Struct TensorBase

pub struct TensorBase<T = f64> { /* private fields */ }

Implementations

impl<T> TensorBase<T>

pub fn from_iter<I>(iter: I) -> TensorBase<T>

where I: IntoIterator<Item = T>,

Create a new tensor from an iterator.

pub unsafe fn from_raw_parts( ptr: *mut T, shape: impl IntoShape, stride: impl IntoStride, ) -> TensorBase<T>

pub fn from_scalar(value: T) -> TensorBase<T>

Create a new tensor from a scalar value.

pub fn from_shape_iter<I>(shape: impl IntoShape, iter: I) -> TensorBase<T>

where I: IntoIterator<Item = T>,

Create a new tensor from an iterator, with a particular shape.

pub unsafe fn from_shape_ptr( shape: impl IntoShape, ptr: *mut T, ) -> TensorBase<T>

pub fn from_shape_vec(shape: impl IntoShape, data: Vec<T>) -> TensorBase<T>

Create a new tensor from a Vec, with a specified shape.

pub fn from_vec(data: Vec<T>) -> TensorBase<T>

Create a new, one-dimensional tensor from a Vec.

pub fn as_mut_ptr(&mut self) -> *mut T

Return a mutable pointer to the tensor’s data.

pub fn as_ptr(&self) -> *const T

Return a pointer to the tensor’s data.

pub fn as_slice(&self) -> &[T]

Return a reference to the tensor’s data.

pub fn as_mut_slice(&mut self) -> &mut [T]

Return a mutable reference to the tensor’s data.

pub fn assign(&mut self, other: &TensorBase<T>)

where T: Clone,

Assign the values of another tensor to this tensor.

pub fn boxed(self) -> Box<TensorBase<T>>

pub fn detach(&self) -> TensorBase<T>

where T: Clone,

Detach the computational graph from the tensor

pub fn first(&self) -> Option<&T>

Returns a reference to the first element of the tensor.

pub fn first_mut(&mut self) -> Option<&mut T>

Returns a mutable reference to the first element of the tensor.

pub fn get(&self, index: impl AsRef<[usize]>) -> Option<&T>

Returns the data at the specified index.

pub fn get_mut(&mut self, index: impl AsRef<[usize]>) -> Option<&mut T>

Returns a mutable reference to the data at the specified index.

pub const fn id(&self) -> TensorId

Returns the unique identifier of the tensor.

pub unsafe fn into_scalar(self) -> T

where T: Clone,

pub fn is_contiguous(&self) -> bool

Returns true if the tensor is contiguous.

pub fn is_empty(&self) -> bool

Returns true if the tensor is empty.

pub fn is_scalar(&self) -> bool

A function to check if the tensor is a scalar

pub fn is_square(&self) -> bool

Returns true if the tensor is a square matrix.

pub const fn is_variable(&self) -> bool

A function to check if the tensor is a variable

pub fn iter(&self) -> Iter<'_, T>

Creates an immutable iterator over the elements in the tensor.

pub fn iter_mut(&mut self) -> IterMut<'_, T>

Create a mutable iterator over the elements in the tensor.

pub const fn kind(&self) -> TensorKind

Get the kind of the tensor

pub fn last(&self) -> Option<&T>

Get a reference to the last element of the tensor

pub fn last_mut(&mut self) -> Option<&mut T>

Get a mutable reference to the last element of the tensor

pub const fn layout(&self) -> &Layout

Get a reference to the Layout of the tensor

pub fn ncols(&self) -> usize

Get the number of columns in the tensor

pub fn nrows(&self) -> usize

Get the number of rows in the tensor

pub const fn op(&self) -> &BackpropOp<T>

Get a reference to the operation of the tensor

pub fn op_view(&self) -> BackpropOp<&T>

Get a reference to the operation of the tensor

pub fn rank(&self) -> Rank

Get an owned reference to the Rank of the tensor

pub fn set(&mut self, index: impl AsRef<[usize]>, value: T)

Set the value of the tensor at the specified index

pub fn shape(&self) -> &Shape

An owned reference of the tensors Shape

pub fn size(&self) -> usize

Returns the number of elements in the tensor.

