Update '*var' according to the adagrad scheme.
tf.raw_ops.ResourceApplyAdagradV2(
var, accum, lr, epsilon, grad, use_locking=False, update_slots=True, name=None
)
accum += grad * grad var -= lr * grad * (1 / (sqrt(accum) + epsilon))
Args | |
---|---|
var
|
A Tensor of type resource . Should be from a Variable().
|
accum
|
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.
|
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 and accum tensors will be protected
by a lock; otherwise the behavior is undefined, but may exhibit less
contention.
|
update_slots
|
An optional bool . Defaults to True .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
The created Operation. |