From d26753dfea52bf5344baec2b33307fea7da02b6f Mon Sep 17 00:00:00 2001
From: Olivier BICHLER <olivier.bichler@cea.fr>
Date: Mon, 2 Oct 2023 11:31:01 +0200
Subject: [PATCH] Renamed parameter to attribute

---
 .../backend/cpu/operator/AddImpl_forward_kernels.hpp |  6 +++---
 .../aidge/backend/cpu/operator/AvgPoolingImpl.hpp    |  4 ++--
 .../cpu/operator/AvgPoolingImpl_forward_kernels.hpp  |  8 ++++----
 include/aidge/backend/cpu/operator/BatchNormImpl.hpp |  4 ++--
 .../cpu/operator/BatchNormImpl_forward_kernels.hpp   |  6 +++---
 .../aidge/backend/cpu/operator/ConvDepthWiseImpl.hpp |  4 ++--
 .../operator/ConvDepthWiseImpl_forward_kernels.hpp   |  8 ++++----
 include/aidge/backend/cpu/operator/ConvImpl.hpp      |  4 ++--
 .../cpu/operator/ConvImpl_forward_kernels.hpp        | 10 +++++-----
 include/aidge/backend/cpu/operator/FCImpl.hpp        |  4 ++--
 .../backend/cpu/operator/FCImpl_forward_kernels.hpp  | 12 ++++++------
 include/aidge/backend/cpu/operator/LeakyReLUImpl.hpp |  4 ++--
 .../cpu/operator/LeakyReLUImpl_forward_kernels.hpp   |  2 +-
 src/operator/AvgPoolingImpl.cpp                      |  2 +-
 src/operator/BatchNormImpl.cpp                       |  2 +-
 src/operator/ConvDepthWiseImpl.cpp                   |  2 +-
 src/operator/ConvImpl.cpp                            |  2 +-
 src/operator/FCImpl.cpp                              |  4 ++--
 src/operator/LeakyReLUImpl.cpp                       |  2 +-
 unit_tests/operator/Test_LeakyReLUImpl.cpp           |  2 +-
 20 files changed, 46 insertions(+), 46 deletions(-)

diff --git a/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp
index 49059859..221e36dc 100644
--- a/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp
@@ -20,7 +20,7 @@ namespace Aidge {
 
 template <class I1, class O>
 void AddImpl1I_cpu_forward_kernel(const std::size_t inputLength, const void* input1_, void* output_) {
-    // FIXME: missing Add parameters as arguments
+    // FIXME: missing Add attributes as arguments
     const I1* input1 = static_cast<const I1*>(input1_);
     O* output = static_cast<O*>(output_);
 
@@ -32,7 +32,7 @@ void AddImpl1I_cpu_forward_kernel(const std::size_t inputLength, const void* inp
 template <class I1, class I2, class O>
 void AddImpl2I_cpu_forward_kernel(const std::size_t inputLength, const void* input1_, const void* input2_,
                                       void* output_) {
-    // FIXME: missing Add parameters as arguments
+    // FIXME: missing Add attributes as arguments
     const I1* input1 = static_cast<const I1*>(input1_);
     const I2* input2 = static_cast<const I2*>(input2_);
     O* output = static_cast<O*>(output_);
@@ -45,7 +45,7 @@ void AddImpl2I_cpu_forward_kernel(const std::size_t inputLength, const void* inp
 template <class I1, class I2, class I3, class O>
 void AddImpl3I_cpu_forward_kernel(const std::size_t inputLength, const void* input1_, const void* input2_,
                                       const void* input3_, void* output_) {
-    // FIXME: missing Add parameters as arguments
+    // FIXME: missing Add attributes as arguments
     const I1* input1 = static_cast<const I1*>(input1_);
     const I2* input2 = static_cast<const I2*>(input2_);
     const I3* input3 = static_cast<const I3*>(input3_);
diff --git a/include/aidge/backend/cpu/operator/AvgPoolingImpl.hpp b/include/aidge/backend/cpu/operator/AvgPoolingImpl.hpp
index 6768a4f1..cfbcadfe 100644
--- a/include/aidge/backend/cpu/operator/AvgPoolingImpl.hpp
+++ b/include/aidge/backend/cpu/operator/AvgPoolingImpl.hpp
@@ -29,11 +29,11 @@ namespace Aidge {
 class AvgPoolingImpl2DForward_cpu
     : public Registrable<AvgPoolingImpl2DForward_cpu,
                          std::tuple<DataType, DataType>,
-                         void(const AvgPooling_Op<2>::Params &, const std::array<DimSize_t, 4> &, const void *, void *)> {};
+                         void(const AvgPooling_Op<2>::Attrs &, const std::array<DimSize_t, 4> &, const void *, void *)> {};
 class AvgPoolingImpl2DBackward_cpu
     : public Registrable<AvgPoolingImpl2DBackward_cpu,
                          std::tuple<DataType, DataType>,
-                         void(const AvgPooling_Op<2>::Params &, const std::array<DimSize_t, 4> &, const void *, void *)> {};
+                         void(const AvgPooling_Op<2>::Attrs &, const std::array<DimSize_t, 4> &, const void *, void *)> {};
 
