Struct dfdx::nn::modules::AccurateGeLU
source · pub struct AccurateGeLU;
Expand description
Calls accurate_gelu(). The GeLU is defined as x * Phi(x) where Phi is the cumulative distribution function of a standard Normal Distribution.
It is often implemented with a fast approximation using tanh (see GeLU). This corresponds to pytorch torch.nn.GELU(approximate='none')
in pytorch.
Trait Implementations§
source§impl Clone for AccurateGeLU
impl Clone for AccurateGeLU
source§fn clone(&self) -> AccurateGeLU
fn clone(&self) -> AccurateGeLU
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 moresource§impl Debug for AccurateGeLU
impl Debug for AccurateGeLU
source§impl Default for AccurateGeLU
impl Default for AccurateGeLU
source§fn default() -> AccurateGeLU
fn default() -> AccurateGeLU
Returns the “default value” for a type. Read more
source§impl<S: Shape, E: Dtype, D: Device<E>, T: Tape<E, D>> Module<Tensor<S, E, D, T>> for AccurateGeLU
impl<S: Shape, E: Dtype, D: Device<E>, T: Tape<E, D>> Module<Tensor<S, E, D, T>> for AccurateGeLU
impl Copy for AccurateGeLU
impl NonMutableModule for AccurateGeLU
impl ZeroSizedModule for AccurateGeLU
Auto Trait Implementations§
impl RefUnwindSafe for AccurateGeLU
impl Send for AccurateGeLU
impl Sync for AccurateGeLU
impl Unpin for AccurateGeLU
impl UnwindSafe for AccurateGeLU
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<D, E, M> BuildModule<D, E> for Mwhere
D: Device<E>,
E: Dtype,
M: TensorCollection<E, D, To<E, D> = M>,
impl<D, E, M> BuildModule<D, E> for Mwhere D: Device<E>, E: Dtype, M: TensorCollection<E, D, To<E, D> = M>,
source§impl<T, D, E> BuildOnDevice<D, E> for Twhere
T: ZeroSizedModule + BuildModule<D, E>,
D: Device<E>,
E: Dtype,
impl<T, D, E> BuildOnDevice<D, E> for Twhere T: ZeroSizedModule + BuildModule<D, E>, D: Device<E>, E: Dtype,
source§impl<E, D, T> LoadFromNpz<E, D> for Twhere
E: Dtype + NumpyDtype,
D: Device<E>,
T: TensorCollection<E, D>,
impl<E, D, T> LoadFromNpz<E, D> for Twhere E: Dtype + NumpyDtype, D: Device<E>, T: TensorCollection<E, D>,
source§impl<E, D, T> LoadFromSafetensors<E, D> for Twhere
E: Dtype + SafeDtype,
D: Device<E>,
T: TensorCollection<E, D>,
impl<E, D, T> LoadFromSafetensors<E, D> for Twhere E: Dtype + SafeDtype, D: Device<E>, T: TensorCollection<E, D>,
source§impl<M, T> ModuleMut<T> for Mwhere
M: NonMutableModule + Module<T>,
impl<M, T> ModuleMut<T> for Mwhere M: NonMutableModule + Module<T>,
source§impl<E, D, M> NumParams<E, D> for Mwhere
E: Dtype,
D: Device<E>,
M: TensorCollection<E, D>,
impl<E, D, M> NumParams<E, D> for Mwhere E: Dtype, D: Device<E>, M: TensorCollection<E, D>,
source§fn num_trainable_params(&self) -> usize
fn num_trainable_params(&self) -> usize
Returns the number of trainable params in any model.
§impl<T> Pointable for T
impl<T> Pointable for T
source§impl<E, D, M> ResetParams<E, D> for Mwhere
E: Dtype,
D: Device<E>,
M: TensorCollection<E, D>,
impl<E, D, M> ResetParams<E, D> for Mwhere E: Dtype, D: Device<E>, M: TensorCollection<E, D>,
source§fn reset_params(&mut self)
fn reset_params(&mut self)
Reset all a model’s parameters.
source§impl<E, D, T> SaveToNpz<E, D> for Twhere
E: Dtype + NumpyDtype,
D: Device<E>,
T: TensorCollection<E, D>,
impl<E, D, T> SaveToNpz<E, D> for Twhere E: Dtype + NumpyDtype, D: Device<E>, T: TensorCollection<E, D>,
source§impl<E, D, T> SaveToSafetensors<E, D> for Twhere
E: Dtype + SafeDtype,
D: Device<E>,
T: TensorCollection<E, D>,
impl<E, D, T> SaveToSafetensors<E, D> for Twhere E: Dtype + SafeDtype, D: Device<E>, T: TensorCollection<E, D>,
source§fn save_safetensors<P: AsRef<Path>>(
&self,
path: P
) -> Result<(), SafeTensorError>
fn save_safetensors<P: AsRef<Path>>( &self, path: P ) -> Result<(), SafeTensorError>
source§impl<E, D, T> TensorCollection<E, D> for Twhere
E: Dtype,
D: Device<E>,
T: ZeroSizedModule,
impl<E, D, T> TensorCollection<E, D> for Twhere E: Dtype, D: Device<E>, T: ZeroSizedModule,
§type To<E2: Dtype, D2: Device<E2>> = T
type To<E2: Dtype, D2: Device<E2>> = T
Type alias that specifies the how a module’s type changes when using a different dtype and/or
device.
