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#include "caffe2/operators/abs_op.h"
#include "caffe2/utils/eigen_utils.h"
#include <algorithm>
#include <functional>
namespace caffe2 {
template <>
template <typename T>
bool AbsGradientFunctor<CPUContext>::Forward(
const std::vector<int>& X_dims,
const std::vector<int>& /* dY_dims */,
const T* X,
const T* dY,
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) =
(X_arr == T(0)).select(T(0), (X_arr > T(0)).select(dY_arr, -dY_arr));
return true;
}
REGISTER_CPU_OPERATOR(
Abs,
UnaryElementwiseOp<TensorTypes<float>, CPUContext, AbsFunctor<CPUContext>>);
REGISTER_CPU_OPERATOR(
AbsGradient,
BinaryElementwiseOp<
TensorTypes<float>,
CPUContext,
AbsGradientFunctor<CPUContext>>);
OPERATOR_SCHEMA(Abs)
.NumInputs(1)
.NumOutputs(1)
.IdenticalTypeAndShape()
.SetDoc(R"DOC(
Calculates the absolute value of the given input tensor, element-wise.
Github Links:
- https://github.com/pytorch/pytorch/blob/master/caffe2/operators/abs_op.cc
<details>
<summary> <b>Example</b> </summary>
**Code**
```
workspace.ResetWorkspace()
op = core.CreateOperator(
"Abs",
["X"],
["Y"]
)
workspace.FeedBlob("X", np.random.randn(5).astype(np.float32))
print("X:", workspace.FetchBlob("X"))
workspace.RunOperatorOnce(op)
print("Y:", workspace.FetchBlob("Y"))
```
**Result**
```
X: [ 0.3005476 1.551666 -1.3591481 0.39191285 -0.21866608]
Y: [0.3005476 1.551666 1.3591481 0.39191285 0.21866608]
```
</details>
)DOC")
.Input(0, "X", "*(type: Tensor<float>)* Input tensor.")
.Output(
0,
"Y",
"*(type: Tensor`<float>`)* Absolute value of input element-wise.")
.InheritOnnxSchema();
OPERATOR_SCHEMA(AbsGradient).NumInputs(2).NumOutputs(1).IdenticalTypeAndShape();
namespace {
class GetAbsGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"AbsGradient",
"",
std::vector<std::string>{I(0), GO(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
REGISTER_GRADIENT(Abs, GetAbsGradient);
} // namespace caffe2
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