Merge branch 'QualityOfLife' into 'dev'

Quality of life

See merge request eclipse/aidge/aidge_core!73

python_binding/operator/pybind_Pad.cpp

@@ -25,7 +25,7 @@ namespace py = pybind11;
 namespace Aidge {
 
 template <DimIdx_t DIM> void declare_PadOp(py::module &m) {
-  py::class_<Pad_Op<DIM>, std::shared_ptr<Pad_Op<DIM>>, Operator, Attributes>(
+  py::class_<Pad_Op<DIM>, std::shared_ptr<Pad_Op<DIM>>, Attributes, Operator>(
     m, ("PadOp" + std::to_string(DIM) + "D").c_str(),
     py::multiple_inheritance())
   .def(py::init<const std::array<DimSize_t, 2*DIM> &,
@@ -36,6 +36,7 @@ template <DimIdx_t DIM> void declare_PadOp(py::module &m) {
         py::arg("borderValue") = 0.0)
     .def("get_inputs_name", &Pad_Op<DIM>::getInputsName)
     .def("get_outputs_name", &Pad_Op<DIM>::getOutputsName)
+    .def("attributes_name", &Pad_Op<DIM>::staticGetAttrsName)
     ;
 
   m.def(("Pad" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& beginEndTuples,

python_binding/operator/pybind_Producer.cpp

@@ -30,13 +30,14 @@ void declare_Producer(py::module &m) {
 
 
 void init_Producer(py::module &m) {
-    py::class_<Producer_Op,  std::shared_ptr<Producer_Op>, OperatorTensor, Attributes>(
+    py::class_<Producer_Op,  std::shared_ptr<Producer_Op>, Attributes, OperatorTensor>(
         m,
         "ProducerOp",
         py::multiple_inheritance())
     .def("dims", &Producer_Op::dims)
     .def("get_inputs_name", &Producer_Op::getInputsName)
-    .def("get_outputs_name", &Producer_Op::getOutputsName);
+    .def("get_outputs_name", &Producer_Op::getOutputsName)
+    .def("attributes_name", &Producer_Op::staticGetAttrsName);
     m.def("Producer", static_cast<std::shared_ptr<Node>(*)(const std::shared_ptr<Tensor>, const std::string&, bool)>(&Producer), py::arg("tensor"), py::arg("name") = "", py::arg("constant") = false);
 
     declare_Producer<1>(m);

python_binding/operator/pybind_ReduceMean.cpp

@@ -24,10 +24,11 @@ namespace py = pybind11;
 namespace Aidge {
 
 template <DimIdx_t DIM> void declare_ReduceMeanOp(py::module &m) {
-  py::class_<ReduceMean_Op<DIM>, std::shared_ptr<ReduceMean_Op<DIM>>, OperatorTensor, Attributes>(
+  py::class_<ReduceMean_Op<DIM>, std::shared_ptr<ReduceMean_Op<DIM>>, Attributes, OperatorTensor>(
     m, ("ReduceMeanOp" + std::to_string(DIM) + "D").c_str(), py::multiple_inheritance())
     .def("get_inputs_name", &ReduceMean_Op<DIM>::getInputsName)
     .def("get_outputs_name", &ReduceMean_Op<DIM>::getOutputsName)
+    .def("attributes_name", &ReduceMean_Op<DIM>::staticGetAttrsName)
     ;
 
   m.def(("ReduceMean" + std::to_string(DIM) + "D").c_str(), [](const std::vector<int>& axes,

python_binding/operator/pybind_Softmax.cpp

@@ -19,9 +19,10 @@ namespace py = pybind11;
 namespace Aidge {
 
 void init_Softmax(py::module& m) {
-    py::class_<Softmax_Op, std::shared_ptr<Softmax_Op>, OperatorTensor, Attributes>(m, "SoftmaxOp", py::multiple_inheritance())
+    py::class_<Softmax_Op, std::shared_ptr<Softmax_Op>, Attributes, OperatorTensor>(m, "SoftmaxOp", py::multiple_inheritance())
     .def("get_inputs_name", &Softmax_Op::getInputsName)
-    .def("get_outputs_name", &Softmax_Op::getOutputsName);
+    .def("get_outputs_name", &Softmax_Op::getOutputsName)
+    .def("attributes_name", &Softmax_Op::staticGetAttrsName);
 
     m.def("Softmax", &Softmax, py::arg("axis"), py::arg("name") = "");
 }

python_binding/operator/pybind_Transpose.cpp

@@ -25,12 +25,13 @@
 namespace py = pybind11;
 namespace Aidge {
 
-template <DimIdx_t DIM> 
+template <DimIdx_t DIM>
 void declare_Transpose(py::module &m) {
-  py::class_<Transpose_Op<DIM>, std::shared_ptr<Transpose_Op<DIM>>, OperatorTensor, Attributes>(
+  py::class_<Transpose_Op<DIM>, std::shared_ptr<Transpose_Op<DIM>>, Attributes, OperatorTensor>(
     m, ("TransposeOp" + std::to_string(DIM) + "D").c_str(), py::multiple_inheritance())
   .def("get_inputs_name", &Transpose_Op<DIM>::getInputsName)
-  .def("get_outputs_name", &Transpose_Op<DIM>::getOutputsName);
+  .def("get_outputs_name", &Transpose_Op<DIM>::getOutputsName)
+  .def("attributes_name", &Transpose_Op<DIM>::staticGetAttrsName);
 
   m.def(("Transpose" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& output_dims_order,
                                                                   const std::string& name) {

python_binding/pybind_core.cpp

@@ -11,6 +11,9 @@
 
 #include <pybind11/pybind11.h>
 
+#include "aidge/backend/cpu/data/TensorImpl.hpp" // This include add Tensor
+
+
 namespace py = pybind11;
 
 namespace Aidge {

python_binding/utils/pybind_Parameter.cpp → python_binding/utils/pybind_Attributes.cpp