pub fn strides(&self) -> &Stride

Get a reference to the stride of the tensor

pub fn to_scalar(&self) -> Result<&T, TensorError>

Turn the tensor into a scalar If the tensor has a rank greater than 0, this will return an error

pub fn to_vec(&self) -> Vec<T>

where T: Clone,

Turn the tensor into a one-dimensional vector

pub fn variable(self) -> TensorBase<T>

Changes the kind of tensor to a variable

pub fn with_layout(self, layout: Layout) -> TensorBase<T>

Set the layout of the tensor

pub unsafe fn with_layout_unchecked(self, layout: Layout) -> TensorBase<T>

Set the layout of the tensor without checking for compatibility

Safety

This function is unsafe because it does not check if the layout is compatible with the tensor.

pub fn with_op(self, op: BackpropOp<T>) -> TensorBase<T>

pub fn with_shape_c(self, shape: impl IntoShape) -> TensorBase<T>

impl<T> TensorBase<T>

pub fn view_from_scalar(scalar: &T) -> TensorBase<&T>

pub fn to_owned(&self) -> TensorBase<T>

where T: Clone,

pub fn view(&self) -> TensorBase<&T>

pub fn view_mut(&mut self) -> TensorBase<&mut T>

impl<T> TensorBase<T>

pub fn max(&self) -> &T

where T: Ord,

pub fn mean(&self) -> T

where T: Scalar,

pub fn min(&self) -> &T

where T: Ord,

pub fn sort(&mut self)

where T: Ord,

pub fn std(&self) -> T

where T: Scalar,

pub fn variance(&self) -> T

where T: Scalar,

impl<T> TensorBase<T>

where T: Scalar,

pub fn apply_binary(&self, other: &TensorBase<T>, op: BinaryOp) -> TensorBase<T>

pub fn apply_binaryf<F>( &self, other: &TensorBase<T>, op: BinaryOp, f: F, ) -> TensorBase<T>

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

impl<T> TensorBase<T>

pub fn pow(&self, exp: T) -> TensorBase<T>

where T: Copy + Pow<T, Output = T>,

pub fn powf(&self, exp: T) -> TensorBase<T>

where T: Float,

pub fn powi(&self, exp: i32) -> TensorBase<T>

where T: FloatCore,

impl<T> TensorBase<T>

where T: Scalar,

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

pub fn add_scalar(&self, other: T) -> TensorBase<T>

impl<T> TensorBase<T>

where T: Scalar,

pub fn abs(&self) -> TensorBase<<T as Scalar>::Real>

where T: Scalar<Real = T>,

pub fn sigmoid(&self) -> TensorBase<T>

where T: ScalarExt,

pub fn cos(&self) -> TensorBase<T>

pub fn cosh(&self) -> TensorBase<T>

pub fn exp(&self) -> TensorBase<T>

pub fn ln(&self) -> TensorBase<T>

pub fn recip(&self) -> TensorBase<T>

pub fn sin(&self) -> TensorBase<T>

pub fn sinh(&self) -> TensorBase<T>

pub fn sqr(&self) -> TensorBase<T>

pub fn sqrt(&self) -> TensorBase<T>

pub fn tan(&self) -> TensorBase<T>

pub fn tanh(&self) -> TensorBase<T>

impl<T> TensorBase<T>

where T: Clone,

pub fn default_like(&self) -> TensorBase<T>

where T: Default,

Create a new tensor, whose elements are set to their default value from the current shape.

pub fn empty(shape: impl IntoShape) -> TensorBase<T>

where T: Default,

Create an empty tensor from the given shape

pub fn fill(shape: impl IntoShape, value: T) -> TensorBase<T>

Create a tensor, from the given shape, filled with the given value

pub fn fill_like(&self, value: T) -> TensorBase<T>

Create a tensor, filled with some value, from the current shape

pub fn like_with(&self, data: Vec<T>) -> TensorBase<T>

impl<T> TensorBase<T>

where T: Copy + NumAssign + PartialOrd,

pub fn arange(start: T, end: T, step: T) -> TensorBase<T>

Create a tensor within a range of values

pub fn eye(size: usize) -> TensorBase<T>

Create an identity matrix of a certain size

pub fn linspace(start: T, end: T, steps: usize) -> TensorBase<T>

where T: FromPrimitive,

Create a tensor with a certain number of elements, evenly spaced between the provided start and end values