 class AvgPoolingImpl2D_cpu : public OperatorImpl {
    private:
diff --git a/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp
index db87fe85..5e9104d6 100644
--- a/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp
@@ -26,17 +26,17 @@ namespace Aidge {
  * @brief Forward kernel for 2D AvgPoolingolution on CPU backend.
  * @tparam I Input data type.
  * @tparam O Output data type.
- * @param params tuple of Parameters from the Operator
+ * @param params tuple of Attributes from the Operator
  * @param dims Array of input dimensions.
  * @param input_ const input Tensor.
  * @param output_ Output Tensor.
  */
 template <class I, class O>
-void AvgPoolingImpl2D_cpu_forward_kernel(const AvgPooling_Op<2>::Params &params,
+void AvgPoolingImpl2D_cpu_forward_kernel(const AvgPooling_Op<2>::Attrs &params,
                                              const std::array<DimSize_t, 4> &dims,
                                              const void *input_,
                                              void *output_) {
-    // FIXME: missing convolution parameters as arguments
+    // FIXME: missing convolution attributes as arguments
     const I *input = static_cast<const I *>(input_);
     O *output = static_cast<O *>(output_);
 
@@ -54,7 +54,7 @@ void AvgPoolingImpl2D_cpu_forward_kernel(const AvgPooling_Op<2>::Params &params,
     // output (batch, outCh, Xout, Yout)
     // input  (batch, ch, Xin, Yin)
     // weight (outCh, ch, kernelX, kernelY)
-    // does not take Dilation parameter into account
+    // does not take Dilation attribute into account
     using signedsize = std::make_signed<std::size_t>::type;
     for (std::size_t batch = 0; batch < dims[0]; ++batch) {
         for (std::size_t ch = 0; ch < dims[1]; ++ch) {
diff --git a/include/aidge/backend/cpu/operator/BatchNormImpl.hpp b/include/aidge/backend/cpu/operator/BatchNormImpl.hpp
index 902dccf4..30557f6c 100644
--- a/include/aidge/backend/cpu/operator/BatchNormImpl.hpp
+++ b/include/aidge/backend/cpu/operator/BatchNormImpl.hpp
@@ -29,7 +29,7 @@ namespace Aidge {
 class BatchNormImpl2DForward_cpu
     : public Registrable<BatchNormImpl2DForward_cpu,
                          std::tuple<DataType, DataType, DataType>,
-                         void(const BatchNorm_Op<2>::Params &,
+                         void(const BatchNorm_Op<2>::Attrs &,
                               const std::array<DimSize_t, 4> &,
                               const void *,
                               const void *,
@@ -41,7 +41,7 @@ class BatchNormImpl2DForward_cpu
 class BatchNormImpl2DBackward_cpu
     : public Registrable<BatchNormImpl2DBackward_cpu,
                          std::tuple<DataType, DataType, DataType>,
-                         void(const BatchNorm_Op<2>::Params &,
+                         void(const BatchNorm_Op<2>::Attrs &,
                               const std::array<DimSize_t, 4> &,
                               const void *,
                               const void *,
diff --git a/include/aidge/backend/cpu/operator/BatchNormImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/BatchNormImpl_forward_kernels.hpp
index c3c2eb00..e46348f9 100644
--- a/include/aidge/backend/cpu/operator/BatchNormImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/BatchNormImpl_forward_kernels.hpp
@@ -27,7 +27,7 @@ namespace Aidge {
  * @tparam W Weight data type.
  * @tparam B Bias data type.
  * @tparam O Output data type.
- * @param params tuple of Parameters from the Operator
+ * @param params tuple of Attributes from the Operator
  * @param dims Array of input dimensions.
  * @param input_ const input Tensor.
  * @param scale_ const scale Tensor.
@@ -37,9 +37,9 @@ namespace Aidge {
  * @param output_ Output Tensor.
  */
 template <class I, class P, class O>
-void BatchNormImpl2D_cpu_forward_kernel(const BatchNorm_Op<2>::Params &params, const std::array<DimSize_t, 4> &dims,
+void BatchNormImpl2D_cpu_forward_kernel(const BatchNorm_Op<2>::Attrs &params, const std::array<DimSize_t, 4> &dims,
                                        const void *input_, const void *scale_, const void *shift_, void *batchMean_, void *batchVar_, void *output_, const bool freeze) {
-    // FIXME: missing convolution parameters as arguments
+    // FIXME: missing convolution attributes as arguments
     const I *input = static_cast<const I *>(input_);
     const P *scale = static_cast<const P *>(scale_);
     const P *shift = static_cast<const P *>(shift_);
diff --git a/include/aidge/backend/cpu/operator/ConvDepthWiseImpl.hpp b/include/aidge/backend/cpu/operator/ConvDepthWiseImpl.hpp
index bd18257e..2826b635 100644
--- a/include/aidge/backend/cpu/operator/ConvDepthWiseImpl.hpp
+++ b/include/aidge/backend/cpu/operator/ConvDepthWiseImpl.hpp
@@ -29,12 +29,12 @@ namespace Aidge {
 class ConvDepthWiseImpl2DForward_cpu
     : public Registrable<ConvDepthWiseImpl2DForward_cpu,
                          std::tuple<DataType, DataType, DataType, DataType>,
-                         void(const ConvDepthWise_Op<2>::Params &, const std::array<DimSize_t, 4> &, const void *,
+                         void(const ConvDepthWise_Op<2>::Attrs &, const std::array<DimSize_t, 4> &, const void *,
                               const void *, const void *, void *)> {};
 class ConvDepthWiseImpl2DBackward_cpu
     : public Registrable<ConvDepthWiseImpl2DBackward_cpu,
                          std::tuple<DataType, DataType, DataType, DataType>,
-                         void(const ConvDepthWise_Op<2>::Params &, const std::array<DimSize_t, 4> &, const void *,
+                         void(const ConvDepthWise_Op<2>::Attrs &, const std::array<DimSize_t, 4> &, const void *,
                               const void *, const void *, void *)> {};
 
