diff --git a/include/aidge/backend/cpu/operator/FCImpl_kernels.hpp b/include/aidge/backend/cpu/operator/FCImpl_kernels.hpp
index 7bf2ea9f1613372640611f6e436278350c9e299d..8944099ddbc7ccfaedfabec9d7295fe3ddcadbb0 100644
--- a/include/aidge/backend/cpu/operator/FCImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/FCImpl_kernels.hpp
@@ -136,7 +136,6 @@ void FCImpl_cpu_backward_kernel(const DimSize_t batchSize,
B* biasesGrad = static_cast<B*>(biasesGrad_);
- Log::info("\t\t Call to FCImpl_cpu_backward_kernel - Doing Bias grad");
// bias grad
if (biasesGrad == nullptr) { // no bias
// Do nothing
@@ -151,7 +150,6 @@ void FCImpl_cpu_backward_kernel(const DimSize_t batchSize,
}
}
- Log::info("\t\t Call to FCImpl_cpu_backward_kernel - Doing Weight grad");
// weight grad
for (std::size_t o = 0; o < outputFeatureSize; ++o) {
for (std::size_t c = 0; c < inputFeatureSize; ++c) {
@@ -163,7 +161,6 @@ void FCImpl_cpu_backward_kernel(const DimSize_t batchSize,
}
}
- Log::info("\t\t Call to FCImpl_cpu_backward_kernel - Doing Input grad");
// input grad
for (std::size_t b = 0; b < batchSize; ++b) {
for (std::size_t c = 0; c < inputFeatureSize; ++c) {
diff --git a/include/aidge/backend/cpu/operator/MulImpl_kernels.hpp b/include/aidge/backend/cpu/operator/MulImpl_kernels.hpp
index 36acb9199c51e900287ca9b262322aa86287d838..1c71ca6399853aaec74acc070fb2d75b4d5d8aeb 100644
--- a/include/aidge/backend/cpu/operator/MulImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/MulImpl_kernels.hpp
@@ -194,6 +194,7 @@ void MulImpl_cpu_backward_kernel(const std::size_t input0Length,
auto idx0 = getFlattenedIndex(broadcastedDims0, idxInput0);
auto idx1 = getFlattenedIndex(broadcastedDims1, idxInput1);
+ Log::info("Multiplication by {}", input1[idx1]);
grad_input_0[idx0] += static_cast<I1>(grad_output[i] * input1[idx1]);
grad_input_1[idx1] += static_cast<I2>(grad_output[i] * input0[idx0]);
}
diff --git a/src/operator/AddImpl.cpp b/src/operator/AddImpl.cpp
index cff6128741db657136aca1006c0f273ce64aa87a..6800d7e0bcdf8e99060db953d855a207262b2e38 100644
--- a/src/operator/AddImpl.cpp
+++ b/src/operator/AddImpl.cpp
@@ -77,4 +77,10 @@ void Aidge::AddImpl_cpu::backward() {
getCPUPtr(in0grad),
getCPUPtr(in1grad));
+ Log::info("AddImpl_cpu::backward() : Gradient of output 0");
+ out0grad->print();
+ Log::info("AddImpl_cpu::backward() : Gradient of input 0");
+ in0grad->print();
+ Log::info("AddImpl_cpu::backward() : Gradient of input 1");
+ in1grad->print();
}
diff --git a/src/operator/FCImpl.cpp b/src/operator/FCImpl.cpp
index 53502be1525d19ac105cd2afa046b68c75835a02..cef4dae2b46907158036ebd31848d169f5e74e85 100644
--- a/src/operator/FCImpl.cpp
+++ b/src/operator/FCImpl.cpp
@@ -55,7 +55,7 @@ void Aidge::FCImpl_cpu::forward()
template <>
void Aidge::FCImpl_cpu::backward()
{
- Log::notice("\t Call to Aidge::FCIMpl_cpu::backward()");
+ Log::info("\t Call to Aidge::FCIMpl_cpu::backward()");
const FC_Op& op_ = dynamic_cast<const FC_Op&>(mOp);
const auto& fc_grad = op_.getOutput(0)->grad();
AIDGE_ASSERT(fc_grad, "missing ouput #0 gradient");
@@ -63,7 +63,6 @@ void Aidge::FCImpl_cpu::backward()
AIDGE_ASSERT(op_.getInput(1)->grad(), "missing input #1 gradient");
const auto impl = Registrar<FCImpl_cpu>::create(getBestMatch(getRequiredSpec()));
- Log::notice("\t Call to Aidge::FCIMpl_cpu::backward() - Found impl in registrar");
// Convert input data (no overhead if not needed!)
