From 1ab9eb0474102e8fe9269388abb0907ee7765c46 Mon Sep 17 00:00:00 2001
From: Antoni Olivier <olivier.antoni@cea.fr>
Date: Thu, 6 Jun 2024 10:22:44 +0200
Subject: [PATCH] Add backward functions for ReLU, Sigmoid and Tanh
---
.../aidge/backend/cpu/operator/ReLUImpl.hpp | 2 +-
.../operator/ReLUImpl_backward_kernels.hpp | 19 +++++++++----------
.../backend/cpu/operator/SigmoidImpl.hpp | 2 +-
.../operator/SigmoidImpl_backward_kernels.hpp | 15 +++++++--------
.../aidge/backend/cpu/operator/TanhImpl.hpp | 2 +-
.../operator/TanhImpl_backward_kernels.hpp | 15 +++++++--------
src/operator/ReLUImpl.cpp | 11 +++++------
src/operator/SigmoidImpl.cpp | 12 +++++-------
src/operator/TanhImpl.cpp | 8 +++-----
9 files changed, 39 insertions(+), 47 deletions(-)
diff --git a/include/aidge/backend/cpu/operator/ReLUImpl.hpp b/include/aidge/backend/cpu/operator/ReLUImpl.hpp
index f8abfcf2..e2ebf446 100644
--- a/include/aidge/backend/cpu/operator/ReLUImpl.hpp
+++ b/include/aidge/backend/cpu/operator/ReLUImpl.hpp
@@ -30,7 +30,7 @@ class ReLUImplForward_cpu
: public Registrable<ReLUImplForward_cpu, std::tuple<DataType, DataType>, void(const std::size_t, const void*, void*)> {
};
class ReLUImplBackward_cpu
- : public Registrable<ReLUImplBackward_cpu, std::tuple<DataType, DataType, DataType, DataType>, void(const std::size_t, const void*, const void*, const void*, void*)> {
+ : public Registrable<ReLUImplBackward_cpu, std::tuple<DataType, DataType, DataType>, void(const std::size_t, const void*, const void*, void*)> {
};
class ReLUImpl_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/ReLUImpl_backward_kernels.hpp b/include/aidge/backend/cpu/operator/ReLUImpl_backward_kernels.hpp
index e67a4588..1bd932e4 100644
--- a/include/aidge/backend/cpu/operator/ReLUImpl_backward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ReLUImpl_backward_kernels.hpp
@@ -18,12 +18,11 @@
#include "aidge/utils/Registrar.hpp"
namespace Aidge {
-template <class I, class O, class GI, class GO>
+template <class I, class GI, class GO>
void ReLUImpl_cpu_backward_kernel(const std::size_t inputLenght,
- const void* input_, const void* output_, const void* grad_output_,
- void* grad_input_) {
+ const void* input_, const void* grad_output_,
+ void* grad_input_) {
const I* input = static_cast<const I*>(input_);
- //const O* output = static_cast<const O*>(output_);
const GO* grad_output = static_cast<const GO*>(grad_output_);
GI* grad_input = static_cast<GI*>(grad_input_);
for (std::size_t i = 0; i < inputLenght; ++i) {
@@ -33,14 +32,14 @@ void ReLUImpl_cpu_backward_kernel(const std::size_t inputLenght,
namespace {
static Registrar<ReLUImplBackward_cpu> registrarReLUImplBackward_cpu_Float32(
- {DataType::Float32, DataType::Float32, DataType::Float32, DataType::Float32},
- Aidge::ReLUImpl_cpu_backward_kernel<float, float, float, float>);
+ {DataType::Float32, DataType::Float32, DataType::Float32},
+ Aidge::ReLUImpl_cpu_backward_kernel<float, float, float>);
static Registrar<ReLUImplBackward_cpu> registrarReLUImplBackward_cpu_Int32(
- {DataType::Int32, DataType::Int32, DataType::Int32, DataType::Int32},
- Aidge::ReLUImpl_cpu_backward_kernel<int, int, int, int>);
+ {DataType::Int32, DataType::Int32, DataType::Int32},
+ Aidge::ReLUImpl_cpu_backward_kernel<int, int, int>);
static Registrar<ReLUImplBackward_cpu> registrarReLUImplBackward_cpu_Float64(
- {DataType::Float64, DataType::Float64, DataType::Float64, DataType::Float64},
- Aidge::ReLUImpl_cpu_backward_kernel<double, double, double, double>);
+ {DataType::Float64, DataType::Float64, DataType::Float64},
+ Aidge::ReLUImpl_cpu_backward_kernel<double, double, double>);
} // namespace
} // namespace Aidge
diff --git a/include/aidge/backend/cpu/operator/SigmoidImpl.hpp b/include/aidge/backend/cpu/operator/SigmoidImpl.hpp
index ed9ffe13..34340e61 100644
--- a/include/aidge/backend/cpu/operator/SigmoidImpl.hpp
+++ b/include/aidge/backend/cpu/operator/SigmoidImpl.hpp
@@ -28,7 +28,7 @@ class SigmoidImplForward_cpu
: public Registrable<SigmoidImplForward_cpu, std::tuple<DataType, DataType>, void(const std::size_t, const void*, void*)> {
};
class SigmoidImplBackward_cpu
