#include <array_ops.h>
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,
```python with tf.get_default_graph().gradient_override_map( {'IdentityN': 'OverrideGradientWithG'}): y, _ = identity_n([f(x), x])
.RegisterGradient('OverrideGradientWithG') def ApplyG(op, dy, _): return [None, g(dy)] # Do not backprop to f(x). ```
Arguments:
Returns:
OutputList
: The output tensor. Constructors and Destructors | |
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IdentityN(const ::tensorflow::Scope & scope, ::tensorflow::InputList input) |
Public attributes | |
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output |
Public functions | |
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operator[](size_t index) const |
::tensorflow::OutputList output
IdentityN( const ::tensorflow::Scope & scope, ::tensorflow::InputList input )
::tensorflow::Output operator[]( size_t index ) const
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/identity-n.html