Learning backend cuda

Context

Suppport Learning with backend_cuda:

• For DataProvider, add a backend attribute to allow reading batch on supported backends
• Add operators to compute Accuracy with a graph: ArgMax, And, ReduceSum

Modified files

• DataProvider.hpp , DataProvider.cpp and pybind_DataProvider.cpp, add backend member to DataProvider;
• ArgMax.hpp , ArgMax.cpp and pybind_ArgMax.cpp, add ArgMax operator;
• And.hpp , And.cpp and pybind_And.cpp, add And operator;
• ReduceSum.hpp , ReduceSum.cpp and pybind_ReduceSum.cpp, add ReduceSum operator;

This MR also fixes: #155 (closed)

TODO

• Support backend_cuda in DataProvider
• Add ArgMax operator for Accuracy computation
• Add And operator for Accuracy computation
• Add ReduceSum operator for Accuracy computation

include/aidge/data/DataProvider.hpp

@@ -35,6 +35,9 @@ private:
     // Desired size of the produced batches
     const std::size_t mBatchSize;
 
+    // The backend for data tensors
+    std::string mBackend;
+
     // Enable random shuffling for learning
     const bool mShuffle;
 
@@ -67,7 +70,7 @@ public:
      * @param database database from which to load the data.
      * @param batchSize number of data samples per batch.
      */
-    DataProvider(const Database& database, const std::size_t batchSize, const bool shuffle = false, const bool dropLast = false);
+    DataProvider(const Database& database, const std::size_t batchSize, const std::string& backend = "cpu", const bool shuffle = false, const bool dropLast = false);
 
 public:
     /**