// TODO: right now, if needed, memory will be allocated/deallocated at each
@@ -76,7 +75,6 @@ void Aidge::FCImpl_cpu::backward()
// Call kernel
const auto batchSize = (input0grad.dims().size() > 1) ? input0grad.dims()[0] : 1;
- Log::notice("\t Call to Aidge::FCIMpl_cpu::backward() - Retrieved grad pointers");
impl.backward(batchSize,
input1grad.dims()[1], // nb input features
input1grad.dims()[0], // nb output features
diff --git a/src/operator/MulImpl.cpp b/src/operator/MulImpl.cpp
index b8bdd161af25a87937b066fc2264ecf1a9816da0..7d640805b1498f77ea376d6d5aadf471e28d37b9 100644
--- a/src/operator/MulImpl.cpp
+++ b/src/operator/MulImpl.cpp
@@ -52,6 +52,10 @@ void Aidge::MulImpl_cpu::backward() {
// Find the correct kernel type
const auto impl = Registrar<MulImpl_cpu>::create(getBestMatch(getRequiredSpec()));
+ Log::info("Debug printing in 1 : ");
+ in1->print();
+ Log::info("Debug printing in 0 : ");
+ in0->print();
// Call kernel
impl.backward(/* input0Length */ in0grad->size(),
@@ -59,10 +63,10 @@ void Aidge::MulImpl_cpu::backward() {
/* grad0Length */ out0grad->size(),
/* input0Dims */ in0->dims(),
/* input1Dims */ in1->dims(),
- out0grad->dims(),
- getCPUPtr(in0),
- getCPUPtr(in1),
- getCPUPtr(out0grad),
+ /* outputDims */ out0grad->dims(),
+ /* input0_ */ getCPUPtr(in0),
+ /* input1_ */ getCPUPtr(in1),
+ /* grad_output_ */ getCPUPtr(out0grad),
getCPUPtr(in0grad),
getCPUPtr(in1grad));
diff --git a/src/operator/SubImpl.cpp b/src/operator/SubImpl.cpp
index 3601675206e5a86cf9c35316b5dd3daa102c59bd..c474394f88cd9aa6331d65f061ab0fc0278bda80 100644
--- a/src/operator/SubImpl.cpp
+++ b/src/operator/SubImpl.cpp
@@ -47,6 +47,7 @@ void Aidge::SubImpl_cpu::backward() {
auto in0 = op_.getInput(0);
auto in1 = op_.getInput(1);
+ auto out0 = op_.getOutput(0);
auto in0grad = op_.getInput(0)->grad();
auto in1grad = op_.getInput(1)->grad();
auto out0grad = op_.getOutput(0)->grad();
@@ -58,6 +59,9 @@ void Aidge::SubImpl_cpu::backward() {
in0grad->print();
in1grad->print();
out0grad->print();
+ Log::info("Sub Impl, pointer of out0 : {}" , static_cast<void*>(out0.get()));
+ out0->print();
+
// Call kernel
impl.backward(/* input0Length */ in0grad->size(),
diff --git a/unit_tests/operator/Test_MetaOperator.cpp b/unit_tests/operator/Test_MetaOperator.cpp
index 4a4dc22dafe6cbb5a880a985df3c7690a67e77a9..fa4102405c815134d664989c993bee020c428d24 100644
--- a/unit_tests/operator/Test_MetaOperator.cpp
+++ b/unit_tests/operator/Test_MetaOperator.cpp
@@ -858,7 +858,7 @@ TEST_CASE("[cpu/operator] MetaOperator", "[Leaky][CPU][Simple]") {
constexpr auto inChannels = 4;
constexpr auto outChannels = 4;
- constexpr auto beta = 1.0;
+ constexpr auto beta = 0.8;
constexpr auto threshold = 1.0;
constexpr auto nbTimeSteps = 2;
@@ -892,6 +892,7 @@ TEST_CASE("[cpu/operator] MetaOperator", "[Leaky][CPU][Simple]") {
auto lif1 = Leaky(nbTimeSteps, beta, threshold, LeakyReset::Subtraction, "leaky");
auto lif1Op = std::static_pointer_cast<OperatorTensor>(lif1->getOperator());
+
auto fc1Op = std::static_pointer_cast<OperatorTensor>(fc1->getOperator());
//fc1Op->associateInput(0, input);
@@ -913,6 +914,17 @@ TEST_CASE("[cpu/operator] MetaOperator", "[Leaky][CPU][Simple]") {
graph->compile("cpu", DataType::Float32);
graph->forwardDims();
+ Log::info("Lif 1 op tensors : \
+ \n Input 0 : {} \
+ \n Input 1 : {} \
+ \n Output 0 : {} \
+ \n Output 1 : {}",
+ static_cast<void*>(lif1Op->getInput(0).get()),
+ static_cast<void*>(lif1Op->getInput(1).get()),
+ static_cast<void*>(lif1Op->getOutput(0).get()),
+ static_cast<void*>(lif1Op->getOutput(1).get())
+ );
+
auto scheduler = SequentialScheduler(graph);
REQUIRE_NOTHROW(scheduler.generateScheduling());
REQUIRE_NOTHROW(scheduler.forward(true));