x.narrow(current_dim, *n, 1)?.squeeze(current_dim)?,
TensorIndexer::Narrow(left_bound, right_bound) => {
let start = match left_bound {
Bound::Included(n) => *n,
Bound::Excluded(n) => *n + 1,
Bound::Unbounded => 0,
};
let stop = match right_bound {
Bound::Included(n) => *n + 1,
Bound::Excluded(n) => *n,
Bound::Unbounded => dims[i],
};
let out = x.narrow(current_dim, start, stop.saturating_sub(start))?;
current_dim += 1;
out
}
TensorIndexer::IndexSelect(indexes) => {
if indexes.rank() != 1 {
crate::bail!("multi-dimensional tensor indexing is not supported")
}
let out = x.index_select(&indexes.to_device(x.device())?, current_dim)?;
current_dim += 1;
out
}
TensorIndexer::Err(e) => crate::bail!("indexing error {e:?}"),
};
}
Ok(x)
}
}
#[derive(Debug)]
/// Generic structure used to index a slice of the tensor
pub enum TensorIndexer {
/// This selects the elements for which an index has some specific value.
Select(usize),
/// This is a regular slice, purely indexing a chunk of the tensor
Narrow(Bound<usize>, Bound<usize>),
/// Indexing via a 1d tensor
IndexSelect(Tensor),
Err(Error),
}
impl From<usize> for TensorIndexer {
fn from(index: usize) -> Self {
TensorIndexer::Select(index)
}
}
impl From<&[u32]> for TensorIndexer {
fn from(index: &[u32]) -> Self {
match Tensor::new(index, &crate::Device::Cpu) {
Ok(tensor) => TensorIndexer::IndexSelect(tensor),
Err(e) => TensorIndexer::Err(e),
}
}
}
impl From<Vec<u32>> for TensorIndexer {
fn from(index: Vec<u32>) -> Self {
let len = index.len();
match Tensor::from_vec(index, len, &crate::Device::Cpu) {
Ok(tensor) => TensorIndexer::IndexSelect(tensor),
Err(e) => TensorIndexer::Err(e),
}
}
}
impl From<&Tensor> for TensorIndexer {
fn from(tensor: &Tensor) -> Self {
TensorIndexer::IndexSelect(tensor.clone())
}
}
trait RB: RangeBounds<usize> {}
impl RB for Range<usize> {}
impl RB for RangeFrom<usize> {}
impl RB for RangeFull {}
impl RB for RangeInclusive<usize> {}
impl RB for RangeTo<usize> {}
impl RB for RangeToInclusive<usize> {}
impl<T: RB> From<T> for TensorIndexer {
fn from(range: T) -> Self {
use std::ops::Bound::*;
let start = match range.start_bound() {
Included(idx) => Included(*idx),
Excluded(idx) => Excluded(*idx),
Unbounded => Unbounded,
};
let end = match range.end_bound() {
Included(idx) => Included(*idx),
Excluded(idx) => Excluded(*idx),
Unbounded => Unbounded,
};
TensorIndexer::Narrow(start, end)
}
}
/// Trait used to implement multiple signatures for ease of use of the slicing
/// of a tensor
pub trait IndexOp<T> {
/// Returns a slicing iterator which are the chunks of data necessary to
/// reconstruct the desired tensor.
fn i(&self, index: T) -> Result<Tensor, Error>;
}
impl<T> IndexOp<T> for Tensor
where
T: Into<TensorIndexer>,
{
///```rust
/// use candle_core::{Tensor, DType, Device, IndexOp};
/// let a = Tensor::new(&[
/// [0., 1.],
/// [2., 3.],
/// [4., 5.]
/// ], &Device::Cpu)?;
///
/// let b = a.i(0)?;
/// assert_eq!(b.shape().dims(), &[2]);
/// assert_eq!(b.to_vec1::<f64>()?, &[0., 1.]);
///
/// let c = a.i(..2)?;
/// assert_eq!(c.shape().dims(), &[2, 2]);
/// assert_eq!(c.to_vec2::<f64>()?, &[
/// [0., 1.],
/// [2., 3.]
