[Upd] standardization of some files

Context

Change some files to apply Aidge C++ standards like no end-of-line spaces, precompilation directoves following the path of the file, include what you use and only what you use

Major modifications

• Standardize #ifndef preprocessor directives in many files
• remove some unused includes and add used includes
• remove end-of-line spaces
• add doxygen to DoReFa.hpp
• add log to CLE.cpp
• move functions from hpp to cpp file in DoReFa, FixedQ and TanhClamp operators
• change size_t for std::size_t

aidge_quantization/unit_tests/test_ptq.py

@@ -21,7 +21,7 @@ ACCURACIES      = (95.4, 94.4)       # (97.9, 97.7)
 NB_BITS         = 4
 
 # --------------------------------------------------------------
-# UTILS 
+# UTILS
 # --------------------------------------------------------------
 
 def propagate(model, scheduler, sample):
@@ -50,7 +50,7 @@ def compute_accuracy(model, samples, labels):
 # --------------------------------------------------------------
 
 class test_ptq(unittest.TestCase):
-    
+
     def setUp(self):
 
         # load the samples / labels (numpy)
@@ -70,19 +70,20 @@ class test_ptq(unittest.TestCase):
     def tearDown(self):
         pass
 
-    
+
     def test_model(self):
 
         Log.set_console_level(Level.Info)
         # compute the base accuracy
         accuracy = compute_accuracy(self.model, self.samples[0:NB_SAMPLES], self.labels)
         self.assertAlmostEqual(accuracy * 100, ACCURACIES[0], msg='base accuracy does not meet the baseline !', delta=0.1)
-    
+
     def test_quant_model(self):
 
-        Log.set_console_level(Level.Info)
+        Log.set_console_level(Level.Debug)
 
         # create the calibration dataset
+
         tensors = []
         for sample in self.samples[0:NB_SAMPLES]:
             sample = prepare_sample(sample)
@@ -91,14 +92,13 @@ class test_ptq(unittest.TestCase):
 
         # quantize the model
 
-        
         aidge_quantization.quantize_network(
-            self.model, 
-            NB_BITS, 
-            tensors, 
-            clipping_mode=aidge_quantization.Clipping.MSE, 
+            self.model,
+            NB_BITS,
+            tensors,
+            clipping_mode=aidge_quantization.Clipping.MSE,
             no_quantization=False,
-            optimize_signs=True, 
+            optimize_signs=True,
             single_shift=False
         )