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@ -31,8 +31,6 @@ template <typename Place, typename T>
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class MulKernel : public framework::OpKernel {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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// Eigen::array<Eigen::IndexPair<Eigen::DenseIndex>, 1> dim_pair = {
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// {Eigen::IndexPair<Eigen::DenseIndex>(1, 0)}};
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auto* X = context.Input<Tensor>("X");
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auto* Y = context.Input<Tensor>("Y");
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auto* Z = context.Output<Tensor>("Out");
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@ -40,13 +38,6 @@ class MulKernel : public framework::OpKernel {
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auto* device_context =
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const_cast<platform::DeviceContext*>(context.device_context_);
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math::matmul<Place, T>(*X, false, *Y, false, 1, Z, 0, device_context);
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// auto X = EigenMatrix<T>::From(*input0);
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// auto Y = EigenMatrix<T>::From(*input1);
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// auto Z = EigenMatrix<T>::From(*output);
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// auto& place = context.GetEigenDevice<Place>();
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// Z.device(place) = X.contract(Y, dim_pair);
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}
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};
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@ -60,25 +51,10 @@ class MulGradKernel : public framework::OpKernel {
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auto* dX = ctx.Output<Tensor>(framework::GradVarName("X"));
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auto* dY = ctx.Output<Tensor>(framework::GradVarName("Y"));
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// auto* dXdata = dX->template mutable_data<T>(ctx.GetPlace());
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// auto* dYdata = dY->template mutable_data<T>(ctx.GetPlace());
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auto* device_context =
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const_cast<platform::DeviceContext*>(ctx.device_context_);
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math::matmul<Place, T>(*dOut, false, *Y, true, 1, dX, 0, device_context);
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math::matmul<Place, T>(*X, true, *dOut, false, 1, dY, 0, device_context);
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// auto X = EigenMatrix<T>::From(*input0);
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// auto Y = EigenMatrix<T>::From(*input1);
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// auto dOut = EigenMatrix<T>::From(*input2);
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// auto dX = EigenMatrix<T>::From(*output0);
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// auto dY = EigenMatrix<T>::From(*output1);
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// dX = Out@G * Y'
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// dY = X' * Out@G
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// auto place = ctx.GetEigenDevice<Place>();
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// TODO(dzh,qijun) : need transpose feature of blas library
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// Eigen Tensor does not support it very well
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// dX.device(place) = matmul(input2, )
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}
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};
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