pub fn logspace(start: T, end: T, steps: usize) -> TensorBase<T>

where T: Real,

pub fn geomspace(start: T, end: T, steps: usize) -> TensorBase<T>

where T: Real,

impl<T> TensorBase<T>

where T: Clone + One,

pub fn ones(shape: impl IntoShape) -> TensorBase<T>

Create a tensor, filled with ones, from the given shape

pub fn ones_from(tensor: &TensorBase<T>) -> TensorBase<T>

Create a tensor, filled with ones, from the shape of another tensor

pub fn ones_like(&self) -> TensorBase<T>

Create a tensor, filled with ones, from the shape of the tensor

impl<T> TensorBase<T>

where T: Clone + Zero,

pub fn zeros(shape: impl IntoShape) -> TensorBase<T>

Create a tensor, filled with zeros, from the given shape

pub fn zeros_from(tensor: &TensorBase<T>) -> TensorBase<T>

Create a tensor, filled with zeros, from the shape of another tensor

pub fn zeros_like(&self) -> TensorBase<T>

Create a tensor, filled with zeros, from the shape of the tensor

impl<T> TensorBase<T>

where T: ScalarExt,

pub fn grad(&self) -> Result<TensorGrad<T>, TensorError>

Compute the gradient of the tensor

impl<T> TensorBase<T>

where T: Copy,

pub fn product(&self) -> T

where T: Product,

Compute the product of all elements in the tensor

pub fn sum(&self) -> T

where T: Sum,

Compute the sum of all elements in the tensor

impl<T> TensorBase<T>

where T: Copy,

pub fn diag(&self) -> TensorBase<T>

Creates a new tensor containing only the diagonal elements of the original tensor.

pub fn inv(&self) -> Result<TensorBase<T>, TensorError>

where T: NumAssign + PartialOrd,

Find the inverse of the tensor

Errors

Returns an error if the matrix is not square or if the matrix is singular.

pub fn trace(&self) -> Result<T, TensorError>

where T: Num,

Compute the trace of the matrix. The trace of a matrix is the sum of the diagonal elements.

impl<T> TensorBase<T>

where T: Clone,

pub fn broadcast(&self, shape: impl IntoShape) -> TensorBase<T>

coerce the tensor to act like a larger shape. This method doesn’t change the underlying data, but it does change the layout.

pub fn swap_axes(&self, swap: Axis, with: Axis) -> TensorBase<T>

Swap two axes in the tensor.

pub fn t(&self) -> TensorBase<T>

Transpose the tensor.

pub fn reshape( self, shape: impl IntoShape, ) -> Result<TensorBase<T>, TensorError>

Reshape the tensor returns an error if the new shape specifies a different number of elements.

Trait Implementations

impl<'a, 'b, T> Add<&'b TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Add<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the + operator.

fn add( self, other: &'b TensorBase<T>, ) -> <&'a TensorBase<T> as Add<&'b TensorBase<T>>>::Output

Performs the + operation.

impl<'a, T> Add<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Add<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the + operator.

fn add( self, other: &'a TensorBase<T>, ) -> <TensorBase<T> as Add<&'a TensorBase<T>>>::Output

Performs the + operation.

impl<'a, T> Add<T> for &'a TensorBase<T>

where T: Copy + Add<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the + operator.

fn add(self, other: T) -> <&'a TensorBase<T> as Add<T>>::Output

Performs the + operation.

impl<T> Add<T> for TensorBase<T>

where T: Copy + Add<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the + operator.

fn add(self, other: T) -> <TensorBase<T> as Add<T>>::Output

Performs the + operation.

impl<'a, T> Add<TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Add<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the + operator.

fn add( self, other: TensorBase<T>, ) -> <&'a TensorBase<T> as Add<TensorBase<T>>>::Output

Performs the + operation.

impl<T> Add for TensorBase<T>

where T: Copy + Add<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the + operator.

fn add(self, other: TensorBase<T>) -> <TensorBase<T> as Add>::Output

Performs the + operation.

impl<'a, T> AddAssign<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Add<Output = T>,

fn add_assign(&mut self, other: &'a TensorBase<T>)

Performs the += operation.

impl<T> AddAssign for TensorBase<T>

where T: Copy + Add<Output = T>,

fn add_assign(&mut self, other: TensorBase<T>)

Performs the += operation.

impl<'a, T> AsRef<TensorBase<T>> for TensorBase<&'a T>

fn as_ref(&self) -> &TensorBase<T>

Converts this type into a shared reference of the (usually inferred) input type.

impl<T> Clone for TensorBase<T>

where T: Clone,

fn clone(&self) -> TensorBase<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T> Debug for TensorBase<T>

where T: Debug,

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

Formats the value using the given formatter.