 class ConvDepthWiseImpl2D_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/ConvDepthWiseImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/ConvDepthWiseImpl_forward_kernels.hpp
index fb255982..885115d5 100644
--- a/include/aidge/backend/cpu/operator/ConvDepthWiseImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ConvDepthWiseImpl_forward_kernels.hpp
@@ -27,7 +27,7 @@ namespace Aidge {
  * @tparam W Weight data type.
  * @tparam B Bias data type.
  * @tparam O Output data type.
- * @param params tuple of Parameters from the Operator
+ * @param params tuple of Attributes from the Operator
  * @param dims Array of input dimensions.
  * @param input_ const input Tensor.
  * @param weights_ const weight Tensor.
@@ -35,9 +35,9 @@ namespace Aidge {
  * @param output_ Output Tensor.
  */
 template <class I, class W, class B, class O>
-void ConvDepthWiseImpl2D_cpu_forward_kernel(const ConvDepthWise_Op<2>::Params &params, const std::array<DimSize_t, 4> &dims,
+void ConvDepthWiseImpl2D_cpu_forward_kernel(const ConvDepthWise_Op<2>::Attrs &params, const std::array<DimSize_t, 4> &dims,
                                        const void *input_, const void *weights_, const void *biases_, void *output_) {
-    // FIXME: missing convolution parameters as arguments
+    // FIXME: missing convolution attributes as arguments
     const I *input = static_cast<const I *>(input_);
     const W *weights = static_cast<const W *>(weights_);
     const B *biases = static_cast<const B *>(biases_);
@@ -57,7 +57,7 @@ void ConvDepthWiseImpl2D_cpu_forward_kernel(const ConvDepthWise_Op<2>::Params &p
     // output (batch, outCh, Xout, Yout)
     // input  (batch, ch, Xin, Yin)
     // weight (outCh, ch, kernelX, kernelY)
-    // does not take Dilation parameter into account
+    // does not take Dilation attribute into account
     using signedsize = std::make_signed<std::size_t>::type;
     for (std::size_t batch = 0; batch < dims[0]; ++batch) {
         for (std::size_t ch = 0; ch < std::get<2>(params); ++ch) {
diff --git a/include/aidge/backend/cpu/operator/ConvImpl.hpp b/include/aidge/backend/cpu/operator/ConvImpl.hpp
index eab08ff4..b9411fe0 100644
--- a/include/aidge/backend/cpu/operator/ConvImpl.hpp
+++ b/include/aidge/backend/cpu/operator/ConvImpl.hpp
@@ -29,12 +29,12 @@ namespace Aidge {
 class ConvImpl2DForward_cpu
     : public Registrable<ConvImpl2DForward_cpu,
                          std::tuple<DataType, DataType, DataType, DataType>,
-                         void(const Conv_Op<2>::Params &, const std::array<DimSize_t, 4> &, const void *,
+                         void(const Conv_Op<2>::Attrs &, const std::array<DimSize_t, 4> &, const void *,
                               const void *, const void *, void *)> {};
 class ConvImpl2DBackward_cpu
     : public Registrable<ConvImpl2DBackward_cpu,
                          std::tuple<DataType, DataType, DataType, DataType>,
-                         void(const Conv_Op<2>::Params &, const std::array<DimSize_t, 4> &, const void *,
+                         void(const Conv_Op<2>::Attrs &, const std::array<DimSize_t, 4> &, const void *,
                               const void *, const void *, void *)> {};
 
 class ConvImpl2D_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/ConvImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/ConvImpl_forward_kernels.hpp
index c9bf3b8d..5594927e 100644
--- a/include/aidge/backend/cpu/operator/ConvImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ConvImpl_forward_kernels.hpp
