Fix the NaN bug

Previous version of the PTQ implementation could result in a model producing NaN values. This was due to a poor memory initialization obtained by doing a multiplication by zero. Thus, rescaleTensor(tensor, 0) is now replaced by fillTensor(tensor, 0) which solves the problem.

include/aidge/QuantPTQ.hpp

@@ -54,9 +54,9 @@ namespace Aidge {
      * @brief Normalize the activations of each affine node so that it become equal to one.
      * This is done by reconfiguring the scaling nodes, as well as rescaling the weights and biases tensors.
      * @param graphView The GraphView containing the affine nodes.
-     * @param inputDataSet The input dataset on which the value ranges are computed.
+     * @param valueRanges The node output value ranges computed over the calibration dataset. 
      */
-    void normalizeActivations(std::shared_ptr<GraphView> graphView, std::vector<std::shared_ptr<Tensor>> inputDataSet);
+    void normalizeActivations(std::shared_ptr<GraphView> graphView, std::map<std::string, float> valueRanges);
 
 
     /**
@@ -72,7 +72,7 @@ namespace Aidge {
      * @param nbBits The desired number of bits of the quantization.
      * @param inputDataSet The input dataset on which the value ranges are computed.
      */
-    void quantizeNetwork(std::shared_ptr<GraphView> graphView, std::uint8_t nbBits, std::vector<std::shared_ptr<Tensor>> inputDataSet);
+    void quantizeNetwork(std::shared_ptr<GraphView> graphView, std::uint8_t nbBits, std::vector<std::shared_ptr<Tensor>> inputDataSet, bool OptimizeCliping);
 
     /**
      * @brief Compute the weight ranges of every affine node. Provided for debuging purposes.
@@ -88,6 +88,11 @@ namespace Aidge {
     void clearBiases(std::shared_ptr<GraphView> graphView);
 
     void devPTQ(std::shared_ptr<GraphView> graphView);
+
+    std::map<std::string, std::vector<int>> computeScalingHistograms(std::map<std::string, float> valueRanges, int nbBins, std::shared_ptr<GraphView> graphView, std::vector<std::shared_ptr<Tensor>> inputDataSet);
+
+    float computeBestClipping(std::vector<int> histogram, std::uint8_t nbBits);
+
 }
 
 #endif /* AIDGE_QUANTIZATION_QUANTPTQ_H_ */