- : public Registrable<SigmoidImplBackward_cpu, std::tuple<DataType, DataType, DataType, DataType>, void(const std::size_t, const void*, const void*, const void*, void*)> {
+ : public Registrable<SigmoidImplBackward_cpu, std::tuple<DataType, DataType, DataType>, void(const std::size_t, const void*, const void*, void*)> {
};
class SigmoidImpl_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/SigmoidImpl_backward_kernels.hpp b/include/aidge/backend/cpu/operator/SigmoidImpl_backward_kernels.hpp
index 931a2e4d..4ceb3bd7 100644
--- a/include/aidge/backend/cpu/operator/SigmoidImpl_backward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/SigmoidImpl_backward_kernels.hpp
@@ -18,11 +18,10 @@
#include "aidge/utils/Registrar.hpp"
namespace Aidge {
-template <class I, class O, class GI, class GO>
+template <class O, class GI, class GO>
void SigmoidImpl_cpu_backward_kernel(const std::size_t inputLenght,
- const void* input_, const void* output_, const void* grad_output_,
- void* grad_input_) {
- //const I* input = static_cast<const I*>(input_);
+ const void* output_, const void* grad_output_,
+ void* grad_input_) {
const O* output = static_cast<const O*>(output_);
const GO* grad_output = static_cast<const GO*>(grad_output_);
GI* grad_input = static_cast<GI*>(grad_input_);
@@ -33,11 +32,11 @@ void SigmoidImpl_cpu_backward_kernel(const std::size_t inputLenght,
namespace {
static Registrar<SigmoidImplBackward_cpu> registrarSigmoidImplBackward_cpu_Float32(
- {DataType::Float32, DataType::Float32, DataType::Float32, DataType::Float32},
- Aidge::SigmoidImpl_cpu_backward_kernel<float, float, float, float>);
+ {DataType::Float32, DataType::Float32, DataType::Float32},
+ Aidge::SigmoidImpl_cpu_backward_kernel<float, float, float>);
static Registrar<SigmoidImplBackward_cpu> registrarSigmoidImplBackward_cpu_Float64(
- {DataType::Float64, DataType::Float64, DataType::Float64, DataType::Float64},
- Aidge::SigmoidImpl_cpu_backward_kernel<double, double, double, double>);
+ {DataType::Float64, DataType::Float64, DataType::Float64},
+ Aidge::SigmoidImpl_cpu_backward_kernel<double, double, double>);
} // namespace
} // namespace Aidge
diff --git a/include/aidge/backend/cpu/operator/TanhImpl.hpp b/include/aidge/backend/cpu/operator/TanhImpl.hpp
index a62cd050..0bf851e7 100644
--- a/include/aidge/backend/cpu/operator/TanhImpl.hpp
+++ b/include/aidge/backend/cpu/operator/TanhImpl.hpp
@@ -28,7 +28,7 @@ class TanhImplForward_cpu
: public Registrable<TanhImplForward_cpu, std::tuple<DataType, DataType>, void(const std::size_t, const void*, void*)> {
};
class TanhImplBackward_cpu
- : public Registrable<TanhImplBackward_cpu, std::tuple<DataType, DataType, DataType, DataType>, void(const std::size_t, const void*, const void*, const void*, void*)> {
+ : public Registrable<TanhImplBackward_cpu, std::tuple<DataType, DataType, DataType>, void(const std::size_t, const void*, const void*, void*)> {
};
class TanhImpl_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/TanhImpl_backward_kernels.hpp b/include/aidge/backend/cpu/operator/TanhImpl_backward_kernels.hpp
index 3f49e4c4..3a13c2ca 100644
--- a/include/aidge/backend/cpu/operator/TanhImpl_backward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/TanhImpl_backward_kernels.hpp
@@ -18,11 +18,10 @@
#include "aidge/utils/Registrar.hpp"
namespace Aidge {
-template <class I, class O, class GI, class GO>
+template <class O, class GI, class GO>
void TanhImpl_cpu_backward_kernel(const std::size_t inputLenght,
- const void* input_, const void* output_, const void* grad_output_,
- void* grad_input_) {
- //const I* input = static_cast<const I*>(input_);
+ const void* output_, const void* grad_output_,
+ void* grad_input_) {
const O* output = static_cast<const O*>(output_);
const GO* grad_output = static_cast<const GO*>(grad_output_);
GI* grad_input = static_cast<GI*>(grad_input_);
@@ -33,11 +32,11 @@ void TanhImpl_cpu_backward_kernel(const std::size_t inputLenght,
namespace {
static Registrar<TanhImplBackward_cpu> registrarTanhImplBackward_cpu_Float32(
- {DataType::Float32, DataType::Float32, DataType::Float32, DataType::Float32},
