From 5506a972dd6e25e623dfc8a0834e6c38fe5edec5 Mon Sep 17 00:00:00 2001
From: Houssem Rouis <houssemeddine.rouis92@gmail.com>
Date: Fri, 27 Oct 2023 12:00:05 +0200
Subject: [PATCH] add support for operations of tensor with different dims
---
.../cpu/operator/DivImpl_forward_kernels.hpp | 7 ++++
.../cpu/operator/PowImpl_forward_kernels.hpp | 7 ++++
src/operator/DivImpl.cpp | 7 ++--
src/operator/PowImpl.cpp | 9 +++--
unit_tests/operator/Test_DivImpl.cpp | 38 ++++++++++++++++++
unit_tests/operator/Test_PowImpl.cpp | 39 +++++++++++++++++++
6 files changed, 100 insertions(+), 7 deletions(-)
diff --git a/include/aidge/backend/cpu/operator/DivImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/DivImpl_forward_kernels.hpp
index 01c18a66..e2ead9ca 100644
--- a/include/aidge/backend/cpu/operator/DivImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/DivImpl_forward_kernels.hpp
@@ -39,6 +39,13 @@ void DivImpl_cpu_forward_kernel(std::size_t input1Length,
output[i] = input_1[i] / input_2[0];
}
}
+ else // input_2 is 1d and of size the number of channels of input_1
+ {
+ for (std::size_t i = 0; i < input1Length; ++i) {
+ std::size_t channelIdx = i % input2Length;
+ output[i] = input_1[i] / input_2[channelIdx];
+ }
+ }
}
namespace {
diff --git a/include/aidge/backend/cpu/operator/PowImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/PowImpl_forward_kernels.hpp
index 0b9e2648..c9c5db7e 100644
--- a/include/aidge/backend/cpu/operator/PowImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/PowImpl_forward_kernels.hpp
@@ -41,6 +41,13 @@ void PowImpl_cpu_forward_kernel(std::size_t input1Length,
output[i] = std::pow(input_1[i], input_2[0]);
}
}
+ else // input_2 is 1d and of size the number of channels of input_1
+ {
+ for (std::size_t i = 0; i < input1Length; ++i) {
+ std::size_t channelIdx = i % input2Length;
+ output[i] = std::pow(input_1[i], input_2[channelIdx]);
+ }
+ }
}
namespace {
diff --git a/src/operator/DivImpl.cpp b/src/operator/DivImpl.cpp
index f8b7f84f..f7cbc7d2 100644
--- a/src/operator/DivImpl.cpp
+++ b/src/operator/DivImpl.cpp
@@ -30,10 +30,11 @@ void Aidge::DivImpl_cpu::forward() {
assert(mOp.getInput(0) && "missing input #0");
assert(mOp.getInput(1) && "missing input #1");
- // TODO add support for when input1 is a 1d tensor of size the channels of input0
assert(((mOp.getInput(1)->size() == 1) ||
- (mOp.getInput(1)->size() == mOp.getInput(0)->size())) &&
- "input #1 must either be a tensor of size 1 or the same size of input #0");
+ (mOp.getInput(1)->size() == mOp.getInput(0)->size()) ||
+ (mOp.getInput(1)->nbDims() == 1 && mOp.getInput(1)->size() == mOp.getInput(0)->dims()[mOp.getInput(0)->nbDims()-1])
+ ) &&
+ "input #1 must either be a tensor of size 1, the number of channels of input # or the same size of input #0");
// Find the correct kernel type
auto kernelFunc = Registrar<DivImplForward_cpu>::create({
diff --git a/src/operator/PowImpl.cpp b/src/operator/PowImpl.cpp
index d359d40d..52a4f469 100644
--- a/src/operator/PowImpl.cpp
+++ b/src/operator/PowImpl.cpp
@@ -29,11 +29,12 @@ Aidge::NbElts_t Aidge::PowImpl_cpu::getNbRequiredProtected(const Aidge::IOIndex_
void Aidge::PowImpl_cpu::forward() {
assert(mOp.getInput(0) && "missing input #0");
assert(mOp.getInput(1) && "missing input #1");
-
- // TODO add support for when input1 is a 1d tensor of size the channels of input0
+
assert(((mOp.getInput(1)->size() == 1) ||
- (mOp.getInput(1)->size() == mOp.getInput(0)->size())) &&
- "input #1 must either be a tensor of size 1 or the same size of input #0");
+ (mOp.getInput(1)->size() == mOp.getInput(0)->size()) ||
+ (mOp.getInput(1)->nbDims() == 1 && mOp.getInput(1)->size() == mOp.getInput(0)->dims()[mOp.getInput(0)->nbDims()-1])
