Added lazy init for grad

include/aidge/data/Tensor.hpp

@@ -591,23 +591,16 @@ public:
 
     inline void print() const { fmt::print("{}\n", toString()); }
 
-    std::shared_ptr<Tensor> grad() {
-        return mGrad;
-    }
-    void setGrad(std::shared_ptr<Tensor> newGrad) {
-        mGrad = newGrad;
-    }
-
     /**
-     * @brief Associate the gradient with a Tensor instance and set its implementation
-     * if none was previously set.
+     * @brief Get the gradient Tensor. If not initialized, set a Tensor instance
+     * and set its implementation if none was previously set.
      * @note Dimensions for the Tensor instance are copied from the original current Tensor.
      * @note If a Tensor instance was already associated, only the implementation is created
      * with values set to 0.
      * @note If Tensor instance and implementation already existed for the gradient
      * nothing is done.
      */
-    void initGrad() {
+    std::shared_ptr<Tensor> grad() {
         if (!mGrad) {
             mGrad = std::make_shared<Tensor>(mDims);
         }
@@ -617,6 +610,11 @@ public:
             mGrad->setBackend(hasImpl() ? mImpl->backend() : "cpu");
             mGrad->zeros();
         }
+        return mGrad;
+    }
+
+    void setGrad(std::shared_ptr<Tensor> newGrad) {
+        mGrad = newGrad;
     }
 
     /**

include/aidge/recipes/GraphViewHelper.hpp

@@ -39,8 +39,6 @@ std::set<std::shared_ptr<Tensor>> producers(std::shared_ptr<GraphView> graphview
  */
 std::set<std::shared_ptr<Tensor>> parameters(std::shared_ptr<GraphView> graphview);
 
-void compile_gradient(std::shared_ptr<Aidge::GraphView> gv);
-
 } // namespace Aidge
 
 #endif /* AIDGE_CORE_UTILS_GRAPHVIEWHELPER_H_ */

include/aidge/scheduler/SequentialScheduler.hpp

@@ -54,7 +54,7 @@ public:
     /**
      * @brief Run the provided Computational Graph with a batch of data
      */
-    void backward(bool instantiateGrad = true);
+    void backward();
 
 private:
     SchedulingPolicy mSchedulingPolicy;

python_binding/data/pybind_Tensor.cpp

@@ -83,7 +83,6 @@ void init_Tensor(py::module& m){
     .def("grad", &Tensor::grad)
     .def("set_grad", &Tensor::setGrad)
     .def("dtype", &Tensor::dataType)
-    .def("init_grad", &Tensor::initGrad)
     .def("size", &Tensor::size)
     .def("resize", (void (Tensor::*)(const std::vector<DimSize_t>&, std::vector<DimSize_t>)) &Tensor::resize)
     .def("has_impl", &Tensor::hasImpl)

python_binding/recipes/pybind_GraphViewHelper.cpp

@@ -24,6 +24,5 @@ namespace py = pybind11;
 namespace Aidge {
 void init_GraphViewHelper(py::module &m) {
     m.def("producers", &producers, py::arg("graphview"));
-    m.def("compile_gradient", &compile_gradient, py::arg("graphview"));
 }
 } // namespace Aidge

src/recipes/GraphViewHelper.cpp

@@ -44,14 +44,3 @@ std::set<std::shared_ptr<Aidge::Tensor>> Aidge::parameters(std::shared_ptr<Aidge
     }
     return res;
 }
-
-void Aidge::compile_gradient(std::shared_ptr<Aidge::GraphView> gv) {
-    for (const auto& node : gv->getNodes()) {
-        // TODO: check that each node is an OperatorTensor
-        AIDGE_ASSERT(node->getOperator()->operatorType() == OperatorType::Tensor, "Cannot instanciate gradient of an Operator ({}) that doesn't use Tensor.", node->getOperator()->type());
-        const std::shared_ptr<OperatorTensor> op = std::dynamic_pointer_cast<OperatorTensor>(node -> getOperator());
-        for (std::size_t o = 0; o < node -> nbOutputs(); ++o) {
-            op->getOutput(o)->initGrad();
-        }
-    }
-}

src/scheduler/SequentialScheduler.cpp

@@ -73,10 +73,7 @@ void Aidge::SequentialScheduler::forward(bool forwardDims, const std::vector<std
     }
 }
 
-void Aidge::SequentialScheduler::backward(bool instanciateGrad) {
-    // create ad set Grad values
-    if (instanciateGrad) { compile_gradient(mGraphView); }
-
+void Aidge::SequentialScheduler::backward() {
     // TODO: Check output grad are not empty
 
     // Generate scheduling *only if empty*