# tensorflow::ops::ApplyAdam

`#include <training_ops.h>`

Update '*var' according to the Adam algorithm.

## Summary

\$\$lr_t := {learning_rate} * {(1 - beta_2^t) / (1 - beta_1^t)}\$\$ \$\$m_t := beta_1 * m_{t-1} + (1 - beta_1) * g\$\$ \$\$v_t := beta_2 * v_{t-1} + (1 - beta_2) * g * g\$\$ \$\$variable := variable - lr_t * m_t / ({v_t} + )\$\$

Arguments:

• scope: A Scope object
• var: Should be from a Variable().
• m: Should be from a Variable().
• v: Should be from a Variable().
• beta1_power: Must be a scalar.
• beta2_power: Must be a scalar.
• lr: Scaling factor. Must be a scalar.
• beta1: Momentum factor. Must be a scalar.
• beta2: Momentum factor. Must be a scalar.
• epsilon: Ridge term. Must be a scalar.
• grad: The gradient.

Optional attributes (see `Attrs`):

• use_locking: If `True`, updating of the var, m, and v tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
• use_nesterov: If `True`, uses the nesterov update.

Returns:

• `Output`: Same as "var".

### Constructors and Destructors

`ApplyAdam(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input m, ::tensorflow::Input v, ::tensorflow::Input beta1_power, ::tensorflow::Input beta2_power, ::tensorflow::Input lr, ::tensorflow::Input beta1, ::tensorflow::Input beta2, ::tensorflow::Input epsilon, ::tensorflow::Input grad)`
`ApplyAdam(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input m, ::tensorflow::Input v, ::tensorflow::Input beta1_power, ::tensorflow::Input beta2_power, ::tensorflow::Input lr, ::tensorflow::Input beta1, ::tensorflow::Input beta2, ::tensorflow::Input epsilon, ::tensorflow::Input grad, const ApplyAdam::Attrs & attrs)`

### Public attributes

`out`
`::tensorflow::Output`

### Public functions

`node() const `
`::tensorflow::Node *`
`operator::tensorflow::Input() const `
``` ```
``` ```
`operator::tensorflow::Output() const `
``` ```
``` ```

### Public static functions

`UseLocking(bool x)`
`Attrs`
`UseNesterov(bool x)`
`Attrs`

### Structs

tensorflow::ops::ApplyAdam::Attrs

Optional attribute setters for ApplyAdam.

## Public attributes

### out

`::tensorflow::Output out`

## Public functions

### ApplyAdam

``` ApplyAdam(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input m,
::tensorflow::Input v,
::tensorflow::Input beta1_power,
::tensorflow::Input beta2_power,
::tensorflow::Input lr,
::tensorflow::Input beta1,
::tensorflow::Input beta2,
::tensorflow::Input epsilon,
::tensorflow::Input grad
)```

### ApplyAdam

``` ApplyAdam(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input m,
::tensorflow::Input v,
::tensorflow::Input beta1_power,
::tensorflow::Input beta2_power,
::tensorflow::Input lr,
::tensorflow::Input beta1,
::tensorflow::Input beta2,
::tensorflow::Input epsilon,
::tensorflow::Input grad,
const ApplyAdam::Attrs & attrs
)```

### node

`::tensorflow::Node * node() const `

### operator::tensorflow::Input

` operator::tensorflow::Input() const `

### operator::tensorflow::Output

` operator::tensorflow::Output() const `

## Public static functions

### UseLocking

```Attrs UseLocking(
bool x
)```

### UseNesterov

```Attrs UseNesterov(
bool x
)```