Struct burn::nn::conv::ConvTranspose2dConfig

pub struct ConvTranspose2dConfig {
    pub channels: [usize; 2],
    pub kernel_size: [usize; 2],
    pub stride: [usize; 2],
    pub dilation: [usize; 2],
    pub groups: usize,
    pub padding: [usize; 2],
    pub padding_out: [usize; 2],
    pub bias: bool,
    pub initializer: Initializer,
}

Configuration to create an 2D transposed convolution layer using the init function.

Fields

channels: [usize; 2]

The number of channels.

kernel_size: [usize; 2]

The size of the kernel.

stride: [usize; 2]

The stride of the convolution.

dilation: [usize; 2]

Spacing between kernel elements.

groups: usize

Controls the connections between input and output channels.

padding: [usize; 2]

The padding configuration.

padding_out: [usize; 2]

The padding output configuration.

bias: bool

If bias should be added to the output.

initializer: Initializer

The type of function used to initialize neural network parameters

Implementations

impl ConvTranspose2dConfig

pub fn new( channels: [usize; 2], kernel_size: [usize; 2], ) -> ConvTranspose2dConfig

Create a new instance of the config.

impl ConvTranspose2dConfig

pub fn with_stride(self, stride: [usize; 2]) -> ConvTranspose2dConfig

The stride of the convolution.

pub fn with_dilation(self, dilation: [usize; 2]) -> ConvTranspose2dConfig

Spacing between kernel elements.

pub fn with_groups(self, groups: usize) -> ConvTranspose2dConfig

Controls the connections between input and output channels.

pub fn with_padding(self, padding: [usize; 2]) -> ConvTranspose2dConfig

The padding configuration.

pub fn with_padding_out(self, padding_out: [usize; 2]) -> ConvTranspose2dConfig

The padding output configuration.

pub fn with_bias(self, bias: bool) -> ConvTranspose2dConfig

If bias should be added to the output.

pub fn with_initializer(self, initializer: Initializer) -> ConvTranspose2dConfig

The type of function used to initialize neural network parameters

impl ConvTranspose2dConfig

pub fn init<B>(&self, device: &<B as Backend>::Device) -> ConvTranspose2d<B>

where B: Backend,

Initialize a new conv transpose 2d module.

Trait Implementations

impl Clone for ConvTranspose2dConfig

fn clone(&self) -> ConvTranspose2dConfig

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Config for ConvTranspose2dConfig

fn save<P>(&self, file: P) -> Result<(), Error>

where P: AsRef<Path>,

Saves the configuration to a file.

fn load<P>(file: P) -> Result<Self, ConfigError>

where P: AsRef<Path>,

Loads the configuration from a file.

fn load_binary(data: &[u8]) -> Result<Self, ConfigError>

Loads the configuration from a binary buffer.

impl Debug for ConvTranspose2dConfig

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for ConvTranspose2dConfig

fn deserialize<D>( deserializer: D, ) -> Result<ConvTranspose2dConfig, <D as Deserializer<'de>>::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for ConvTranspose2dConfig

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

Formats the value using the given formatter.

impl Serialize for ConvTranspose2dConfig

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.