@@ -27,7 +27,7 @@ namespace Aidge {
  * @tparam W Weight data type.
  * @tparam B Bias data type.
  * @tparam O Output data type.
- * @param params tuple of Parameters from the Operator
+ * @param params tuple of Attributes from the Operator
  * @param dims Array of input dimensions.
  * @param input_ const input Tensor.
  * @param weights_ const weight Tensor.
@@ -35,9 +35,9 @@ namespace Aidge {
  * @param output_ Output Tensor.
  */
 template <class I, class W, class B, class O>
-void ConvImpl2D_cpu_forward_kernel(const Conv_Op<2>::Params &params, const std::array<DimSize_t, 4> &dims,
+void ConvImpl2D_cpu_forward_kernel(const Conv_Op<2>::Attrs &params, const std::array<DimSize_t, 4> &dims,
                                        const void *input_, const void *weights_, const void *biases_, void *output_) {
-    // FIXME: missing convolution parameters as arguments
+    // FIXME: missing convolution attributes as arguments
     const I *input = static_cast<const I *>(input_);
     const W *weights = static_cast<const W *>(weights_);
     const B *biases = static_cast<const B *>(biases_);
@@ -56,7 +56,7 @@ void ConvImpl2D_cpu_forward_kernel(const Conv_Op<2>::Params &params, const std::
     // output (Xout, Yout, outCh, batch)
     // input  (Xin, Yin, inCh, batch)
     // weight (kernelX, kernelY, inCh, outCh)
-    // does not take Dilation parameter into account
+    // does not take Dilation attribute into account
     for (std::size_t ox = 0; ox < oxSize; ++ox) {
         for (std::size_t oy = 0; oy < oySize; ++oy) {
             const std::size_t ix = ox * std::get<0>(params)[0];
@@ -99,7 +99,7 @@ void ConvImpl2D_cpu_forward_kernel(const Conv_Op<2>::Params &params, const std::
     // output (batch, outCh, Xout, Yout)
     // input  (batch, inCh, Xin, Yin)
     // weight (outCh, inCh, kernelX, kernelY)
-    // does not take Dilation parameter into account
+    // does not take Dilation attribute into account
     using signedsize = std::make_signed<std::size_t>::type;
     for (std::size_t batch = 0; batch < dims[0]; ++batch) {
         for (std::size_t outCh = 0; outCh < std::get<3>(params); ++outCh) {
diff --git a/include/aidge/backend/cpu/operator/FCImpl.hpp b/include/aidge/backend/cpu/operator/FCImpl.hpp
index 22905739..1dfa4043 100644
--- a/include/aidge/backend/cpu/operator/FCImpl.hpp
+++ b/include/aidge/backend/cpu/operator/FCImpl.hpp
@@ -26,11 +26,11 @@ namespace Aidge {
 // compute kernel registry for forward and backward
 class FCImplForward_cpu : public Registrable<FCImplForward_cpu,
                                                  std::tuple<DataType, DataType, DataType, DataType>,
-                                                 void(const FC_Op::Params &, const DimSize_t, const DimSize_t,
+                                                 void(const FC_Op::Attrs &, const DimSize_t, const DimSize_t,
                                                       const void *, const void *, const void *, void *)> {};
 class FCImplBackward_cpu : public Registrable<FCImplBackward_cpu,
                                                   std::tuple<DataType, DataType, DataType, DataType>,
-                                                  void(const FC_Op::Params &, const DimSize_t, const DimSize_t,
+                                                  void(const FC_Op::Attrs &, const DimSize_t, const DimSize_t,
                                                        const void *, const void *, const void *, void *)> {};
 
