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move elementwise mul grad (#40252)
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@YuanRisheng
YuanRisheng authored Mar 9, 2022
1 parent 0604df9 commit 452c75b
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Showing 12 changed files with 539 additions and 401 deletions.
2 changes: 1 addition & 1 deletion paddle/fluid/framework/new_executor/standalone_executor_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@ USE_OP(matmul_grad);
USE_OP(square);
USE_OP(transpose2_grad);
USE_OP(concat_grad);
USE_OP(elementwise_mul_grad);
USE_OP_ITSELF(elementwise_mul_grad);
USE_OP(sigmoid_grad);
USE_OP(tanh_grad);
USE_OP(sum);
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41 changes: 0 additions & 41 deletions paddle/fluid/operators/elementwise/elementwise_functor.h
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Original file line number Diff line number Diff line change
Expand Up @@ -196,47 +196,6 @@ struct MinGradXYFunctor {
}
};

template <typename T>
struct MulGradFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a * b; }
};
template <typename T>
struct MulGradFunctor<Complex<T>> {
inline HOSTDEVICE Complex<T> operator()(const Complex<T> a,
const Complex<T> b) const {
Complex<T> b_conj(b.real, -b.imag);
return a * b_conj;
}
};

template <typename InT, typename OutT>
struct MulGradXYFunctor {
inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT a, const InT b,
const InT c) {
phi::Array<OutT, 2> outs;
// dx = dout * y
outs[0] = a * b;
// dy = dout * x
outs[1] = a * c;
return outs;
}
};

template <typename InT, typename OutT>
struct MulGradXYFunctor<Complex<InT>, Complex<OutT>> {
inline HOSTDEVICE phi::Array<Complex<OutT>, 2> operator()(
const Complex<InT> a, const Complex<InT> b, const Complex<InT> c) {
phi::Array<Complex<OutT>, 2> outs;
// dx = dout * y
Complex<InT> b_conj(b.real, -b.imag);
outs[0] = a * b_conj;
// dy = dout * x
Complex<InT> c_conj(c.real, -c.imag);
outs[1] = a * c_conj;
return outs;
}
};

// Ternary compare
template <typename T>
struct MaxGradXFunctor {
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49 changes: 0 additions & 49 deletions paddle/fluid/operators/elementwise/elementwise_mul_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -173,55 +173,6 @@ REGISTER_OP_CPU_KERNEL(
paddle::platform::complex<float>>,
ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<double>>);
REGISTER_OP_CPU_KERNEL(
elementwise_mul_grad,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, double>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, int>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, bool>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::bfloat16>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<float>>,
ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<double>>);
REGISTER_OP_CPU_KERNEL(
elementwise_mul_grad_grad,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
float>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
double>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
int>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
int64_t>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
bool>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::bfloat16>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<float>>,
ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<double>>);
REGISTER_OP_CPU_KERNEL(
elementwise_mul_triple_grad,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
float>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
double>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
int>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
int64_t>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
bool>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::bfloat16>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<float>>,
ops::ElementwiseMulTripleGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::complex<double>>);

REGISTER_OP_VERSION(elementwise_mul)
.AddCheckpoint(
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68 changes: 0 additions & 68 deletions paddle/fluid/operators/elementwise/elementwise_mul_op.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -63,33 +63,6 @@ class ElementwiseMulKernel<platform::CUDADeviceContext, T>
}
};

template <typename DeviceContext, typename T>
typename std::enable_if<
std::is_same<DeviceContext, platform::CUDADeviceContext>::value>::type
ElementwiseMulGrad(const framework::ExecutionContext& ctx,
const framework::Tensor* x, const framework::Tensor* y,
const framework::Tensor* out, const framework::Tensor* dout,
framework::Tensor* dx, framework::Tensor* dy) {
int axis = ctx.Attr<int>("axis");
const auto& dev_ctx =
ctx.template device_context<platform::CUDADeviceContext>();
const auto place = ctx.GetPlace();

if (dx != nullptr && dy != nullptr) {
std::vector<const framework::Tensor*> ins = {dout, y, x};
GetGradXAndYOut<ElementwiseType::kTernary, T>(
dev_ctx, place, axis, ins, dout, dx, dy, MulGradXYFunctor<T, T>());
} else if (dx != nullptr && dy == nullptr) {
std::vector<const framework::Tensor*> ins = {dout, y};
GetGradXOrYOut<ElementwiseType::kBinary, T>(dev_ctx, place, axis, ins, dout,
dx, MulGradFunctor<T>());
} else if (dx == nullptr && dy != nullptr) {
std::vector<const framework::Tensor*> ins = {dout, x};
GetGradXOrYOut<ElementwiseType::kBinary, T>(dev_ctx, place, axis, ins, dout,
dy, MulGradFunctor<T>());
}
}

} // namespace operators
} // namespace paddle

Expand All @@ -103,44 +76,3 @@ REGISTER_OP_CUDA_KERNEL(
ops::ElementwiseMulKernel<plat::CUDADeviceContext, plat::bfloat16>,
ops::ElementwiseMulKernel<plat::CUDADeviceContext, plat::complex<float>>,
ops::ElementwiseMulKernel<plat::CUDADeviceContext, plat::complex<double>>);
REGISTER_OP_CUDA_KERNEL(
elementwise_mul_grad,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, float>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, double>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, int>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, int64_t>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, bool>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, plat::float16>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, plat::bfloat16>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext,
plat::complex<float>>,
ops::ElementwiseMulGradKernel<plat::CUDADeviceContext,
plat::complex<double>>);
REGISTER_OP_CUDA_KERNEL(
elementwise_mul_grad_grad,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, float>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, double>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, int>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, int64_t>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, bool>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, plat::float16>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext,
plat::bfloat16>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext,
plat::complex<float>>,
ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext,
plat::complex<double>>);
REGISTER_OP_CUDA_KERNEL(
elementwise_mul_triple_grad,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext, float>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext, double>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext, int>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext, int64_t>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext, bool>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext, plat::float16>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext,
plat::bfloat16>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext,
plat::complex<float>>,
ops::ElementwiseMulTripleGradKernel<plat::CUDADeviceContext,
plat::complex<double>>);
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