Update '*var' according to the adagrad scheme.
accum += grad * grad var -= lr * grad * (1 / sqrt(accum))
Nested Classes
class | ApplyAdagrad.Options | Optional attributes for ApplyAdagrad
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Constants
String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
Output<T> |
asOutput()
Returns the symbolic handle of the tensor.
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static <T extends TType> ApplyAdagrad<T> | |
Output<T> |
out()
Same as "var".
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static ApplyAdagrad.Options |
updateSlots(Boolean updateSlots)
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static ApplyAdagrad.Options |
useLocking(Boolean useLocking)
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Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public Output<T> asOutput ()
Returns the symbolic handle of the tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static ApplyAdagrad<T> create (Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Options... options)
Factory method to create a class wrapping a new ApplyAdagrad operation.
Parameters
scope | current scope |
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var | Should be from a Variable(). |
accum | Should be from a Variable(). |
lr | Scaling factor. Must be a scalar. |
grad | The gradient. |
options | carries optional attributes values |
Returns
- a new instance of ApplyAdagrad
public static ApplyAdagrad.Options useLocking (Boolean useLocking)
Parameters
useLocking | 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. |
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