impl<'de, T> Deserialize<'de> for TensorBase<T>

where T: Deserialize<'de>,

fn deserialize<__D>( __deserializer: __D, ) -> Result<TensorBase<T>, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<'a, 'b, T> Div<&'b TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Div<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the / operator.

fn div( self, other: &'b TensorBase<T>, ) -> <&'a TensorBase<T> as Div<&'b TensorBase<T>>>::Output

Performs the / operation.

impl<'a, T> Div<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Div<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the / operator.

fn div( self, other: &'a TensorBase<T>, ) -> <TensorBase<T> as Div<&'a TensorBase<T>>>::Output

Performs the / operation.

impl<'a, T> Div<T> for &'a TensorBase<T>

where T: Copy + Div<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the / operator.

fn div(self, other: T) -> <&'a TensorBase<T> as Div<T>>::Output

Performs the / operation.

impl<T> Div<T> for TensorBase<T>

where T: Copy + Div<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the / operator.

fn div(self, other: T) -> <TensorBase<T> as Div<T>>::Output

Performs the / operation.

impl<'a, T> Div<TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Div<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the / operator.

fn div( self, other: TensorBase<T>, ) -> <&'a TensorBase<T> as Div<TensorBase<T>>>::Output

Performs the / operation.

impl<T> Div for TensorBase<T>

where T: Copy + Div<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the / operator.

fn div(self, other: TensorBase<T>) -> <TensorBase<T> as Div>::Output

Performs the / operation.

impl<'a, T> DivAssign<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Div<Output = T>,

fn div_assign(&mut self, other: &'a TensorBase<T>)

Performs the /= operation.

impl<T> DivAssign for TensorBase<T>

where T: Copy + Div<Output = T>,

fn div_assign(&mut self, other: TensorBase<T>)

Performs the /= operation.

impl<'a, T> From<&'a TensorBase<T>> for Iter<'a, T>

fn from(tensor: &'a TensorBase<T>) -> Iter<'a, T>

Converts to this type from the input type.

impl<'a, T> From<TensorBase<&'a T>> for Iter<'a, T>

fn from(tensor: TensorBase<&'a T>) -> Iter<'a, T>

Converts to this type from the input type.

impl<T> From<TensorBase<T>> for Tensors<T>

where T: Clone,

fn from(tensor: TensorBase<T>) -> Tensors<T>

Converts to this type from the input type.

impl<T> FromIterator<T> for TensorBase<T>

fn from_iter<I>(iter: I) -> TensorBase<T>

where I: IntoIterator<Item = T>,

Creates a value from an iterator.

impl<T> Hash for TensorBase<T>

where T: Hash,

fn hash<__H>(&self, state: &mut __H)

where __H: Hasher,

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl<Idx, T> Index<Idx> for TensorBase<T>

where Idx: AsRef<[usize]>,

type Output = T

The returned type after indexing.

fn index(&self, index: Idx) -> &<TensorBase<T> as Index<Idx>>::Output

Performs the indexing (container[index]) operation.

impl<Idx, T> IndexMut<Idx> for TensorBase<T>

where Idx: AsRef<[usize]>,

fn index_mut( &mut self, index: Idx, ) -> &mut <TensorBase<T> as Index<Idx>>::Output

Performs the mutable indexing (container[index]) operation.

impl<T> IntoIterator for TensorBase<T>

type Item = T

The type of the elements being iterated over.

type IntoIter = IntoIter<T>

Which kind of iterator are we turning this into?

fn into_iter(self) -> <TensorBase<T> as IntoIterator>::IntoIter

Creates an iterator from a value.

impl<T> Inverse for TensorBase<T>

where T: Copy + Num + NumAssign + PartialOrd,

type Output = Result<TensorBase<T>, TensorError>

fn inv(&self) -> <TensorBase<T> as Inverse>::Output

impl<T> Matmul for TensorBase<T>

where T: Scalar,

type Output = TensorBase<T>

fn matmul(&self, other: &TensorBase<T>) -> TensorBase<T>

impl<'a, 'b, T> Mul<&'b TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Mul<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the * operator.

fn mul( self, other: &'b TensorBase<T>, ) -> <&'a TensorBase<T> as Mul<&'b TensorBase<T>>>::Output

Performs the * operation.

impl<'a, T> Mul<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Mul<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the * operator.

fn mul( self, other: &'a TensorBase<T>, ) -> <TensorBase<T> as Mul<&'a TensorBase<T>>>::Output

Performs the * operation.

impl<'a, T> Mul<T> for &'a TensorBase<T>

where T: Copy + Mul<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the * operator.

