Struct 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,
}
Expand description
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
impl ConvTranspose2dConfig
pub fn with_stride(self, stride: [usize; 2]) -> ConvTranspose2dConfig
pub fn with_stride(self, stride: [usize; 2]) -> ConvTranspose2dConfig
The stride of the convolution.
pub fn with_dilation(self, dilation: [usize; 2]) -> ConvTranspose2dConfig
pub fn with_dilation(self, dilation: [usize; 2]) -> ConvTranspose2dConfig
Spacing between kernel elements.
pub fn with_groups(self, groups: usize) -> ConvTranspose2dConfig
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
pub fn with_padding(self, padding: [usize; 2]) -> ConvTranspose2dConfig
The padding configuration.
pub fn with_padding_out(self, padding_out: [usize; 2]) -> ConvTranspose2dConfig
pub fn with_padding_out(self, padding_out: [usize; 2]) -> ConvTranspose2dConfig
The padding output configuration.
pub fn with_bias(self, bias: bool) -> ConvTranspose2dConfig
pub fn with_bias(self, bias: bool) -> ConvTranspose2dConfig
If bias should be added to the output.
pub fn with_initializer(self, initializer: Initializer) -> ConvTranspose2dConfig
pub fn with_initializer(self, initializer: Initializer) -> ConvTranspose2dConfig
The type of function used to initialize neural network parameters
§impl ConvTranspose2dConfig
impl ConvTranspose2dConfig
pub fn init<B>(&self, device: &<B as Backend>::Device) -> ConvTranspose2d<B>where
B: Backend,
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
impl Clone for ConvTranspose2dConfig
§fn clone(&self) -> ConvTranspose2dConfig
fn clone(&self) -> ConvTranspose2dConfig
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read more§impl Config for ConvTranspose2dConfig
impl Config for ConvTranspose2dConfig
§impl Debug for ConvTranspose2dConfig
impl Debug for ConvTranspose2dConfig
§impl<'de> Deserialize<'de> for ConvTranspose2dConfig
impl<'de> Deserialize<'de> for ConvTranspose2dConfig
§fn deserialize<D>(
deserializer: D,
) -> Result<ConvTranspose2dConfig, <D as Deserializer<'de>>::Error>where
D: Deserializer<'de>,
fn deserialize<D>(
deserializer: D,
) -> Result<ConvTranspose2dConfig, <D as Deserializer<'de>>::Error>where
D: Deserializer<'de>,
§impl Display for ConvTranspose2dConfig
impl Display for ConvTranspose2dConfig
§impl Serialize for ConvTranspose2dConfig
impl Serialize for ConvTranspose2dConfig
§fn serialize<S>(
&self,
serializer: S,
) -> Result<<S as Serializer>::Ok, <S as Serializer>::Error>where
S: Serializer,
fn serialize<S>(
&self,
serializer: S,
) -> Result<<S as Serializer>::Ok, <S as Serializer>::Error>where
S: Serializer,
Auto Trait Implementations§
impl Freeze for ConvTranspose2dConfig
impl RefUnwindSafe for ConvTranspose2dConfig
impl Send for ConvTranspose2dConfig
impl Sync for ConvTranspose2dConfig
impl Unpin for ConvTranspose2dConfig
impl UnwindSafe for ConvTranspose2dConfig
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T: ?Sized,
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T: Clone,
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