Struct engram::linalg::Tensor

pub struct Tensor {
    pub rows: usize,
    pub cols: usize,
    pub data: Tensor2D,
    pub grad: Option<Tensor2D>,
}

A tensor of floating point values.

Fields

rows: usize

The number of rows in the tensor.

cols: usize

The number of columns in the tensor.

data: Tensor2D

The data in the tensor, represented as a two-dimensional vector.

grad: Option<Tensor2D>

Gradient of the tensor.

Implementations

impl Tensor

pub fn shape(&self) -> (usize, usize)

Returns the shape of the tensor as a tuple of (rows, columns).

Examples

let t1 = Tensor::zeros(2, 3);
let t2 = Tensor::zeros(3, 2);
t1.shape();
t2.shape();

pub fn size(&self) -> usize

Returns the number of elements in the tensor.

Examples

let t1 = Tensor::zeros(2, 3);
let t2 = Tensor::zeros(5, 4);
t1.size();
t2.size();

pub fn first(&self) -> f64

Returns the first element in the tensor.

Examples

let t = tensor![[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]];
t.first();

impl Tensor

pub fn matmul(&self, other: &Tensor) -> Tensor

Performs matrix multiplication between two tensors.

Examples

let a = tensor![[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]];
let b = tensor![[7.0, 8.0], [9.0, 10.0], [11.0, 12.0]];
let c = a.matmul(&b);

pub fn mapv(&self, function: &dyn Fn(f64) -> f64) -> Tensor

Applies a function to each element in the tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.mapv(&|x| x * 2.0);

pub fn mapv_mut(&mut self, function: &dyn Fn(f64) -> f64)

Applies a function to each element in the tensor in-place.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.mapv_mut(&|x| x * 2.0);

pub fn square(&self) -> Tensor

Returns the square of each element in the tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.square();

pub fn square_mut(&mut self)

Squares each element in the tensor in-place.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.square_mut();

pub fn sqrt(&self) -> Tensor

Returns the square root of each element in the tensor.

Examples

let a = tensor![[1.0, 4.0], [9.0, 16.0]];
let b = a.sqrt();

pub fn sqrt_mut(&mut self)

Takes the square root of each element in the tensor in-place.

Examples

let mut a = tensor![[1.0, 4.0], [9.0, 16.0]];
a.sqrt_mut();

pub fn pow(&self, exponent: f64) -> Tensor

Returns each element in the tensor raised to the given exponent.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.pow(2.0);

pub fn pow_mut(&mut self, exponent: f64)

Raises each element in the tensor to the given exponent in-place.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.pow_mut(2.0);

pub fn ln(&self) -> Tensor

Returns each element in the tensor applied with the natural logarithm.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.ln();

pub fn ln_mut(&mut self)

Applies the natural logarithm to each element in the tensor in-place.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.ln_mut();

pub fn log2(&self) -> Tensor

Returns each element in the tensor applied with the base 2 logarithm.

Examples

let a = tensor![[1.0, 2.0], [4.0, 8.0]];
let b = a.log2();

pub fn log2_mut(&mut self)

Applies the base 2 logarithm to each element in the tensor in-place.

Examples

let mut a = tensor![[1.0, 2.0], [4.0, 8.0]];
a.log2_mut();

pub fn abs(&self) -> Tensor

Returns a tensor with the absolute value of each element in the tensor.

Examples

let a = tensor![[-1.0, 2.0], [-3.0, 4.0]];
let b = a.abs();

pub fn dot(&self, other: &Tensor) -> f64

Computes the dot product between two tensors.

Examples

let a = tensor![[1.0], [2.0], [3.0]];
let b = tensor![[4.0], [5.0], [6.0]];
let c = a.dot(&b);

pub fn sum(&self) -> f64

Returns the sum of all elements in the tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.sum();

pub fn sum_axis(&self, axis: u8) -> Tensor

Returns the sum of all elements in the tensor along the given axis.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]];
let sum_cols = a.sum_axis(0);
let sum_rows = a.sum_axis(1);

pub fn mean(&self) -> f64

Returns the mean of all elements in the tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.mean();

pub fn norm(&self, p: f64) -> f64

Returns the p-norm of the tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.norm(2.0);

pub fn activate(&self, activation: &Activation) -> Tensor

Returns a new tensor with each element in the tensor activated by the given activation function.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.activate(&Activation::Sigmoid);

pub fn activate_mut(&mut self, activation: &Activation)

Mutates the tensor in-place with each element in the tensor activated by the given activation function.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.activate_mut(&Activation::Sigmoid);

pub fn grad(&mut self, activation: &Activation) -> Tensor

Returns a new tensor with each element in the tensor activated by the derivative of the given activation function.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.grad(&Activation::Sigmoid);

impl Tensor

pub fn new(rows: usize, cols: usize, value: f64) -> Tensor

Creates a new Tensor with the specified number of rows, columns, and value.

