Struct dfdx::tensor::Cpu

pub struct Cpu { /* private fields */ }

A device that stores data on the heap.

The Default impl seeds the underlying rng with seed of 0.

Use Cpu::seed_from_u64 to control what seed is used.

Implementations

impl Cpu

pub fn seed_from_u64(seed: u64) -> Self

Constructs rng with the given seed.

Trait Implementations

impl Cache for Cpu

fn try_enable_cache(&self) -> Result<(), Self::Err>

Tries to enable the cache of the device.

fn try_disable_cache(&self) -> Result<(), Self::Err>

Tries to disable the cache of the device. See Cache::disable_cache for details of when this is useful.

fn try_empty_cache(&self) -> Result<(), Self::Err>

Tries to empty the cache of the device. See Cache::empty_cache for details of when this is useful.

fn enable_cache(&self)

Enables the cache of the device.

fn disable_cache(&self)

Disables the cache of the device. This will also empty the cache if there are things in it. See Cache::empty_cache for more information.

fn empty_cache(&self)

Empties the cache of the device.

impl Clone for Cpu

fn clone(&self) -> Cpu

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<E: Unit> CopySlice<E> for Cpu

fn copy_from<S: Shape, T>(dst: &mut Tensor<S, E, Self, T>, src: &[E])

fn copy_into<S: Shape, T>(src: &Tensor<S, E, Self, T>, dst: &mut [E])

impl Debug for Cpu

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

Formats the value using the given formatter.

impl Default for Cpu

fn default() -> Self

Returns the “default value” for a type.

impl DeviceBuildExt for Cpu

fn build_module<M: BuildOnDevice<Self, E>, E: Dtype>(&self) -> M::Builtwhere Self: Device<E>,

fn try_build_module<M: BuildOnDevice<Self, E>, E: Dtype>( &self ) -> Result<M::Built, Self::Err>where Self: Device<E>,

impl HasErr for Cpu

type Err = CpuError

impl<E: Unit> OnesTensor<E> for Cpu

fn try_ones_like<S: HasShape>( &self, src: &S ) -> Result<Tensor<S::Shape, E, Self>, Self::Err>

Fallible version of OnesTensor::ones_like

fn ones<S: ConstShape>(&self) -> Tensor<S, E, Self>

Creates a tensor filled with ones.

fn try_ones<S: ConstShape>(&self) -> Result<Tensor<S, E, Self>, Self::Err>

Fallible version of OnesTensor::ones

fn ones_like<S: HasShape>(&self, src: &S) -> Tensor<S::Shape, E, Self>

Build the tensor with a shape given by something else.

impl RandomU64 for Cpu

fn random_u64(&self) -> u64

Generates a random u64 number

impl<E: Unit> SampleTensor<E> for Cpu

fn try_sample_like<S: HasShape, D: Distribution<E>>( &self, src: &S, distr: D ) -> Result<Tensor<S::Shape, E, Self>, Self::Err>

Fallibly samples a tensor with a given shape from a given distribution.

fn try_fill_with_distr<D: Distribution<E>>( &self, storage: &mut Self::Vec, distr: D ) -> Result<(), Self::Err>

Fills tensor Storage<E> with data from a given distribution

fn sample<S: ConstShape, D: Distribution<E>>( &self, distr: D ) -> Tensor<S, E, Self>

Samples a const tensor from a given distribution.

fn try_sample<S: ConstShape, D: Distribution<E>>( &self, distr: D ) -> Result<Tensor<S, E, Self>, Self::Err>

Fallibly samples a const tensor from a given distribution.

fn sample_like<S: HasShape, D: Distribution<E>>( &self, src: &S, distr: D ) -> Tensor<S::Shape, E, Self>

Samples a tensor with a given shape from a given distribution.

impl<E: Unit> Storage<E> for Cpu

type Vec = CachableVec<E>

Generic Storage type

fn try_alloc_len(&self, len: usize) -> Result<Self::Vec, Self::Err>

fn len(&self, v: &Self::Vec) -> usize

fn tensor_to_vec<S: Shape, T>(&self, tensor: &Tensor<S, E, Self, T>) -> Vec<E>

fn try_alloc_grad(&self, storage: &Self::Vec) -> Result<Self::Vec, Self::Err>

Allocates a gradient for the given nd array

impl Synchronize for Cpu

fn try_synchronize(&self) -> Result<(), Self::Err>

Blocks until all work on device to complete. Useful for benchmarking.

fn synchronize(&self)

Blocks until all work on device to complete. Useful for benchmarking.

