IdentityN
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Returns a list of tensors with the same shapes and contents as the input
tensors.
This op can be used to override the gradient for complicated functions. For
example, suppose y = f(x) and we wish to apply a custom function g for backprop
such that dx = g(dy). In Python,
{@code
with tf.get_default_graph().gradient_override_map(
{'IdentityN': 'OverrideGradientWithG'}):
y, _ = identity_n([f(x), x])
Inherited Methods
From class
java.lang.Object
boolean
|
equals(Object arg0)
|
final
Class<?>
|
getClass()
|
int
|
hashCode()
|
final
void
|
notify()
|
final
void
|
notifyAll()
|
String
|
toString()
|
final
void
|
wait(long arg0, int arg1)
|
final
void
|
wait(long arg0)
|
final
void
|
wait()
|
From interface
java.lang.Iterable
void
|
forEach(Consumer<? super T> arg0)
|
abstract
Iterator<Operand<Object>>
|
iterator()
|
Spliterator<Operand<Object>>
|
spliterator()
|
Public Methods
Factory method to create a class wrapping a new IdentityN operation.
Returns
- a new instance of IdentityN
public
Iterator<Operand<Object>>
iterator
()
public
List<Output<?>>
output
()
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Last updated 2022-10-27 UTC.
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