Examples

let t1 = Tensor::new(2, 3, 0.0);
let t2 = Tensor::new(3, 2, 0.0);

pub fn new_like(other: &Tensor, value: f64) -> Tensor

Creates a new Tensor with the same shape as the provided Tensor, filled with the specified value.

Examples

let t1 = Tensor::new(2, 3, 0.0);
let t2 = Tensor::new_like(&t1, 0.0);

pub fn zeros(rows: usize, cols: usize) -> Tensor

pub fn zeros_like(other: &Tensor) -> Tensor

pub fn ones(rows: usize, cols: usize) -> Tensor

pub fn ones_like(other: &Tensor) -> Tensor

pub fn identity(size: usize) -> Tensor

Creates a new Tensor with the specified size, initialized to the identity matrix.

Examples

let t = Tensor::identity(3);

pub fn initialize(rows: usize, cols: usize, initializer: &Initializer) -> Tensor

Creates a new Tensor with the specified number of rows and columns, initialized using the provided initializer.

Examples

let t = Tensor::initialize(2, 3, &Initializer::Xavier);

impl Tensor

pub fn iter_rows(&self) -> impl Iterator<Item = &Tensor1D>

Returns an iterator over the rows of the tensor.

Examples

let mut tensor = tensor![[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]];
let mut iter = tensor.iter_rows();

pub fn iter_rows_mut(&mut self) -> impl Iterator<Item = &mut Tensor1D>

Returns a mutable iterator over the rows of the tensor.

Examples

let mut tensor = tensor![[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]];
let mut iter = tensor.iter_rows_mut();

impl Tensor

pub fn reshape(&self, rows: usize, cols: usize) -> Tensor

Reshapes the tensor to a new shape.

Examples

let a = tensor![[1.0, 2.0, 3.0, 4.0, 5.0, 6.0]];
let b = tensor![[1.0, 2.0], [4.0, 5.0], [7.0, 8.0], [3.0, 6.0]];
let c = a.reshape(2, 3);
let d = b.reshape(2, 4);

pub fn resize(&self, rows: usize, cols: usize) -> Tensor

Returns a resized version of the tensor with the given rows and cols.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]];
let b = a.resize(2, 2);
let c = b.resize(2, 3);

pub fn resize_mut(&mut self, rows: usize, cols: usize)

Returns a resized version of the tensor with the given rows and cols inplace.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]];
let b = a.resize(2, 2);
let c = b.resize(2, 3);

pub fn flatten(&self) -> Tensor1D

Returns a flattened version of the tensor data.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = a.flatten();

pub fn resize_to(&self, other: &Tensor) -> Tensor

Returns a resized version of the tensor with the same shape as the given tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]];
let b = tensor![[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]];
let c = a.resize_to(&b);
let d = b.resize_to(&a);

pub fn clip(&self, min: f64, max: f64) -> Tensor

Returns a clipped version of the tensor with values between the given min and max.

Examples

let a = tensor![[-1.0, 2.0], [3.0, 4.0], [5.0, 6.0]];
let b = a.clip(0.0, 4.0);

pub fn slice(&self, start: usize, end: usize) -> Tensor

Returns a slice of the tensor.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]];
let b = a.slice(1, 3);

impl Tensor

pub fn add<T: Rhs>(&self, other: T) -> Tensor

Performs self + rhs.

pub fn sub<T: Rhs>(&self, other: T) -> Tensor

Performs self - rhs.

pub fn mul<T: Rhs>(&self, other: T) -> Tensor

Performs self * rhs.

pub fn div<T: Rhs>(&self, other: T) -> Tensor

Performs self / rhs.

pub fn broadcast_and_apply<F>(&self, other: &Tensor, op: F) -> Tensor

where F: Fn(f64, f64) -> f64,

Broadcasts two tensors and applies a function element-wise.