fn mul(self, other: T) -> <&'a TensorBase<T> as Mul<T>>::Output

Performs the * operation.

impl<T> Mul<T> for TensorBase<T>

where T: Copy + Mul<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the * operator.

fn mul(self, other: T) -> <TensorBase<T> as Mul<T>>::Output

Performs the * operation.

impl<'a, T> Mul<TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Mul<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the * operator.

fn mul( self, other: TensorBase<T>, ) -> <&'a TensorBase<T> as Mul<TensorBase<T>>>::Output

Performs the * operation.

impl<T> Mul for TensorBase<T>

where T: Copy + Mul<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the * operator.

fn mul(self, other: TensorBase<T>) -> <TensorBase<T> as Mul>::Output

Performs the * operation.

impl<'a, T> MulAssign<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Mul<Output = T>,

fn mul_assign(&mut self, other: &'a TensorBase<T>)

Performs the *= operation.

impl<T> MulAssign for TensorBase<T>

where T: Copy + Mul<Output = T>,

fn mul_assign(&mut self, other: TensorBase<T>)

Performs the *= operation.

impl<'a, T> Neg for &'a TensorBase<T>

where T: Copy + Neg<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn neg(self) -> <&'a TensorBase<T> as Neg>::Output

Performs the unary - operation.

impl<T> Neg for TensorBase<T>

where T: Copy + Neg<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn neg(self) -> <TensorBase<T> as Neg>::Output

Performs the unary - operation.

impl<'a, T> Not for &'a TensorBase<T>

where T: Copy + Not<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the ! operator.

fn not(self) -> <&'a TensorBase<T> as Not>::Output

Performs the unary ! operation.

impl<T> Not for TensorBase<T>

where T: Copy + Not<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the ! operator.

fn not(self) -> <TensorBase<T> as Not>::Output

Performs the unary ! operation.

impl<T> Num for TensorBase<T>

where T: Scalar + Num,

type FromStrRadixErr = <T as Num>::FromStrRadixErr

fn from_str_radix( str: &str, radix: u32, ) -> Result<TensorBase<T>, <TensorBase<T> as Num>::FromStrRadixErr>

Convert from a string and radix (typically 2..=36).

impl<T> One for TensorBase<T>

where T: Copy + One,

fn one() -> TensorBase<T>

Returns the multiplicative identity element of Self, 1.

fn set_one(&mut self)

Sets self to the multiplicative identity element of Self, 1.

fn is_one(&self) -> bool

where Self: PartialEq,

Returns true if self is equal to the multiplicative identity.

impl<T> Ord for TensorBase<T>

where T: Ord,

fn cmp(&self, other: &TensorBase<T>) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized,

Restrict a value to a certain interval.

impl<S, T> PartialEq<S> for TensorBase<T>

where S: AsRef<[T]>, T: PartialEq,

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl<T> PartialEq for TensorBase<T>

where T: PartialEq,

fn eq(&self, other: &TensorBase<T>) -> bool

Tests for self and other values to be equal, and is used by ==.

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

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

impl<T> PartialOrd for TensorBase<T>

where T: PartialOrd,

fn partial_cmp(&self, other: &TensorBase<T>) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

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

Tests less than (for self and other) and is used by the < operator.

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

Tests less than or equal to (for self and other) and is used by the <= operator.

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

Tests greater than (for self and other) and is used by the > operator.

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

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl<'a, T> Pow<T> for &'a TensorBase<T>

where T: Copy + Pow<T, Output = T>,

type Output = TensorBase<T>

The result after applying the operator.

fn pow(self, exp: T) -> <&'a TensorBase<T> as Pow<T>>::Output

Returns self to the power rhs.

impl<T> Pow<T> for TensorBase<T>

where T: Copy + Pow<T, Output = T>,

type Output = TensorBase<T>

The result after applying the operator.

fn pow(self, exp: T) -> <TensorBase<T> as Pow<T>>::Output

Returns self to the power rhs.

impl<'a, 'b, T> Rem<&'b TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Rem<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the % operator.

fn rem( self, other: &'b TensorBase<T>, ) -> <&'a TensorBase<T> as Rem<&'b TensorBase<T>>>::Output

Performs the % operation.

impl<'a, T> Rem<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Rem<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the % operator.

fn rem( self, other: &'a TensorBase<T>, ) -> <TensorBase<T> as Rem<&'a TensorBase<T>>>::Output

Performs the % operation.

