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#include "caffe2/operators/mish_op.h"
#include <string>
#include <vector>
#include "caffe2/core/types.h"
#include "caffe2/utils/eigen_utils.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <>
template <typename T>
bool MishFunctor<CPUContext>::
operator()(const int N, const T* X, T* Y, CPUContext* context) const {
ConstEigenVectorArrayMap<T> X_arr(X, N);
EigenVectorArrayMap<T> Y_arr(Y, N);
math::Exp<T, CPUContext>(N, X, Y, context);
math::Log1p<T, CPUContext>(N, Y, Y, context);
Y_arr = X_arr * Y_arr.tanh();
return true;
}
template <>
template <typename T>
bool MishGradientOp<CPUContext>::DoRunWithType() {
const auto& X = Input(INPUT);
const auto& Y = Input(OUTPUT);
const auto& dY = Input(OUTPUT_GRAD);
CAFFE_ENFORCE_EQ(X.numel(), Y.numel());
CAFFE_ENFORCE_EQ(dY.numel(), Y.numel());
auto* dX = Output(INPUT_GRAD, X.sizes(), at::dtype<T>());
const T* X_data = X.template data<T>();
const T* Y_data = Y.template data<T>();
const T* dY_data = dY.template data<T>();
T* dX_data = dX->template mutable_data<T>();
const int64_t N = X.numel();
ConstEigenVectorArrayMap<T> X_arr(X_data, N);
ConstEigenVectorArrayMap<T> Y_arr(Y_data, N);
ConstEigenVectorArrayMap<T> dY_arr(dY_data, N);
EigenVectorArrayMap<T> dX_arr(dX_data, N);
math::Exp<T, CPUContext>(N, X_data, dX_data, &context_);
math::Log1p<T, CPUContext>(N, dX_data, dX_data, &context_);
math::Tanh<T, CPUContext>(N, dX_data, dX_data, &context_);
dX_arr = dY_arr *
(dX_arr +
X_arr * (T(1) - dX_arr.square()) * T(0.5) *
((X_arr * T(0.5)).tanh() + T(1)));
return true;
}
REGISTER_CPU_OPERATOR(
Mish,
UnaryElementwiseOp<
TensorTypes<float, double>,
CPUContext,
MishFunctor<CPUContext>>);
REGISTER_CPU_OPERATOR(MishGradient, MishGradientOp<CPUContext>);
// Input: X, output: Y
OPERATOR_SCHEMA(Mish)
.NumInputs(1)
.NumOutputs(1)
.IdenticalTypeAndShape()
.SetDoc(R"DOC(
Mish takes one input data (Tensor) and produces one output data
(Tensor) where the Mish function, y = x * tanh(ln(1 + exp(x))), is applied to the
tensor elementwise.
)DOC")
.Input(0, "X", "1D input tensor")
.Output(0, "Y", "1D output tensor");
// Input: X, Y, dY, output: dX
OPERATOR_SCHEMA(MishGradient).NumInputs(3).NumOutputs(1).SetDoc(R"DOC(
MishGradient takes X, Y and dY and uses this to update dX according to the
chain rule and derivatives of the Mish function.
)DOC");
namespace {
class GetMishGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"MishGradient",
"",
std::vector<std::string>{I(0), O(0), GO(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
REGISTER_GRADIENT(Mish, GetMishGradient);
} // namespace caffe2
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