Struct burn::nn::transformer::TransformerDecoderConfig
pub struct TransformerDecoderConfig {
pub d_model: usize,
pub d_ff: usize,
pub n_heads: usize,
pub n_layers: usize,
pub dropout: f64,
pub norm_first: bool,
pub quiet_softmax: bool,
pub initializer: Initializer,
}
Expand description
Configuration to create a Transformer Decoder layer using the init function.
Fields§
§d_model: usize
The size of the model.
d_ff: usize
The size of the position-wise feed-forward network.
n_heads: usize
The number of attention heads.
n_layers: usize
The number of layers.
dropout: f64
The dropout rate. Default: 0.1
norm_first: bool
Layer norm will be applied first instead of after the other modules.
quiet_softmax: bool
Use “quiet softmax” instead of regular softmax.
- Usage may improve performance by allowing attention heads to deposit no information (if the sequence contains no information relevant to that head).
- Usage may reduce the entropy of weights in the model, enhancing quantization and compression.
Reference: https://www.evanmiller.org/attention-is-off-by-one.html
initializer: Initializer
The type of function used to initialize neural network parameters
Implementations§
§impl TransformerDecoderConfig
impl TransformerDecoderConfig
pub fn with_dropout(self, dropout: f64) -> TransformerDecoderConfig
pub fn with_dropout(self, dropout: f64) -> TransformerDecoderConfig
The dropout rate. Default: 0.1
pub fn with_norm_first(self, norm_first: bool) -> TransformerDecoderConfig
pub fn with_norm_first(self, norm_first: bool) -> TransformerDecoderConfig
Layer norm will be applied first instead of after the other modules.
pub fn with_quiet_softmax(self, quiet_softmax: bool) -> TransformerDecoderConfig
pub fn with_quiet_softmax(self, quiet_softmax: bool) -> TransformerDecoderConfig
Use “quiet softmax” instead of regular softmax.
pub fn with_initializer(
self,
initializer: Initializer,
) -> TransformerDecoderConfig
pub fn with_initializer( self, initializer: Initializer, ) -> TransformerDecoderConfig
The type of function used to initialize neural network parameters
§impl TransformerDecoderConfig
impl TransformerDecoderConfig
pub fn init<B>(&self, device: &<B as Backend>::Device) -> TransformerDecoder<B>where
B: Backend,
pub fn init<B>(&self, device: &<B as Backend>::Device) -> TransformerDecoder<B>where
B: Backend,
Initialize a new Transformer Decoder module.
Trait Implementations§
§impl Clone for TransformerDecoderConfig
impl Clone for TransformerDecoderConfig
§fn clone(&self) -> TransformerDecoderConfig
fn clone(&self) -> TransformerDecoderConfig
Returns a copy of the value. Read more
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source
. Read more§impl Config for TransformerDecoderConfig
impl Config for TransformerDecoderConfig
§impl<'de> Deserialize<'de> for TransformerDecoderConfig
impl<'de> Deserialize<'de> for TransformerDecoderConfig
§fn deserialize<D>(
deserializer: D,
) -> Result<TransformerDecoderConfig, <D as Deserializer<'de>>::Error>where
D: Deserializer<'de>,
fn deserialize<D>(
deserializer: D,
) -> Result<TransformerDecoderConfig, <D as Deserializer<'de>>::Error>where
D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
§impl Display for TransformerDecoderConfig
impl Display for TransformerDecoderConfig
§impl Serialize for TransformerDecoderConfig
impl Serialize for TransformerDecoderConfig
§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,
Serialize this value into the given Serde serializer. Read more
Auto Trait Implementations§
impl Freeze for TransformerDecoderConfig
impl RefUnwindSafe for TransformerDecoderConfig
impl Send for TransformerDecoderConfig
impl Sync for TransformerDecoderConfig
impl Unpin for TransformerDecoderConfig
impl UnwindSafe for TransformerDecoderConfig
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
source§unsafe fn clone_to_uninit(&self, dst: *mut T)
unsafe fn clone_to_uninit(&self, dst: *mut T)
🔬This is a nightly-only experimental API. (
clone_to_uninit
)§impl<T> Instrument for T
impl<T> Instrument for T
§fn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
§fn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
source§impl<T> IntoEither for T
impl<T> IntoEither for T
source§fn into_either(self, into_left: bool) -> Either<Self, Self>
fn into_either(self, into_left: bool) -> Either<Self, Self>
Converts
self
into a Left
variant of Either<Self, Self>
if into_left
is true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read moresource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
Converts
self
into a Left
variant of Either<Self, Self>
if into_left(&self)
returns true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read more§impl<T> Pointable for T
impl<T> Pointable for T
§impl<T> ToCompactString for Twhere
T: Display,
impl<T> ToCompactString for Twhere
T: Display,
§fn try_to_compact_string(&self) -> Result<CompactString, ToCompactStringError>
fn try_to_compact_string(&self) -> Result<CompactString, ToCompactStringError>
Fallible version of [
ToCompactString::to_compact_string()
] Read more§fn to_compact_string(&self) -> CompactString
fn to_compact_string(&self) -> CompactString
Converts the given value to a [
CompactString
]. Read more