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#include "caffe2/operators/sinh_op.h"
#include <algorithm>
#include <functional>
namespace caffe2 {
template <>
template <typename T>
bool SinhGradientFunctor<CPUContext>::Forward(
const std::vector<int>& /* dY_dims */,
const std::vector<int>& X_dims,
const T* dY,
const T* X,
T* dX,
CPUContext* /* context */) const {
const int size = std::accumulate(
X_dims.cbegin(), X_dims.cend(), 1, std::multiplies<int>());
ConstEigenVectorArrayMap<T> dY_arr(dY, size);
ConstEigenVectorArrayMap<T> X_arr(X, size);
EigenVectorMap<T>(dX, size) = dY_arr * (X_arr.exp() + (-X_arr).exp()) / 2;
return true;
}
REGISTER_CPU_OPERATOR(
Sinh,
UnaryElementwiseOp<
TensorTypes<float>,
CPUContext,
SinhFunctor<CPUContext>>);
REGISTER_CPU_OPERATOR(
SinhGradient,
BinaryElementwiseOp<
TensorTypes<float>,
CPUContext,
SinhGradientFunctor<CPUContext>>);
OPERATOR_SCHEMA(Sinh)
.NumInputs(1)
.NumOutputs(1)
.IdenticalTypeAndShape()
.SetDoc(R"DOC(
Calculates the hyperbolic sine of the given input tensor, element-wise.
Github Links:
- https://github.com/pytorch/pytorch/blob/master/caffe2/operators/sinh_op.cc
<details>
<summary> <b>Example</b> </summary>
**Code**
```
workspace.ResetWorkspace()
op = core.CreateOperator(
"Sinh",
["X"],
["Y"]
)
workspace.FeedBlob("X", np.random.rand(5).astype(np.float32))
print("X:", workspace.FetchBlob("X"))
workspace.RunOperatorOnce(op)
print("Y:", workspace.FetchBlob("Y"))
```
**Result**
```
X: [0.98907769 0.52907848 0.03216429 0.94983935 0.47881418]
Y: [1.15841695 0.5541099 0.03216984 1.09924557 0.49732079]
```
</details>
)DOC")
.Input(0, "input", "Input tensor")
.Output(
0,
"output",
"The hyperbolic sine values of the input tensor, computed "
"element-wise")
.InheritOnnxSchema();
OPERATOR_SCHEMA(SinhGradient)
.NumInputs(2)
.NumOutputs(1)
.IdenticalTypeAndShape();
namespace {
class GetSinhGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"SinhGradient",
"",
std::vector<std::string>{GO(0), I(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
REGISTER_GRADIENT(Sinh, GetSinhGradient);
} // namespace caffe2
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