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#include <cmath>
#include "caffe2/operators/elementwise_op.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
struct TanhCPUFunctor {
template <typename T>
inline void operator()(const int n, const T* x,
T* y, CPUContext* device_context) {
#ifdef CAFFE2_USE_ACCELERATE
vvtanhf(y, x, &n);
#else
ConstEigenVectorArrayMap<T> x_arr(x, n);
EigenVectorMap<T>(y, n) = 1 - 2 * ((x_arr * 2).exp() + 1).inverse();
#endif
}
};
struct TanhGradientCPUFunctor {
template <typename T>
inline void
Run(const int n, const T* y, const T* dy, T* dx, CPUContext* device_context) {
ConstEigenVectorArrayMap<T> dy_arr(dy, n);
ConstEigenVectorArrayMap<T> y_arr(y, n);
EigenVectorMap<T>(dx, n) = dy_arr * (1 - y_arr * y_arr);
}
};
namespace {
REGISTER_CPU_OPERATOR(
Tanh, UnaryElementwiseOp<TensorTypes<float>, CPUContext, TanhCPUFunctor>);
REGISTER_CPU_OPERATOR(
TanhGradient,
BinaryElementwiseOp<
TensorTypes<float>,
CPUContext,
WithoutBroadcast<TanhGradientCPUFunctor>>);
OPERATOR_SCHEMA(Tanh)
.NumInputs(1)
.NumOutputs(1)
.AllowInplace({{0, 0}})
.IdenticalTypeAndShape()
.SetDoc(R"DOC(
Calculates the hyperbolic tangent of the given input tensor element-wise. This
operation can be done in an in-place fashion too, by providing the same input
and output blobs.
)DOC")
.Input(0, "input", "1-D input tensor")
.Output(0, "output", "The hyperbolic tangent values of the input tensor "
"computed element-wise");
OPERATOR_SCHEMA(TanhGradient).NumInputs(2).NumOutputs(1).AllowInplace({{1, 0}});
class GetTanhGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"TanhGradient", "",
std::vector<string>{O(0), GO(0)},
std::vector<string>{GI(0)});
}
};
REGISTER_GRADIENT(Tanh, GetTanhGradient);
} // namespace
} // namespace caffe2
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