Update '*var' according to the adadelta scheme.
tf.raw_ops.ResourceApplyAdadelta(
var, accum, accum_update, lr, rho, epsilon, grad, use_locking=False, name=None
)
accum = rho() * accum + (1 - rho()) * grad.square(); update = (update_accum + epsilon).sqrt() * (accum + epsilon()).rsqrt() * grad; update_accum = rho() * update_accum + (1 - rho()) * update.square(); var -= update;
Args | |
|---|---|
var
|
A Tensor of type resource. Should be from a Variable().
|
accum
|
A Tensor of type resource. Should be from a Variable().
|
accum_update
|
A Tensor of type resource. Should be from a Variable().
|
lr
|
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64.
Scaling factor. Must be a scalar.
|
rho
|
A Tensor. Must have the same type as lr.
Decay factor. Must be a scalar.
|
epsilon
|
A Tensor. Must have the same type as lr.
Constant factor. Must be a scalar.
|
grad
|
A Tensor. Must have the same type as lr. The gradient.
|
use_locking
|
An optional bool. Defaults to False.
If True, updating of the var, accum and update_accum tensors will be protected by
a lock; otherwise the behavior is undefined, but may exhibit less contention.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
| The created Operation. |