Change argument type from size_t to std::size_t in DataProvider

include/aidge/data/DataProvider.hpp

@@ -20,14 +20,14 @@ public:
      * @param database database from which to load the data.
      * @param batchSize number of data samples per batch.
      */
-    DataProvider(Database& database, size_t batchSize);
+    DataProvider(Database& database, std::size_t batchSize);
 
     /**
      * @brief Create a batch for each data modality in the database. The returned batch contain the data as sorted in the database.
      * @param startIndex the starting index in the database to start the batch from. 
      * @return a vector of tensors. Each tensor is a batch corresponding to one modality.
      */
-    std::vector<std::shared_ptr<Tensor>> readBatch(size_t startIndex);
+    std::vector<std::shared_ptr<Tensor>> readBatch(std::size_t startIndex);
 
 protected:
 
@@ -35,7 +35,7 @@ protected:
     Database& mDatabase;
     
     size_t mNumberModality;
-    std::vector<std::vector<size_t>> mDataSizes;
+    std::vector<std::vector<std::size_t>> mDataSizes;
     std::vector<std::string> mDataBackends;
     std::vector<DataType> mDataTypes;
     

src/data/DataProvider.cpp

@@ -4,7 +4,7 @@
 
 using namespace Aidge; 
 
-DataProvider::DataProvider(Database& database, size_t batchSize)
+DataProvider::DataProvider(Database& database, std::size_t batchSize)
     :
     mDatabase(database),
     mBatchSize(batchSize)
@@ -22,7 +22,7 @@ DataProvider::DataProvider(Database& database, size_t batchSize)
     }
 }
 
-std::vector<std::shared_ptr<Tensor>> DataProvider::readBatch(size_t startIndex)
+std::vector<std::shared_ptr<Tensor>> DataProvider::readBatch(std::size_t startIndex)
 {
     assert((startIndex) <= mDatabase.getLen() && " DataProvider readBatch : database fetch out of bounds");