Struct NeuralFeatures 

pub struct NeuralFeatures { /* private fields */ }

Implementations

impl NeuralFeatures

pub fn new( attention: usize, memory: usize, inputs: usize, outputs: usize, hidden: usize, layers: usize, ) -> NeuralFeatures

pub const fn attention(&self) -> usize

returns a copy of the attention size

pub const fn codex(&self) -> usize

returns a copy of the number of features within the read/write heads

pub const fn hidden(&self) -> usize

returns a copy of the hidden size

pub const fn inputs(&self) -> usize

returns a copy of the input size

pub const fn layers(&self) -> usize

returns a copy of the number of hidden layers

pub const fn outputs(&self) -> usize

returns a copy of the output size

pub const fn dim_attention(&self) -> (usize, usize)

the shape of the attention layer (n_outputs, n_attention)

pub const fn dim_input(&self) -> (usize, usize)

the shape of the input layer (inputs, n_hidden)

pub const fn dim_hidden(&self) -> (usize, usize)

the shape of the hidden layer (hidden, hidden)

pub const fn dim_memory(&self) -> (usize, usize)

the shape of the memory matrix (n_memory, n_attention)

pub const fn dim_output(&self) -> (usize, usize)

the shape of the output layer (n_hidden, n_out)

pub fn set_attention(&mut self, attention: usize)

set the number of features for attention

pub fn set_codex(&mut self, codex: usize)

set the number of features for the read/write heads

pub fn set_inputs(&mut self, inputs: usize)

set the number of features for then input layer

pub fn set_hidden(&mut self, hidden: usize)

set the number of features for the hidden layer

pub fn set_outputs(&mut self, outputs: usize)

set the number of features for the output layer

pub fn with_attention(self, attention: usize) -> NeuralFeatures

consumes the current instance; returns another with the given number of features for attention

pub fn with_codex(self, codex: usize) -> NeuralFeatures

consumes the current instance; returns another with the given number of features for the read/write heads

pub fn with_inputs(self, inputs: usize) -> NeuralFeatures

consumes the current instance; returns another with the given number of input features

pub fn with_hidden(self, hidden: usize) -> NeuralFeatures

consumes the current instance; returns another with the given number of hidden features

pub fn with_outputs(self, outputs: usize) -> NeuralFeatures

consumes the current instance; returns another with the given number of output features

Trait Implementations

impl Clone for NeuralFeatures

fn clone(&self) -> NeuralFeatures

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NeuralFeatures

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

Formats the value using the given formatter.

impl Default for NeuralFeatures

fn default() -> NeuralFeatures

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for NeuralFeatures

fn deserialize<__D>( __deserializer: __D, ) -> Result<NeuralFeatures, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Hash for NeuralFeatures

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 Ord for NeuralFeatures

fn cmp(&self, other: &NeuralFeatures) -> 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 PartialEq for NeuralFeatures

fn eq(&self, other: &NeuralFeatures) -> 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 PartialOrd for NeuralFeatures

fn partial_cmp(&self, other: &NeuralFeatures) -> 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 Serialize for NeuralFeatures

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 Copy for NeuralFeatures

impl Eq for NeuralFeatures

impl StructuralPartialEq for NeuralFeatures