tf.raw_ops.ResourceApplyAdagrad
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Update '*var' according to the adagrad scheme.
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Compat aliases for migration
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more details.
tf.compat.v1.raw_ops.ResourceApplyAdagrad
tf.raw_ops.ResourceApplyAdagrad(
var, accum, lr, grad, use_locking=False, update_slots=True, name=None
)
accum += grad * grad
var -= lr * grad * (1 / sqrt(accum))
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 , qint16 , quint16 , uint16 , complex128 , half , uint32 , uint64 .
Scaling 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.
|
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Last updated 2024-04-26 UTC.
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