/// ]);
///
/// let d = a.i(1..)?;
/// assert_eq!(d.shape().dims(), &[2, 2]);
/// assert_eq!(d.to_vec2::<f64>()?, &[
/// [2., 3.],
/// [4., 5.]
/// ]);
/// # Ok::<(), candle_core::Error>(())
/// ```
fn i(&self, index: T) -> Result<Tensor, Error> {
self.index(&[index.into()])
}
}
impl<A> IndexOp<(A,)> for Tensor
where
A: Into<TensorIndexer>,
{
///```rust
/// use candle_core::{Tensor, DType, Device, IndexOp};
/// let a = Tensor::new(&[
/// [0f32, 1.],
/// [2. , 3.],
/// [4. , 5.]
/// ], &Device::Cpu)?;
///
/// let b = a.i((0,))?;
/// assert_eq!(b.shape().dims(), &[2]);
/// assert_eq!(b.to_vec1::<f32>()?, &[0., 1.]);
///
/// let c = a.i((..2,))?;
/// assert_eq!(c.shape().dims(), &[2, 2]);
/// assert_eq!(c.to_vec2::<f32>()?, &[
/// [0., 1.],
/// [2., 3.]
/// ]);
///
/// let d = a.i((1..,))?;
/// assert_eq!(d.shape().dims(), &[2, 2]);
/// assert_eq!(d.to_vec2::<f32>()?, &[
/// [2., 3.],
/// [4., 5.]
/// ]);
/// # Ok::<(), candle_core::Error>(())
/// ```
fn i(&self, (a,): (A,)) -> Result<Tensor, Error> {
self.index(&[a.into()])
}
}
#[allow(non_snake_case)]
impl<A, B> IndexOp<(A, B)> for Tensor
where
A: Into<TensorIndexer>,
B: Into<TensorIndexer>,
{
///```rust
/// use candle_core::{Tensor, DType, Device, IndexOp};
/// let a = Tensor::new(&[[0f32, 1., 2.], [3., 4., 5.], [6., 7., 8.]], &Device::Cpu)?;
///
/// let b = a.i((1, 0))?;
/// assert_eq!(b.to_vec0::<f32>()?, 3.);
///
/// let c = a.i((..2, 1))?;
/// assert_eq!(c.shape().dims(), &[2]);
/// assert_eq!(c.to_vec1::<f32>()?, &[1., 4.]);
///
/// let d = a.i((2.., ..))?;
/// assert_eq!(d.shape().dims(), &[1, 3]);
/// assert_eq!(d.to_vec2::<f32>()?, &[[6., 7., 8.]]);
/// # Ok::<(), candle_core::Error>(())
/// ```
fn i(&self, (a, b): (A, B)) -> Result<Tensor, Error> {
self.index(&[a.into(), b.into()])
}
}
macro_rules! index_op_tuple {
($doc:tt, $($t:ident),+) => {
#[allow(non_snake_case)]
impl<$($t),*> IndexOp<($($t,)*)> for Tensor
where
$($t: Into<TensorIndexer>,)*
{
#[doc=$doc]
fn i(&self, ($($t,)*): ($($t,)*)) -> Result<Tensor, Error> {
self.index(&[$($t.into(),)*])
}
}
};
}
index_op_tuple!("see [TensorIndex#method.i]", A, B, C);
index_op_tuple!("see [TensorIndex#method.i]", A, B, C, D);
index_op_tuple!("see [TensorIndex#method.i]", A, B, C, D, E);
index_op_tuple!("see [TensorIndex#method.i]", A, B, C, D, E, F);
index_op_tuple!("see [TensorIndex#method.i]", A, B, C, D, E, F, G);