Struct Conv3dConfig 

pub struct Conv3dConfig {
    pub channels: [usize; 2],
    pub kernel_size: [usize; 3],
    pub stride: [usize; 3],
    pub dilation: [usize; 3],
    pub groups: usize,
    pub padding: PaddingConfig3d,
    pub bias: bool,
    pub initializer: Initializer,
}

Configuration to create a 3D convolution layer, using the init function.

Fields

channels: [usize; 2]

The number of channels.

kernel_size: [usize; 3]

The size of the kernel.

stride: [usize; 3]

The stride of the convolution.

dilation: [usize; 3]

Spacing between kernel elements.

groups: usize

Controls the connections between input and output channels.

padding: PaddingConfig3d

The padding 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 Conv3dConfig

pub fn new(channels: [usize; 2], kernel_size: [usize; 3]) -> Conv3dConfig

Create a new instance of the config.

Arguments

Required Arguments

channels

The number of channels.

kernel_size

The size of the kernel.

Default Arguments

stride

The stride of the convolution.

• Defaults to "[1, 1, 1]"

dilation

Spacing between kernel elements.

• Defaults to "[1, 1, 1]"

groups

Controls the connections between input and output channels.

• Defaults to "1"

padding

The padding configuration.

• Defaults to "PaddingConfig3d::Valid"

bias

If bias should be added to the output.

• Defaults to true

initializer

The type of function used to initialize neural network parameters

• Defaults to "Initializer::KaimingUniform{gain:1.0/num_traits::Float::sqrt(3.0),fan_out_only:false}"

impl Conv3dConfig

pub fn with_stride(self, stride: [usize; 3]) -> Conv3dConfig

Sets the value for the field stride.

The stride of the convolution.

• Defaults to "[1, 1, 1]"

pub fn with_dilation(self, dilation: [usize; 3]) -> Conv3dConfig

Sets the value for the field dilation.

Spacing between kernel elements.

• Defaults to "[1, 1, 1]"

pub fn with_groups(self, groups: usize) -> Conv3dConfig

Sets the value for the field groups.

Controls the connections between input and output channels.

• Defaults to "1"

pub fn with_padding(self, padding: PaddingConfig3d) -> Conv3dConfig

Sets the value for the field padding.

The padding configuration.

• Defaults to "PaddingConfig3d::Valid"

pub fn with_bias(self, bias: bool) -> Conv3dConfig

Sets the value for the field bias.

If bias should be added to the output.

• Defaults to true

pub fn with_initializer(self, initializer: Initializer) -> Conv3dConfig

Sets the value for the field initializer.

The type of function used to initialize neural network parameters

• Defaults to "Initializer::KaimingUniform{gain:1.0/num_traits::Float::sqrt(3.0),fan_out_only:false}"

impl Conv3dConfig

pub fn init<B>(&self, device: &<B as BackendTypes>::Device) -> Conv3d<B>

where B: Backend,

Initialize a new conv3d module.

Trait Implementations

impl Clone for Conv3dConfig

fn clone(&self) -> Conv3dConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Config for Conv3dConfig

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 Conv3dConfig

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for Conv3dConfig

fn deserialize<D>( deserializer: D, ) -> Result<Conv3dConfig, <D as Deserializer<'de>>::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for Conv3dConfig

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

Formats the value using the given formatter.

impl Serialize for Conv3dConfig

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.