diff --git a/include/aidge/backend/cpu/operator/ClipImpl.hpp b/include/aidge/backend/cpu/operator/ClipImpl.hpp
index a46230d0a2a648beece00d546fd4038c5f1d83e7..c83836d5aa1d6aae27e3fdce1bbb9561b70ec31e 100644
--- a/include/aidge/backend/cpu/operator/ClipImpl.hpp
+++ b/include/aidge/backend/cpu/operator/ClipImpl.hpp
@@ -16,6 +16,7 @@
#include <memory>
#include <tuple> // std::tuple
#include <vector>
+#include <algorithm>
#include "aidge/backend/cpu/operator/OperatorImpl.hpp"
#include "aidge/operator/Clip.hpp"
@@ -27,13 +28,13 @@
namespace Aidge {
// Operator implementation entry point for the backend
using ClipImpl_cpu = OperatorImpl_cpu<Clip_Op,
- void(const void*, //Forward Types
- const void*,
+ void(float, //Forward Types
+ float,
const void*,
const std::size_t,
void*),
- void(const void*,//Backward Types
- const void*,
+ void(float,//Backward Types
+ float,
const std::size_t,
const void*,
const void*,
diff --git a/include/aidge/backend/cpu/operator/ClipImpl_kernels.hpp b/include/aidge/backend/cpu/operator/ClipImpl_kernels.hpp
index 7c80aed59d6ff11f7f29b8e2a4abaaab997ecdd1..6646aa1c3772962afd320452a51257c319367808 100644
--- a/include/aidge/backend/cpu/operator/ClipImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ClipImpl_kernels.hpp
@@ -19,40 +19,35 @@
namespace Aidge {
template <class I, class O>
void ClipImpl_cpu_forward_kernel(
- const void* min_,
- const void* max_,
+ float min_,
+ float max_,
const void* input_,
const std::size_t length,
void* output_)
{
- const I* min = static_cast<const I*>(min_);
- const I* max = static_cast<const I*>(max_);
-
const I* input = static_cast<const I*>(input_);
O* output = static_cast<O*>(output_);
for (std::size_t i = 0; i < length; ++i) {
- output[i] = std::max(min[0], std::min(input[i], max[0]));
+ output[i] = std::max(min_, std::min(static_cast<float>(input[i]), max_));
}
}
template <class I, class GI, class GO>
void ClipImpl_cpu_backward_kernel(
- const void* min_,
- const void* max_,
+ float min_,
+ float max_,
const std::size_t length,
const void* input_,
const void* grad_output_,
void* grad_input_)
{
- const I* min = static_cast<const I*>(min_);
- const I* max = static_cast<const I*>(max_);
const I* input = static_cast<const I*>(input_);
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 < length; ++i) {
- grad_input[i] = ((input[i] > min[0]) && (input[i] < max[0])) ? grad_output[i] : 0;
+ grad_input[i] = ((input[i] > min_) && (input[i] < max_)) ? grad_output[i] : 0;
}
}
diff --git a/src/operator/ClipImpl.cpp b/src/operator/ClipImpl.cpp
index 3949ae9568c4a3a4d38bf573eecf420f95a8c5e7..931d25426a8f6e08363bfc08d23f1714e934634c 100644
--- a/src/operator/ClipImpl.cpp
+++ b/src/operator/ClipImpl.cpp
@@ -26,33 +26,17 @@ void Aidge::ClipImpl_cpu::forward() {
const Clip_Op& op_ = dynamic_cast<const Clip_Op&>(mOp);
std::shared_ptr<Tensor> in0 = op_.getInput(0);
- std::shared_ptr<Tensor> in1 = op_.getInput(1);
- std::shared_ptr<Tensor> in2 = op_.getInput(2);
