Struct NeuralNetwork 

pub struct NeuralNetwork {
    pub layers: Vec<NeuralNetworkLayer>,
    pub preprocessing: Vec<NeuralNetworkPreprocessing>,
    pub array_input_shape_mapping: i32,
    pub image_input_shape_mapping: i32,
    pub update_params: Option<NetworkUpdateParameters>,
}

A neural network.

Fields

layers: Vec<NeuralNetworkLayer>

preprocessing: Vec<NeuralNetworkPreprocessing>

array_input_shape_mapping: i32

use this enum value to determine the input tensor shapes to the neural network, for multiarray inputs

image_input_shape_mapping: i32

use this enum value to determine the input tensor shapes to the neural network, for image inputs

update_params: Option<NetworkUpdateParameters>

Implementations

impl NeuralNetwork

pub fn array_input_shape_mapping(&self) -> NeuralNetworkMultiArrayShapeMapping

Returns the enum value of array_input_shape_mapping, or the default if the field is set to an invalid enum value.

pub fn set_array_input_shape_mapping( &mut self, value: NeuralNetworkMultiArrayShapeMapping, )

Sets array_input_shape_mapping to the provided enum value.

pub fn image_input_shape_mapping(&self) -> NeuralNetworkImageShapeMapping

Returns the enum value of image_input_shape_mapping, or the default if the field is set to an invalid enum value.

pub fn set_image_input_shape_mapping( &mut self, value: NeuralNetworkImageShapeMapping, )

Sets image_input_shape_mapping to the provided enum value.

Trait Implementations

impl Clone for NeuralNetwork

fn clone(&self) -> NeuralNetwork

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NeuralNetwork

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

Formats the value using the given formatter.

impl Default for NeuralNetwork

fn default() -> Self

Returns the “default value” for a type.

impl Message for NeuralNetwork

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for NeuralNetwork

fn eq(&self, other: &NeuralNetwork) -> 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 StructuralPartialEq for NeuralNetwork