Fixed test issues

aidge_export_cpp/unit_tests/test_export.py

@@ -25,10 +25,10 @@ def initFiller(model):
             value.set_backend("cpu")
             tuple_out = node.output(0)[0]
             # No conv in current network
-            if tuple_out[0].type() == "Conv" and tuple_out[1] == 1:
+            if tuple_out[0].type() == "Conv2D" and tuple_out[1] == 1:
                 # Conv weight
                 aidge_core.xavier_uniform_filler(value)
-            elif tuple_out[0].type() == "Conv" and tuple_out[1] == 2:
+            elif tuple_out[0].type() == "Conv2D" and tuple_out[1] == 2:
                 # Conv bias
                 aidge_core.constant_filler(value, 0.01)
             elif tuple_out[0].type() == "FC" and tuple_out[1] == 1:
@@ -520,7 +520,7 @@ class test_operator_export(unittest.TestCase):
             aidge_core.ConvDepthWise2D(nb_channels=3, kernel_dims=(3, 3), name="conv")
         ])
 
-        self.unit_test_export(model, "ConvDepthWise2D", [[1, 3, 12, 12]], False, False)
+        self.unit_test_export(model, "ConvDepthWise2D", [[1, 3, 12, 12]])
 
     def test_max_pooling(self):
         print("MaxPooling2D")
@@ -529,7 +529,7 @@ class test_operator_export(unittest.TestCase):
         ])
         model.set_ordered_outputs([(model.get_node("max_pool"), 0)], True)
 
-        self.unit_test_export(model, "MaxPooling2D", [[1, 2, 12, 12]], False, False)
+        self.unit_test_export(model, "MaxPooling2D", [[1, 2, 12, 12]])
 
     def test_avg_pooling(self):
         print("AvgPooling2D")
@@ -537,7 +537,7 @@ class test_operator_export(unittest.TestCase):
             aidge_core.AvgPooling2D(kernel_dims=(3, 3), name="avg_pool")
         ])
 
-        self.unit_test_export(model, "AvgPooling2D", [[1, 2, 12, 12]], False, False)
+        self.unit_test_export(model, "AvgPooling2D", [[1, 2, 12, 12]])
 
     def test_pad2D(self):
         print("Pad2D")
@@ -668,5 +668,12 @@ class test_operator_export(unittest.TestCase):
         initFiller(model)
         self.unit_test_export(model, "Conv", [[1, 1, 9, 9]])
 
+    def test_Conv2(self):
+        model = aidge_core.sequential([
+            aidge_core.Conv2D(2, 2, [3, 3], name="InputNode")
+        ])
+        initFiller(model)
+        self.unit_test_export(model, "Conv2", [[1, 2, 9, 9]])
+
 if __name__ == '__main__':
     unittest.main()