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# C++ gradients
Gradients are currently being ported from
[python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python/ops)
to C++ (in this directory).
Contributions are welcome and much appreciated; please follow the instructions
below.
1. Create the op gradient function in `foo_grad.cc` corresponding to the
`foo_grad.py` file where the op originated (i.e. `array_grad.py` op
gradients should be written in `array_grad.cc`).
2. Write the op gradient with the following naming scheme:
Status OpNameGrad(const Scope& scope, const Operation& op,
const std::vector<Output>& grad_inputs,
std::vector<Output>* grad_outputs) {
...
return scope.status();
}
REGISTER_GRADIENT_OP("OpName", OpNameGrad);
3. Ops gradients are implemented by using the [C++
API](https://www.tensorflow.org/api_docs/cc/).
4. Tests should be included in `foo_grad_test.cc`. Please see
[`array_grad_test.cc`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/cc/gradients/array_grad_test.cc)
for an many examples. Tests are as simple as, creating a placeholder input
for the op's inputs and calling `RunTest` (`RunTest` uses a [gradient
checker](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/cc/framework/gradient_checker.cc)
to verify that the theoretical gradient matches the numeric gradient). For
example:
TEST_F(ArrayGradTest, IdentityGrad) {
TensorShape shape({5, 2});
auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape));
auto y = Identity(scope_, x);
RunTest(x, shape, y, shape);
}
NOTE: There are some ops that require features from the C++ API that are not yet
implemented.
* Ops that require PartialTensorShape information cannot yet be implemented.
* Ops that require SparseTensor or IndexSlices (currently only in python)
cannot yet be implemented.
* Maybe more.
For questions: Please create an issue assigned to suharshs.
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