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#ifndef TENSORFLOW_KERNELS_SOFTPLUS_OP_H_
#define TENSORFLOW_KERNELS_SOFTPLUS_OP_H_
// Functor definition for SoftplusOp and SoftplusGradOp, must be compilable by
// nvcc.
#include "tensorflow/core/framework/tensor_types.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
namespace tensorflow {
namespace functor {
// Functor used by SoftplusOp to do the computations.
template <typename Device, typename T>
struct Softplus {
// Computes Softplus activation.
//
// features: any shape.
// activations: same shape as "features".
void operator()(const Device& d, typename TTypes<T>::ConstTensor features,
typename TTypes<T>::Tensor activations) {
activations.device(d) =
(features > features.constant(30.f))
.select(features, (features.exp() + features.constant(1.0f)).log());
}
};
// Functor used by SoftplusGradOp to do the computations.
template <typename Device, typename T>
struct SoftplusGrad {
// Computes SoftplusGrad backprops.
//
// gradients: gradients backpropagated to the Softplus op.
// features: inputs that where passed to the Softplus op.
// backprops: gradients to backpropagate to the Softplus inputs.
void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients,
typename TTypes<T>::ConstTensor features,
typename TTypes<T>::Tensor backprops) {
backprops.device(d) =
gradients / ((-features).exp() + features.constant(1.0f));
}
};
} // namespace functor
} // namespace tensorflow
#endif // TENSORFLOW_KERNELS_SOFTPLUS_OP_H_
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