Struct tensorflow::eager::raw_ops::SparseApplyAdagradV2

pub struct SparseApplyAdagradV2 { /* private fields */ }

SparseApplyAdagradV2

See : https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseApplyAdagradV2

Implementations

impl SparseApplyAdagradV2

pub fn new() -> Self

Creates a new SparseApplyAdagradV2.

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>, T5: ToTensorHandle<'a>>( &self, ctx: &'a Context, var: &T0, accum: &T1, lr: &T2, epsilon: &T3, grad: &T4, indices: &T5 ) -> Result<TensorHandle<'a>>

Execute sparse_apply_adagrad_v2.

Trait Implementations

impl Clone for SparseApplyAdagradV2

fn clone(&self) -> SparseApplyAdagradV2

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for SparseApplyAdagradV2

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

Formats the value using the given formatter.

impl Default for SparseApplyAdagradV2

fn default() -> Self

Returns the “default value” for a type.