Examples

let t1 = tensor![[1.0], [2.0]];
let t2 = tensor![3.0, 4.0];
let t3 = t1.broadcast_and_apply(&t2, |a, b| a + b);

pub fn broadcast_and_apply_mut<F>(&mut self, other: &Tensor, op: F)

where F: Fn(f64, f64) -> f64,

Broadcasts two tensors and applies a function element-wise in-place.

Examples

let mut t1 = tensor![[1.0], [2.0]];
let t2 = tensor![3.0, 4.0];
t1.broadcast_and_apply_mut(&t2, |a, b| a + b);

impl Tensor

pub fn sparse_matmul(&self, other: &Tensor) -> Tensor

Performs sparse matrix multiplication between two tensors.

Examples

let a = tensor![[1.0, 0.0, 0.0], [0.0, 5.0, 0.0], [0.0, 0.0, 2.0]];
let b = tensor![[7.0, 8.0], [9.0, 10.0], [11.0, 12.0]];
let c = a.sparse_matmul(&b);

pub fn sparse(&self) -> HashMap<(usize, usize), f64>

Returns a vector of the indices of all non-zero elements in the tensor.

Examples

let a = tensor![[0.0, 2.0], [3.0, 0.0]];
let b = a.sparse();
let expected = HashMap::from([((0, 1), 2.0), ((1, 0), 3.0)]);

impl Tensor

pub fn set_grad(&mut self, grad: Vec<Vec<f64>>)

Sets the gradient of the tensor.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.set_grad(vec![vec![1.0, 2.0], vec![3.0, 4.0]]);

pub fn zero_grad(&mut self)

Zeros out the gradient of the tensor.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.zero_grad();

impl Tensor

pub fn transpose(&self) -> Tensor

Returns the transpose of the tensor.

Examples

let a = tensor![[1.0, 2.0, 3.0], [3.0, 4.0, 6.0]];
let b = a.transpose();

pub fn transpose_mut(&mut self)

Transposes the tensor in-place.

Examples

let mut a = tensor![[1.0, 2.0], [3.0, 4.0]];
a.transpose_mut();

pub fn broadcast(&self, other: &Tensor) -> Tensor

Broadcasts the tensor to another tensor’s shape.

Examples

let a = tensor![[1.0, 2.0], [3.0, 4.0]];
let b = tensor![[1.0, 2.0, 8.0], [3.0, 4.0, 9.0]];
let c = a.broadcast(&b);

impl Tensor

pub fn is_symmetric(&self) -> bool

Returns true if the tensor is symmetric, i.e. a square matrix with equal elements across the diagonal.

Examples

let t = tensor![[1.0, 2.0, 3.0], [2.0, 1.0, 2.0], [3.0, 2.0, 1]];
assert!(t.is_symmetric());

pub fn is_positive_definite(&self) -> bool

Returns true if the tensor is positive definite, i.e. symmetric and all eigenvalues are positive.

Examples

let t = tensor![[4.0, 12.0, -16.0], [12.0, 37.0, -43.0], [-16.0, -43.0, 98.0]];
assert!(t.is_positive_definite());

Trait Implementations

impl Add<&Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the + operator.

fn add(self, rhs: &Tensor) -> Tensor

Performs the + operation.

impl Add<&Tensor> for Tensor

type Output = Tensor

The resulting type after applying the + operator.

fn add(self, rhs: &Tensor) -> Tensor

Performs the + operation.

impl Add<Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the + operator.

fn add(self, rhs: Tensor) -> Tensor

Performs the + operation.

impl Add<f64> for &Tensor

type Output = Tensor

The resulting type after applying the + operator.

fn add(self, rhs: f64) -> Tensor

Performs the + operation.

impl Add<f64> for Tensor

type Output = Tensor

The resulting type after applying the + operator.

fn add(self, rhs: f64) -> Tensor

Performs the + operation.

impl Add for Tensor

type Output = Tensor

The resulting type after applying the + operator.

fn add(self, rhs: Tensor) -> Tensor

Performs the + operation.

impl AddAssign<f64> for Tensor

fn add_assign(&mut self, rhs: f64)

Performs the += operation.

impl AddAssign for Tensor

fn add_assign(&mut self, rhs: Tensor)

Performs the += operation.