std::shared_ptr<Tensor> out0 = op_.getOutput(0);
AIDGE_ASSERT(in0, "missing input #0");
/*AIDGE_ASSERT(in1, "missing input #1 -> Min value empty shape Tensor");
AIDGE_ASSERT(in2, "missing input #2 -> Max value empty shape Tensor");*/
- void* min;
- void* max;
-
- if (!in1 || !in2)
- {
- min = &op_.min();
- max = &op_.max();
- }
- else
- {
- min = getCPUPtr(mOp.getRawInput(1));
- max = getCPUPtr(mOp.getRawInput(2));
- }
// Find the correct kernel type
const auto impl = Registrar<ClipImpl_cpu>::create(getBestMatch(getRequiredSpec()));
-
// Call kernel
impl.forward(
- min,
- max,
+ op_.min(),
+ op_.max(),
getCPUPtr(mOp.getRawInput(0)),
in0->size(),
getCPUPtr(mOp.getRawOutput(0))
@@ -64,8 +48,6 @@ void Aidge::ClipImpl_cpu::backward() {
const Clip_Op& op_ = dynamic_cast<const Clip_Op&>(mOp);
std::shared_ptr<Tensor> in0 = op_.getInput(0);
- std::shared_ptr<Tensor> in1min = op_.getInput(1);
- std::shared_ptr<Tensor> in2max = op_.getInput(2);
std::shared_ptr<Tensor> out0 = op_.getOutput(0);
std::shared_ptr<Tensor> gra_in0 = op_.getInput(0)->grad();
std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
@@ -73,22 +55,10 @@ void Aidge::ClipImpl_cpu::backward() {
// Find the correct kernel type
const auto impl = Registrar<ClipImpl_cpu>::create(getBestMatch(getRequiredSpec()));
- void* min;
- void* max;
- if (!in1min || !in2max)
- {
- min = &op_.min();
- max = &op_.max();
- }
- else
- {
- min = getCPUPtr(mOp.getRawInput(1));
- max = getCPUPtr(mOp.getRawInput(2));
- }
// Call kernel
impl.backward(
- min,
- max,
+ op_.min(),
+ op_.max(),
gra_in0->size(),
getCPUPtr(in0),
getCPUPtr(gra_out0),
diff --git a/unit_tests/operator/Test_ClipImpl.cpp b/unit_tests/operator/Test_ClipImpl.cpp
index b7f286f1c6e0703509c9117afa06705706f7c3c2..a2da6d71a989f026439e3e60f66d272cc6f7e864 100644
--- a/unit_tests/operator/Test_ClipImpl.cpp
+++ b/unit_tests/operator/Test_ClipImpl.cpp
@@ -108,13 +108,14 @@ TEST_CASE("[cpu/operator] Clip", "[Clip][CPU]")
op->associateInput(2, Tmax);
op->setDataType(DataType::Float32);
op->setBackend("cpu");
- op->forwardDims();
+ op->forwardDims(true);
start = std::chrono::system_clock::now();
myClip->forward();
end = std::chrono::system_clock::now();
duration += std::chrono::duration_cast<std::chrono::microseconds>(end - start);
+
REQUIRE(approxEq<float>(*(op->getOutput(0)), *Tres));
}
std::cout << "multiplications over time spent: " << totalComputation/duration.count() << std::endl;
@@ -161,7 +162,7 @@ TEST_CASE("[cpu/operator] Clip", "[Clip][CPU]")
op->associateInput(0, TInput);
op->setDataType(DataType::Float32);
op->setBackend("cpu");
- op->forwardDims();
+ op->forwardDims(true);
start = std::chrono::system_clock::now();
myCl->forward();
end = std::chrono::system_clock::now();
@@ -231,7 +232,7 @@ TEST_CASE("[cpu/operator] Clip", "[Clip][CPU]")
op->associateInput(2, Tmax);
op->setDataType(DataType::Float32);
op->setBackend("cpu");
- op->forwardDims();
+ op->forwardDims(true);
myClip->forward();
op->getOutput(0)->setGrad(TGrad);