impl<E: Unit> TensorFromVec<E> for Cpu

fn try_tensor_from_vec<S: Shape>( &self, src: Vec<E>, shape: S ) -> Result<Tensor<S, E, Self>, Self::Err>

fn tensor_from_vec<S: Shape>(&self, src: Vec<E>, shape: S) -> Tensor<S, E, Self>

impl<E: Unit> TensorToArray<(), E> for Cpu

type Array = E

fn tensor_to_array<T>(&self, tensor: &Tensor<Rank0, E, Self, T>) -> Self::Array

impl<E: Unit, const M: usize> TensorToArray<(Const<M>,), E> for Cpu

type Array = [E; M]

fn tensor_to_array<T>( &self, tensor: &Tensor<Rank1<M>, E, Self, T> ) -> Self::Array

impl<E: Unit, const M: usize, const N: usize> TensorToArray<(Const<M>, Const<N>), E> for Cpu

type Array = [[E; N]; M]

fn tensor_to_array<T>( &self, tensor: &Tensor<Rank2<M, N>, E, Self, T> ) -> Self::Array

impl<E: Unit, const M: usize, const N: usize, const O: usize> TensorToArray<(Const<M>, Const<N>, Const<O>), E> for Cpu

type Array = [[[E; O]; N]; M]

fn tensor_to_array<T>( &self, tensor: &Tensor<Rank3<M, N, O>, E, Self, T> ) -> Self::Array

impl<E: Unit, const M: usize, const N: usize, const O: usize, const P: usize> TensorToArray<(Const<M>, Const<N>, Const<O>, Const<P>), E> for Cpu

type Array = [[[[E; P]; O]; N]; M]

fn tensor_to_array<T>( &self, tensor: &Tensor<Rank4<M, N, O, P>, E, Self, T> ) -> Self::Array

impl<E: Unit> TriangleTensor<E> for Cpu

fn try_upper_tri_like<S: HasShape>( &self, src: &S, val: E, diagonal: impl Into<Option<isize>> ) -> Result<Tensor<S::Shape, E, Self>, Self::Err>

Fallible version of TriangleTensor::upper_tri_like

fn try_lower_tri_like<S: HasShape>( &self, src: &S, val: E, diagonal: impl Into<Option<isize>> ) -> Result<Tensor<S::Shape, E, Self>, Self::Err>

Fallible version of TriangleTensor::lower_tri_like

fn upper_tri<S: ConstShape>( &self, val: E, diagonal: impl Into<Option<isize>> ) -> Tensor<S, E, Self>

Build a tensor containing the upper triangle part of each lowest 2D matrix set to the given value, along the given diagonal. The other values will be E::default().

fn try_upper_tri<S: ConstShape>( &self, val: E, diagonal: impl Into<Option<isize>> ) -> Result<Tensor<S, E, Self>, Self::Err>

Fallible version of TriangleTensor::upper_tri

fn upper_tri_like<S: HasShape>( &self, src: &S, val: E, diagonal: impl Into<Option<isize>> ) -> Tensor<S::Shape, E, Self>

Build an upper triangular tensor with the given shape. See TriangleTensor::upper_tri.

fn lower_tri<S: ConstShape>( &self, val: E, diagonal: impl Into<Option<isize>> ) -> Tensor<S, E, Self>

Build a tensor containing the lower triangle part of each lowest 2D matrix set to the given value, along the given diagonal. The other values will be E::default().

fn try_lower_tri<S: ConstShape>( &self, val: E, diagonal: impl Into<Option<isize>> ) -> Result<Tensor<S, E, Self>, Self::Err>

Fallible version of TriangleTensor::lower_tri

fn lower_tri_like<S: HasShape>( &self, src: &S, val: E, diagonal: impl Into<Option<isize>> ) -> Tensor<S::Shape, E, Self>

Build a lower triangular tensor with the given shape. See TriangleTensor::lower_tri.

impl<E: Unit> ZerosTensor<E> for Cpu

fn try_zeros_like<S: HasShape>( &self, src: &S ) -> Result<Tensor<S::Shape, E, Self>, Self::Err>

Fallible version of ZerosTensor::zeros_like

fn zeros<S: ConstShape>(&self) -> Tensor<S, E, Self>

Creates a tensor filled with zeros.

fn try_zeros<S: ConstShape>(&self) -> Result<Tensor<S, E, Self>, Self::Err>

Fallible version of ZerosTensor::zeros

fn zeros_like<S: HasShape>(&self, src: &S) -> Tensor<S::Shape, E, Self>

Build the tensor with a shape given by something else.

impl Device<f32> for Cpu

impl Device<f64> for Cpu