impl Clone for Tensor

fn clone(&self) -> Tensor

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Tensor

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Display for Tensor

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Div<&Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the / operator.

fn div(self, rhs: &Tensor) -> Tensor

Performs the / operation.

impl Div<&Tensor> for Tensor

type Output = Tensor

The resulting type after applying the / operator.

fn div(self, rhs: &Tensor) -> Tensor

Performs the / operation.

impl Div<Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the / operator.

fn div(self, rhs: Tensor) -> Tensor

Performs the / operation.

impl Div<f64> for &Tensor

type Output = Tensor

The resulting type after applying the / operator.

fn div(self, rhs: f64) -> Tensor

Performs the / operation.

impl Div<f64> for Tensor

type Output = Tensor

The resulting type after applying the / operator.

fn div(self, rhs: f64) -> Tensor

Performs the / operation.

impl Div for Tensor

type Output = Tensor

The resulting type after applying the / operator.

fn div(self, rhs: Tensor) -> Tensor

Performs the / operation.

impl DivAssign<f64> for Tensor

fn div_assign(&mut self, rhs: f64)

Performs the /= operation.

impl DivAssign for Tensor

fn div_assign(&mut self, rhs: Tensor)

Performs the /= operation.

impl From<&Vec<Vec<f64>>> for Tensor

fn from(data: &Tensor2D) -> Self

Converts to this type from the input type.

impl From<&Vec<f64>> for Tensor

fn from(data: &Tensor1D) -> Self

Converts to this type from the input type.

impl From<Vec<Vec<f64>>> for Tensor

fn from(data: Tensor2D) -> Self

Converts to this type from the input type.

impl From<Vec<f64>> for Tensor

fn from(data: Tensor1D) -> Self

Converts to this type from the input type.

impl FromIterator<Vec<f64>> for Tensor

fn from_iter<I: IntoIterator<Item = Tensor1D>>(iter: I) -> Self

Creates a value from an iterator.

impl Mul<&Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the * operator.

fn mul(self, rhs: &Tensor) -> Tensor

Performs the * operation.

impl Mul<&Tensor> for Tensor

type Output = Tensor

The resulting type after applying the * operator.

fn mul(self, rhs: &Tensor) -> Tensor

Performs the * operation.

impl Mul<Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the * operator.

fn mul(self, rhs: Tensor) -> Tensor

Performs the * operation.

impl Mul<f64> for &Tensor

type Output = Tensor

The resulting type after applying the * operator.

fn mul(self, rhs: f64) -> Tensor

Performs the * operation.

impl Mul<f64> for Tensor

type Output = Tensor

The resulting type after applying the * operator.

fn mul(self, rhs: f64) -> Tensor

Performs the * operation.

impl Mul for Tensor

type Output = Tensor

The resulting type after applying the * operator.

fn mul(self, rhs: Tensor) -> Tensor

Performs the * operation.

impl MulAssign<f64> for Tensor

fn mul_assign(&mut self, rhs: f64)

Performs the *= operation.

impl MulAssign for Tensor

fn mul_assign(&mut self, rhs: Tensor)

Performs the *= operation.

impl PartialEq for Tensor

fn eq(&self, other: &Self) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Sub<&Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the - operator.

fn sub(self, rhs: &Tensor) -> Tensor

Performs the - operation.

impl Sub<&Tensor> for Tensor

type Output = Tensor

The resulting type after applying the - operator.

fn sub(self, rhs: &Tensor) -> Tensor

Performs the - operation.

impl Sub<Tensor> for &Tensor

type Output = Tensor

The resulting type after applying the - operator.

fn sub(self, rhs: Tensor) -> Tensor

Performs the - operation.

impl Sub<f64> for &Tensor

type Output = Tensor

The resulting type after applying the - operator.

fn sub(self, rhs: f64) -> Tensor

Performs the - operation.

impl Sub<f64> for Tensor

type Output = Tensor

The resulting type after applying the - operator.

fn sub(self, rhs: f64) -> Tensor

Performs the - operation.

impl Sub for Tensor

type Output = Tensor

The resulting type after applying the - operator.

fn sub(self, rhs: Tensor) -> Tensor

Performs the - operation.

impl SubAssign<f64> for Tensor

fn sub_assign(&mut self, rhs: f64)

Performs the -= operation.

impl SubAssign for Tensor

fn sub_assign(&mut self, rhs: Tensor)

Performs the -= operation.