 class FCImpl_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/FCImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/FCImpl_forward_kernels.hpp
index 3e8b3e34..2b639a73 100644
--- a/include/aidge/backend/cpu/operator/FCImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/FCImpl_forward_kernels.hpp
@@ -19,9 +19,9 @@
 
 namespace Aidge {
 // template <class I, class W, class B, class O>
-// void FCImpl_cpu_forward_kernel(const FC_Op::Params& params, const std::array<DimSize_t, 4>& dims,
+// void FCImpl_cpu_forward_kernel(const FC_Op::Attrs& params, const std::array<DimSize_t, 4>& dims,
 //                                    const void* input_, const void* weights_, const void* biases_, void* output_) {
-//     // FIXME: missing FC parameters as arguments
+//     // FIXME: missing FC attributes as arguments
 //     const I* input = static_cast<const I*>(input_);
 //     const W* weights = static_cast<const W*>(weights_);
 //     const B* biases = static_cast<const B*>(biases_);
@@ -53,9 +53,9 @@ namespace Aidge {
 // }
 
 // template <class I, class W, class B, class O>
-// void FCImpl_cpu_forward_kernel(const FC_Op::Params& params, const std::array<DimSize_t, 2>& dims,
+// void FCImpl_cpu_forward_kernel(const FC_Op::Attrs& params, const std::array<DimSize_t, 2>& dims,
 //                                    const void* input_, const void* weights_, const void* biases_, void* output_) {
-//     // FIXME: missing FC parameters as arguments
+//     // FIXME: missing FC attributes as arguments
 //     const I* input = static_cast<const I*>(input_);
 //     const W* weights = static_cast<const W*>(weights_);
 //     const B* biases = static_cast<const B*>(biases_);
@@ -83,9 +83,9 @@ namespace Aidge {
 // }
 
 template <class I, class W, class B, class O>
-void FCImpl_cpu_forward_kernel(const FC_Op::Params& params, const DimSize_t batchSize, const DimSize_t oneInputSize,
+void FCImpl_cpu_forward_kernel(const FC_Op::Attrs& params, const DimSize_t batchSize, const DimSize_t oneInputSize,
                                    const void* input_, const void* weights_, const void* biases_, void* output_) {
-    // FIXME: missing FC parameters as arguments
+    // FIXME: missing FC attributes as arguments
     const I* input = static_cast<const I*>(input_);
     const W* weights = static_cast<const W*>(weights_);
     const B* biases = static_cast<const B*>(biases_);
diff --git a/include/aidge/backend/cpu/operator/LeakyReLUImpl.hpp b/include/aidge/backend/cpu/operator/LeakyReLUImpl.hpp
index 48a13a54..386ef999 100644
--- a/include/aidge/backend/cpu/operator/LeakyReLUImpl.hpp
+++ b/include/aidge/backend/cpu/operator/LeakyReLUImpl.hpp
@@ -24,10 +24,10 @@ namespace Aidge {
 
