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,
with tf.get_default_graph().gradient_override_map(
{'IdentityN': 'OverrideGradientWithG'
):
y, _ = identity_n([f(x), x])
Public Methods
static IdentityN | |
Iterator< Operand <Object>> |
iterator
()
|
List< Output <?>> |
output
()
|
Inherited Methods
Public Methods
public static IdentityN create ( Scope scope, Iterable< Operand <?>> input)
Factory method to create a class wrapping a new IdentityN operation.
Parameters
scope | current scope |
---|
Returns
- a new instance of IdentityN