Struct tensorflow::eager::raw_ops::SparseApplyAdagrad

pub struct SparseApplyAdagrad { /* private fields */ }

SparseApplyAdagrad

See : https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseApplyAdagrad

Implementations

impl SparseApplyAdagrad

pub fn new() -> Self

Creates a new SparseApplyAdagrad.

pub fn use_locking<ArgType: Into<bool>>(self, value: ArgType) -> Self

Sets the use_locking attribute.

pub fn update_slots<ArgType: Into<bool>>(self, value: ArgType) -> Self

Sets the update_slots attribute.

pub fn target_device_name<ArgType: Into<String>>(self, value: ArgType) -> Self

Sets the `` attribute.

pub fn call<'a, T0: ToTensorHandle<'a>, T1: ToTensorHandle<'a>, T2: ToTensorHandle<'a>, T3: ToTensorHandle<'a>, T4: ToTensorHandle<'a>>( &self, ctx: &'a Context, var: &T0, accum: &T1, lr: &T2, grad: &T3, indices: &T4 ) -> Result<TensorHandle<'a>>

Execute sparse_apply_adagrad.

Trait Implementations

impl Clone for SparseApplyAdagrad

fn clone(&self) -> SparseApplyAdagrad

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for SparseApplyAdagrad

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

Formats the value using the given formatter.

impl Default for SparseApplyAdagrad

fn default() -> Self

Returns the “default value” for a type.