 // compute kernel registry for forward and backward
 class LeakyReLUImplForward_cpu
-    : public Registrable<LeakyReLUImplForward_cpu, std::tuple<DataType, DataType>, void(const LeakyReLU_Op::Params&, std::size_t, const void*, void*)> {
+    : public Registrable<LeakyReLUImplForward_cpu, std::tuple<DataType, DataType>, void(const LeakyReLU_Op::Attrs&, std::size_t, const void*, void*)> {
 };
 class LeakyReLUImplBackward_cpu
-    : public Registrable<LeakyReLUImplBackward_cpu, std::tuple<DataType, DataType>, void(const LeakyReLU_Op::Params&, std::size_t, const void*, void*)> {
+    : public Registrable<LeakyReLUImplBackward_cpu, std::tuple<DataType, DataType>, void(const LeakyReLU_Op::Attrs&, std::size_t, const void*, void*)> {
 };
 
 class LeakyReLUImpl_cpu : public OperatorImpl {
diff --git a/include/aidge/backend/cpu/operator/LeakyReLUImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/LeakyReLUImpl_forward_kernels.hpp
index 68d60b0b..a4a926e8 100644
--- a/include/aidge/backend/cpu/operator/LeakyReLUImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/LeakyReLUImpl_forward_kernels.hpp
@@ -18,7 +18,7 @@
 
 namespace Aidge {
 template <class I, class O>
-void LeakyReLUImpl_cpu_forward_kernel(const LeakyReLU_Op::Params& params,
+void LeakyReLUImpl_cpu_forward_kernel(const LeakyReLU_Op::Attrs& params,
                                      std::size_t inputLenght,
                                      const void* input_,
                                      void* output_) {
diff --git a/src/operator/AvgPoolingImpl.cpp b/src/operator/AvgPoolingImpl.cpp
index 137bf639..b1f82bbb 100644
--- a/src/operator/AvgPoolingImpl.cpp
+++ b/src/operator/AvgPoolingImpl.cpp
@@ -70,7 +70,7 @@ void Aidge::AvgPoolingImpl2D_cpu::forward() {
             Registrar<AvgPoolingImpl2DForward_cpu>::create({mOp.getInput(0)->dataType(), mOp.getOutput(0)->dataType()});
 
     // Call kernel
-    kernelFunc(mOp.getStaticParameters(),
+    kernelFunc(mOp.getStaticAttributes(),
                mOp.getInput(0)->dims<4>(),
                mOp.getInput(0)->getImpl()->rawPtr(),
                mOp.getOutput(0)->getImpl()->rawPtr());
diff --git a/src/operator/BatchNormImpl.cpp b/src/operator/BatchNormImpl.cpp
index 9ced036e..90ee2b7a 100644
--- a/src/operator/BatchNormImpl.cpp
+++ b/src/operator/BatchNormImpl.cpp
@@ -76,7 +76,7 @@ void Aidge::BatchNormImpl2D_cpu::forward() {
                                                           mOp.getOutput(0)->dataType()});
 
     // Call kernel
-    kernelFunc(mOp.getStaticParameters(),
+    kernelFunc(mOp.getStaticAttributes(),
                mOp.getInput(0)->dims<4>(),
                mOp.getInput(0)->getImpl()->rawPtr(),
                mOp.getInput(1)->getImpl()->rawPtr(),
diff --git a/src/operator/ConvDepthWiseImpl.cpp b/src/operator/ConvDepthWiseImpl.cpp
index 9e11b4ea..7801f64e 100644
--- a/src/operator/ConvDepthWiseImpl.cpp
+++ b/src/operator/ConvDepthWiseImpl.cpp
@@ -77,7 +77,7 @@ void Aidge::ConvDepthWiseImpl2D_cpu::forward() {
                                                           mOp.getInput(2)->dataType(), mOp.getOutput(0)->dataType()});
 