+ ) &&
+ "input #1 must either be a tensor of size 1, the number of channels of input # or the same size of input #0");
// Find the correct kernel type
auto kernelFunc = Registrar<PowImplForward_cpu>::create({
diff --git a/unit_tests/operator/Test_DivImpl.cpp b/unit_tests/operator/Test_DivImpl.cpp
index e3955c55..a6d780e2 100644
--- a/unit_tests/operator/Test_DivImpl.cpp
+++ b/unit_tests/operator/Test_DivImpl.cpp
@@ -88,6 +88,44 @@ TEST_CASE("[cpu/operator] Div(forward)") {
}
+ SECTION("3D Tensor by 1D Tensor") {
+ std::shared_ptr<Tensor> input_1 = std::make_shared<Tensor>(Array3D<float,2,2,3> {
+ {
+ {{0.24180168, 0.44319558, 0.06437260},
+ {0.21270001, 0.34570599, 0.44151264}},
+ {{0.62294692, 0.98043168, 0.18628585},
+ {0.33591706, 0.03432965, 0.32130069}}
+ }
+ });
+ std::shared_ptr<Tensor> input_2 = std::make_shared<Tensor>(Array1D<float,3>{
+ {0.63475525, 0.58620811, 0.69340748}
+ });
+ std::shared_ptr<Tensor> expectedOutput = std::make_shared<Tensor>(Array3D<float,2,2,3> {
+ {
+ {{0.38093686, 0.75603795, 0.09283517},
+ {0.33508980, 0.58973253, 0.63672900}},
+
+ {{0.98139703, 1.67249763, 0.26865280},
+ {0.52920723, 0.05856223, 0.46336490}}
+ }
+ });
+
+ std::shared_ptr<Node> myDiv = Div();
+ myDiv->getOperator()->setDatatype(DataType::Float32);
+ myDiv->getOperator()->setBackend("cpu");
+ myDiv->getOperator()->associateInput(0, input_1);
+ myDiv->getOperator()->associateInput(1, input_2);
+ myDiv->getOperator()->computeOutputDims();
+ myDiv->forward();
+
+ float* resPtr = static_cast<float*>(myDiv->getOperator()->getOutput(0)->getImpl()->rawPtr());
+ float* expectedPtr = static_cast<float*>(expectedOutput->getImpl()->rawPtr());
+ for (std::size_t i = 0; i< 4; ++i) {
+ REQUIRE(std::abs(resPtr[i]-expectedPtr[i]) < 0.00001);
+ }
+
+ }
+
SECTION("4D Tensor") {
std::shared_ptr<Tensor> input_1 = std::make_shared<Tensor>(Array4D<float,2,3,3,3> {
{
diff --git a/unit_tests/operator/Test_PowImpl.cpp b/unit_tests/operator/Test_PowImpl.cpp
index 7ee31ddb..21ea1a52 100644
--- a/unit_tests/operator/Test_PowImpl.cpp
+++ b/unit_tests/operator/Test_PowImpl.cpp
@@ -52,6 +52,45 @@ TEST_CASE("[cpu/operator] Pow(forward)") {
}
+ SECTION("3D Tensor by 1D Tensor") {
+ std::shared_ptr<Tensor> input_1 = std::make_shared<Tensor>(Array3D<float,2,2,3> {
+ {
+ {{0.87519985, 0.10536593, 0.20268351},
+ {0.75532353, 0.95977652, 0.03897029}},
+
+ {{0.67554104, 0.35499334, 0.27741563},
+ {0.94270861, 0.48397779, 0.35532343}}
+ }
+ });
+ std::shared_ptr<Tensor> input_2 = std::make_shared<Tensor>(Array1D<float,3>{
+ {0.39333701, 0.08719915, 0.16713941}
+ });
+ std::shared_ptr<Tensor> expectedOutput = std::make_shared<Tensor>(Array3D<float,2,2,3> {
+ {
+ {{0.94891787, 0.82182676, 0.76584703},
+ {0.89549923, 0.99642646, 0.58137459}},
+
+ {{0.85702944, 0.91364944, 0.80709606},
+ {0.97706109, 0.93867886, 0.84118503}}
+ }
+ });
+
+ std::shared_ptr<Node> myPow = Pow();
+ myPow->getOperator()->setDatatype(DataType::Float32);
+ myPow->getOperator()->setBackend("cpu");
+ myPow->getOperator()->associateInput(0, input_1);
+ myPow->getOperator()->associateInput(1, input_2);
+ myPow->getOperator()->computeOutputDims();
+ myPow->forward();
+
+ float* resPtr = static_cast<float*>(myPow->getOperator()->getOutput(0)->getImpl()->rawPtr());
+ float* expectedPtr = static_cast<float*>(expectedOutput->getImpl()->rawPtr());
+ for (std::size_t i = 0; i< 4; ++i) {
+ REQUIRE(std::abs(resPtr[i]-expectedPtr[i]) < 0.00001);
+ }
+
+ }
+
SECTION("2D Tensors") {
std::shared_ptr<Tensor> input_1 = std::make_shared<Tensor>(Array2D<float,2,2> {
{
--
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