 #include <pybind11/pybind11.h>
 #include "aidge/utils/Attributes.hpp"
 #include "aidge/utils/DynamicAttributes.hpp"
+#include "aidge/utils/StaticAttributes.hpp"
 
 namespace py = pybind11;
 namespace Aidge {
@@ -21,11 +22,13 @@ void init_Attributes(py::module& m){
     .def("has_attr", &Attributes::hasAttr, py::arg("name"))
     .def("get_attr_type", &Attributes::getAttrType, py::arg("name"))
     .def("get_attrs_name", &Attributes::getAttrsName)
-    .def("get_attr", &Attributes::getAttrPy, py::arg("name"));
+    .def("get_attr", &Attributes::getAttrPy, py::arg("name"))
+    .def("__getattr__", &Attributes::getAttrPy, py::arg("name"))
+    .def("set_attr", &Attributes::setAttrPy, py::arg("name"), py::arg("value"))
+    .def("__setattr__", &Attributes::setAttrPy, py::arg("name"), py::arg("value"));
 
     py::class_<DynamicAttributes, std::shared_ptr<DynamicAttributes>, Attributes>(m, "DynamicAttributes")
     .def("add_attr", &DynamicAttributes::addAttrPy, py::arg("name"), py::arg("value"))
-    .def("set_attr", &DynamicAttributes::setAttrPy, py::arg("name"), py::arg("value"))
     .def("del_attr", &DynamicAttributes::delAttr, py::arg("name"));
 
     m.def("test_DynamicAttributes_binding", &test_DynamicAttributes_binding);

unit_tests/data/Test_TensorImpl.cpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <array>
+
+#include <catch2/catch_test_macros.hpp>
+
+#include "aidge/data/Tensor.hpp"
+#include "aidge/utils/TensorUtils.hpp"
+#include "aidge/backend/cpu/data/TensorImpl.hpp"
+
+using namespace Aidge;
+
+TEST_CASE("Tensor creation") {
+  SECTION("from const array") {
+    Tensor x = Array3D<int, 2, 2, 2>{{{{1, 2}, {3, 4}}, {{5, 6}, {7, 8}}}};
+
+    Tensor xCopy = Array3D<int, 2, 2, 2>{{{{1, 2}, {3, 4}}, {{5, 6}, {7, 8}}}};
+
+    Tensor xFloat =
+        Array3D<float, 2, 2, 2>{{{{1., 2.}, {3., 4.}}, {{5., 6.}, {7., 8.}}}};
+
+    SECTION("Tensor features") {
+      REQUIRE(x.nbDims() == 3);
+      REQUIRE(x.dims()[0] == 2);
+      REQUIRE(x.dims()[1] == 2);
+      REQUIRE(x.dims()[2] == 2);
+      REQUIRE(x.size() == 8);
+    }
+
+    SECTION("Access to array") {
+      REQUIRE(static_cast<int *>(x.getImpl()->rawPtr())[0] == 1);
+      REQUIRE(static_cast<int *>(x.getImpl()->rawPtr())[7] == 8);
+    }
+
+    SECTION("get function") {
+      REQUIRE(x.get<int>({0, 0, 0}) == 1);
+      REQUIRE(x.get<int>({0, 0, 1}) == 2);
+      REQUIRE(x.get<int>({0, 1, 1}) == 4);
+      REQUIRE(x.get<int>({1, 1, 0}) == 7);
+      x.set<int>({1, 1, 1}, 36);
+      REQUIRE(x.get<int>({1, 1, 1}) == 36);
+    }
+
+    SECTION("Pretty printing for debug") { REQUIRE_NOTHROW(x.print()); }
+
+    SECTION("Tensor (in)equality") {
+      REQUIRE(x == xCopy);
+      REQUIRE_FALSE(x == xFloat);
+    }
+  }
+}
+
+TEST_CASE("Tensor methods") {
+  Tensor x = Array3D<int, 2, 2, 2>{{
+    {{1, 2},
+     {3, 4}},
+    {{5, 6},
+     {7, 8}}
+  }};
+
+  Tensor xCopy = Array3D<int, 2, 2, 2>{{{{1, 2}, {3, 4}}, {{5, 6}, {7, 8}}}};
+
+  Tensor xFloat =
+      Array3D<float, 2, 2, 2>{{{{1., 2.}, {3., 4.}}, {{5., 6.}, {7., 8.}}}};
+
+  SECTION("Tensor sharing") {
+    Tensor xCopyCtor(x);
+    REQUIRE(xCopyCtor.getImpl() == x.getImpl());
+
+    Tensor xEqOp = x;
+    REQUIRE(xEqOp.getImpl() == x.getImpl());
+
+    Tensor xCloned = x.clone();
+    REQUIRE(xCloned.getImpl() != x.getImpl());
+    REQUIRE(xCloned == x);
+  }
+
+  SECTION("Tensor extract") {
+    Tensor y = x.extract({0, 1});
+    REQUIRE(y.getImpl() == x.getImpl());
+    REQUIRE(approxEq<int>(y, Array1D<int, 2>{{3, 4}}));
+    REQUIRE(y.isContiguous());
+    
+    Tensor y2 = x.extract({0, 1, 1}, {2, 1, 1});
+    REQUIRE(y2.getImpl() == x.getImpl());
+    REQUIRE(!y2.isContiguous());
+    Tensor y3 = y2.clone();
+    REQUIRE(y3.isContiguous());
+    REQUIRE(approxEq<int>(y3, Array3D<int, 2, 1, 1>{{{{4}}, {{8}}}}));
+  }
+}