source§fn iter_tensors<V>(
visitor: &mut V
) -> Result<Option<<T as TensorCollection<E, D>>::To<<V as ModuleVisitor<T, E, D>>::E2, <V as ModuleVisitor<T, E, D>>::D2>>, <V as ModuleVisitor<T, E, D>>::Err>where
V: ModuleVisitor<T, E, D>,
fn iter_tensors<V>( visitor: &mut V ) -> Result<Option<<T as TensorCollection<E, D>>::To<<V as ModuleVisitor<T, E, D>>::E2, <V as ModuleVisitor<T, E, D>>::D2>>, <V as ModuleVisitor<T, E, D>>::Err>where V: ModuleVisitor<T, E, D>,
Specifies how to iterate through tensors or modules containted within this module, and how
to contruct this module given values for its fields. Returns
Err(_)
to indicate an error,
Ok(None)
to indicate that there is no error and a module has not been built, and
Ok(Some(_))
contains Self::Output<E2, D2>
source§fn module<F1, F2, Field>(
name: &str,
get_ref: F1,
get_mut: F2
) -> ModuleField<'_, F1, F2, Self, Field>where
F1: FnMut(&Self) -> &Field,
F2: FnMut(&mut Self) -> &mut Field,
Field: TensorCollection<E, D>,
fn module<F1, F2, Field>( name: &str, get_ref: F1, get_mut: F2 ) -> ModuleField<'_, F1, F2, Self, Field>where F1: FnMut(&Self) -> &Field, F2: FnMut(&mut Self) -> &mut Field, Field: TensorCollection<E, D>,
Creates a ModuleFields that represents a field that may contain one or more tensors. Read more
source§fn tensor<F1, F2, S>(
name: &str,
get_ref: F1,
get_mut: F2,
options: TensorOptions<S, E, D>
) -> TensorField<'_, F1, F2, Self, S, E, D>where
F1: FnMut(&Self) -> &Tensor<S, E, D>,
F2: FnMut(&mut Self) -> &mut Tensor<S, E, D>,
S: Shape,
fn tensor<F1, F2, S>( name: &str, get_ref: F1, get_mut: F2, options: TensorOptions<S, E, D> ) -> TensorField<'_, F1, F2, Self, S, E, D>where F1: FnMut(&Self) -> &Tensor<S, E, D>, F2: FnMut(&mut Self) -> &mut Tensor<S, E, D>, S: Shape,
Creates a ModuleFields that represents a tensor field. Read more
source§fn scalar<F1, F2, N>(
name: &str,
get_ref: F1,
get_mut: F2,
options: ScalarOptions<N>
) -> ScalarField<'_, F1, F2, Self, N>where
F1: FnMut(&Self) -> &N,
F2: FnMut(&mut Self) -> &mut N,
N: NumCast,
fn scalar<F1, F2, N>( name: &str, get_ref: F1, get_mut: F2, options: ScalarOptions<N> ) -> ScalarField<'_, F1, F2, Self, N>where F1: FnMut(&Self) -> &N, F2: FnMut(&mut Self) -> &mut N, N: NumCast,
Creates a ModuleFields that represents a scalar field. Read more
source§impl<E, D1, D2, T> ToDevice<E, D1, D2> for Twhere
E: Dtype,
D1: Device<E>,
D2: Device<E>,
T: TensorCollection<E, D1>,
impl<E, D1, D2, T> ToDevice<E, D1, D2> for Twhere E: Dtype, D1: Device<E>, D2: Device<E>, T: TensorCollection<E, D1>,
source§impl<E1, D, T> ToDtype<E1, D> for Twhere
E1: Dtype,
D: Device<E1>,
T: TensorCollection<E1, D>,
impl<E1, D, T> ToDtype<E1, D> for Twhere E1: Dtype, D: Device<E1>, T: TensorCollection<E1, D>,
source§impl<E, D, M> ZeroGrads<E, D> for Mwhere
E: Dtype,
D: Device<E>,
M: TensorCollection<E, D>,
impl<E, D, M> ZeroGrads<E, D> for Mwhere E: Dtype, D: Device<E>, M: TensorCollection<E, D>,
source§fn alloc_grads(&self) -> Gradients<E, D>
fn alloc_grads(&self) -> Gradients<E, D>
Allocates gradients for this tensor collection. This marks all other
gradients as temporary, so they are dropped after .backward()
source§fn try_alloc_grads(&self) -> Result<Gradients<E, D>, D::Err>
fn try_alloc_grads(&self) -> Result<Gradients<E, D>, D::Err>
Allocates gradients for this tensor collection. This marks all other
gradients as temporary, so they are dropped after .backward()
source§fn zero_grads(&self, gradients: &mut Gradients<E, D>)
fn zero_grads(&self, gradients: &mut Gradients<E, D>)
Zero’s any gradients associated with
self
.