impl<'a, T> Rem<T> for &'a TensorBase<T>

where T: Copy + Rem<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the % operator.

fn rem(self, other: T) -> <&'a TensorBase<T> as Rem<T>>::Output

Performs the % operation.

impl<T> Rem<T> for TensorBase<T>

where T: Copy + Rem<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the % operator.

fn rem(self, other: T) -> <TensorBase<T> as Rem<T>>::Output

Performs the % operation.

impl<'a, T> Rem<TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Rem<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the % operator.

fn rem( self, other: TensorBase<T>, ) -> <&'a TensorBase<T> as Rem<TensorBase<T>>>::Output

Performs the % operation.

impl<T> Rem for TensorBase<T>

where T: Copy + Rem<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the % operator.

fn rem(self, other: TensorBase<T>) -> <TensorBase<T> as Rem>::Output

Performs the % operation.

impl<'a, T> RemAssign<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Rem<Output = T>,

fn rem_assign(&mut self, other: &'a TensorBase<T>)

Performs the %= operation.

impl<T> RemAssign for TensorBase<T>

where T: Copy + Rem<Output = T>,

fn rem_assign(&mut self, other: TensorBase<T>)

Performs the %= operation.

impl<T> Serialize for TensorBase<T>

where T: Serialize,

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<T> Statistics<T> for TensorBase<T>

where T: Ord + Scalar,

fn max(&self) -> T

Returns the maximum value in the collection.

fn mean(&self) -> T

Returns the mean (average) value of the collection.

fn median(&self) -> T

Returns the median value in the collection.

fn min(&self) -> T

Returns the minimum value in the collection.

fn mode(&self) -> T

Get the mode of the collection.

fn sum(&self) -> T

fn std(&self) -> T

Compute the standard deviation

fn variance(&self) -> T

Compute the variance

impl<T> Store<TensorId, TensorBase<T>> for TensorGrad<T>

fn get(&self, key: &TensorId) -> Option<&TensorBase<T>>

fn get_mut(&mut self, key: &TensorId) -> Option<&mut TensorBase<T>>

fn insert( &mut self, key: TensorId, value: TensorBase<T>, ) -> Option<TensorBase<T>>

fn remove(&mut self, key: &TensorId) -> Option<TensorBase<T>>

impl<'a, 'b, T> Sub<&'b TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Sub<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn sub( self, other: &'b TensorBase<T>, ) -> <&'a TensorBase<T> as Sub<&'b TensorBase<T>>>::Output

Performs the - operation.

impl<'a, T> Sub<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Sub<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn sub( self, other: &'a TensorBase<T>, ) -> <TensorBase<T> as Sub<&'a TensorBase<T>>>::Output

Performs the - operation.

impl<'a, T> Sub<T> for &'a TensorBase<T>

where T: Copy + Sub<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn sub(self, other: T) -> <&'a TensorBase<T> as Sub<T>>::Output

Performs the - operation.

impl<T> Sub<T> for TensorBase<T>

where T: Copy + Sub<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn sub(self, other: T) -> <TensorBase<T> as Sub<T>>::Output

Performs the - operation.

impl<'a, T> Sub<TensorBase<T>> for &'a TensorBase<T>

where T: Copy + Sub<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn sub( self, other: TensorBase<T>, ) -> <&'a TensorBase<T> as Sub<TensorBase<T>>>::Output

Performs the - operation.

impl<T> Sub for TensorBase<T>

where T: Copy + Sub<Output = T>,

type Output = TensorBase<T>

The resulting type after applying the - operator.

fn sub(self, other: TensorBase<T>) -> <TensorBase<T> as Sub>::Output

Performs the - operation.

impl<'a, T> SubAssign<&'a TensorBase<T>> for TensorBase<T>

where T: Copy + Sub<Output = T>,

fn sub_assign(&mut self, other: &'a TensorBase<T>)

Performs the -= operation.

impl<T> SubAssign for TensorBase<T>

where T: Copy + Sub<Output = T>,

fn sub_assign(&mut self, other: TensorBase<T>)

Performs the -= operation.

impl<T> Zero for TensorBase<T>

where T: Copy + Zero,

fn zero() -> TensorBase<T>

Returns the additive identity element of Self, 0.

fn is_zero(&self) -> bool

Returns true if self is equal to the additive identity.

fn set_zero(&mut self)

Sets self to the additive identity element of Self, 0.

impl<T> Eq for TensorBase<T>

where T: Eq,