- Aidge::TanhImpl_cpu_backward_kernel<float, float, float, float>);
+ {DataType::Float32, DataType::Float32, DataType::Float32},
+ Aidge::TanhImpl_cpu_backward_kernel<float, float, float>);
static Registrar<TanhImplBackward_cpu> registrarTanhImplBackward_cpu_Float64(
- {DataType::Float64, DataType::Float64, DataType::Float64, DataType::Float64},
- Aidge::TanhImpl_cpu_backward_kernel<double, double, double, double>);
+ {DataType::Float64, DataType::Float64, DataType::Float64},
+ Aidge::TanhImpl_cpu_backward_kernel<double, double, double>);
} // namespace
} // namespace Aidge
diff --git a/src/operator/ReLUImpl.cpp b/src/operator/ReLUImpl.cpp
index 8de2190e..4a0fb9f5 100644
--- a/src/operator/ReLUImpl.cpp
+++ b/src/operator/ReLUImpl.cpp
@@ -46,20 +46,19 @@ void Aidge::ReLUImpl_cpu::forward() {
void Aidge::ReLUImpl_cpu::backward() {
const ReLU_Op& op_ = dynamic_cast<const ReLU_Op&>(mOp);
- std::shared_ptr<Tensor> in0 = op_.getInput(0);
+ std::shared_ptr<Tensor> in0 = op_.getInput(0);
std::shared_ptr<Tensor> out0 = op_.getOutput(0);
std::shared_ptr<Tensor> gra_int0 = op_.getInput(0)->grad();
- std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
+ std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
AIDGE_ASSERT(out0, "missing output #0 for current {} operator", op_.type());
// Find the correct kernel type
auto kernelFunc = Registrar<ReLUImplBackward_cpu>::create({
- in0->dataType(),
- out0->dataType(),
+ in0->dataType(),
gra_int0->dataType(),
- gra_out0->dataType()
+ gra_out0->dataType()
});
// Call kernel
- kernelFunc(gra_int0->size(), getCPUPtr(in0), getCPUPtr(out0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
+ kernelFunc(gra_int0->size(), getCPUPtr(in0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
}
diff --git a/src/operator/SigmoidImpl.cpp b/src/operator/SigmoidImpl.cpp
index fe92ef43..ad69935c 100644
--- a/src/operator/SigmoidImpl.cpp
+++ b/src/operator/SigmoidImpl.cpp
@@ -47,20 +47,18 @@ void Aidge::SigmoidImpl_cpu::forward() {
void Aidge::SigmoidImpl_cpu::backward() {
const Sigmoid_Op& op_ = dynamic_cast<const Sigmoid_Op&>(mOp);
- std::shared_ptr<Tensor> in0 = op_.getInput(0);
std::shared_ptr<Tensor> out0 = op_.getOutput(0);
- std::shared_ptr<Tensor> gra_int0 = op_.getInput(0)->grad();
- std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
+ std::shared_ptr<Tensor> gra_int0 = op_.getInput(0)->grad();
+ std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
AIDGE_ASSERT(out0, "missing output #0 for current {} operator", op_.type());
// Find the correct kernel type
auto kernelFunc = Registrar<SigmoidImplBackward_cpu>::create({
- in0->dataType(),
out0->dataType(),
- gra_int0->dataType(),
+ gra_int0->dataType(),
gra_out0->dataType()
});
// Call kernel
- kernelFunc(gra_int0->size(), getCPUPtr(in0), getCPUPtr(out0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
-}
\ No newline at end of file
+ kernelFunc(gra_int0->size(), getCPUPtr(out0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
+}
diff --git a/src/operator/TanhImpl.cpp b/src/operator/TanhImpl.cpp
index 8b5988e9..a2469ed9 100644
--- a/src/operator/TanhImpl.cpp
+++ b/src/operator/TanhImpl.cpp
@@ -47,21 +47,19 @@ void Aidge::TanhImpl_cpu::forward() {
void Aidge::TanhImpl_cpu::backward() {
const Tanh_Op& op_ = dynamic_cast<const Tanh_Op&>(mOp);
- std::shared_ptr<Tensor> in0 = op_.getInput(0);
std::shared_ptr<Tensor> out0 = op_.getOutput(0);
std::shared_ptr<Tensor> gra_int0 = op_.getInput(0)->grad();
- std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
+ std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
AIDGE_ASSERT(out0, "missing output #0 for current {} operator", op_.type());
// Find the correct kernel type
auto kernelFunc = Registrar<TanhImplBackward_cpu>::create({
- in0->dataType(),
out0->dataType(),
- gra_int0->dataType(),
+ gra_int0->dataType(),
gra_out0->dataType()
});
// Call kernel
- kernelFunc(gra_int0->size(), getCPUPtr(in0), getCPUPtr(out0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
+ kernelFunc(gra_int0->size(), getCPUPtr(out0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
}
--
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