     // Call kernel
-    kernelFunc(mOp.getStaticParameters(), std::static_pointer_cast<Tensor>(mOp.getInput(0))->dims<4>(),
+    kernelFunc(mOp.getStaticAttributes(), std::static_pointer_cast<Tensor>(mOp.getInput(0))->dims<4>(),
                mOp.getInput(0)->getImpl()->rawPtr(), mOp.getInput(1)->getImpl()->rawPtr(),
                mOp.getInput(2)->getImpl()->rawPtr(), mOp.getOutput(0)->getImpl()->rawPtr());
 }
diff --git a/src/operator/ConvImpl.cpp b/src/operator/ConvImpl.cpp
index 97e73ce5..edab4432 100644
--- a/src/operator/ConvImpl.cpp
+++ b/src/operator/ConvImpl.cpp
@@ -75,7 +75,7 @@ void Aidge::ConvImpl2D_cpu::forward() {
                                                           mOp.getInput(2)->dataType(), mOp.getOutput(0)->dataType()});
 
     // Call kernel
-    kernelFunc(mOp.getStaticParameters(), std::static_pointer_cast<Tensor>(mOp.getInput(0))->dims<4>(),
+    kernelFunc(mOp.getStaticAttributes(), std::static_pointer_cast<Tensor>(mOp.getInput(0))->dims<4>(),
                mOp.getInput(0)->getImpl()->rawPtr(), mOp.getInput(1)->getImpl()->rawPtr(),
                mOp.getInput(2)->getImpl()->rawPtr(), mOp.getOutput(0)->getImpl()->rawPtr());
 
diff --git a/src/operator/FCImpl.cpp b/src/operator/FCImpl.cpp
index 540ecdf3..3cf1ccf6 100644
--- a/src/operator/FCImpl.cpp
+++ b/src/operator/FCImpl.cpp
@@ -98,7 +98,7 @@ void Aidge::FCImpl_cpu::forward()
     // Call kernel
     // if (mOp.getInput(0)->nbDims() == 4) {
     //     kernelFunc(
-    //         mOp.getStaticParameters(),
+    //         mOp.getStaticAttributes(),
     //         std::static_pointer_cast<Tensor>(mOp.getInput(0))->dims<4>(),
     //         mOp.getInput(0)->getImpl()->rawPtr(),
     //         mOp.mInputs[1]->getImpl()->rawPtr(),
@@ -107,7 +107,7 @@ void Aidge::FCImpl_cpu::forward()
     // }
     // else
     kernelFunc(
-        mOp.getStaticParameters(),
+        mOp.getStaticAttributes(),
         mOp.getInput(0)->dims()[0],
         mOp.getInput(0)->sizeM1(),
         mOp.getInput(0)->getImpl()->rawPtr(),
diff --git a/src/operator/LeakyReLUImpl.cpp b/src/operator/LeakyReLUImpl.cpp
index 46b7224f..316d3641 100644
--- a/src/operator/LeakyReLUImpl.cpp
+++ b/src/operator/LeakyReLUImpl.cpp
@@ -65,7 +65,7 @@ void Aidge::LeakyReLUImpl_cpu::forward() {
         mOp.getOutput(0)->dataType()});
 
     // Call kernel
-    kernelFunc(mOp.getStaticParameters(),
+    kernelFunc(mOp.getStaticAttributes(),
         std::static_pointer_cast<Tensor>(mOp.getInput(0))->size(),
         mOp.getInput(0)->getImpl()->rawPtr(),
         mOp.getOutput(0)->getImpl()->rawPtr());
diff --git a/unit_tests/operator/Test_LeakyReLUImpl.cpp b/unit_tests/operator/Test_LeakyReLUImpl.cpp
index 7096962e..d5bd91ff 100644
--- a/unit_tests/operator/Test_LeakyReLUImpl.cpp
+++ b/unit_tests/operator/Test_LeakyReLUImpl.cpp
@@ -153,7 +153,7 @@ TEST_CASE("[cpu/operator] LeakyReLU(forward)") {
         REQUIRE(*myLeakyReLU->getOperator()->getOutput(0) == *expectedOutput);
     }
 
-    SECTION("Test construction parameter: negative_slop") {
+    SECTION("Test construction attribute: negative_slop") {
         std::shared_ptr<Tensor> input0 = std::make_shared<Tensor>(Array1D<float,10> {
             {0.0f, 1.0f, 2.0f,-3.0f, 4.0f,-5.0f,-6.0f, 7.0f, 8.0f, 9.0f}
         });
-- 
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