Update operators implementation

• adapt to core changes with Operator not refering to Tensors anymore
• remove assertions already performed in abstract operators constructions
• fix missing 'template' keyword prior to dependent template name 'dims'

aidge_backend_cpu/unit_tests/test_recipies.py

@@ -49,24 +49,24 @@ class test_recipies(unittest.TestCase):
         np_shift = np.array([0.05]).astype(np.float32)
         np_mean = np.array([0.05]).astype(np.float32)
         np_var = np.array([0.05]).astype(np.float32)
-        conv.input(1)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_weights))
-        conv.input(2)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_bias))
-        bn.input(1)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_scale))
-        bn.input(2)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_shift))
-        bn.input(3)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_mean))
-        bn.input(4)[0].get_operator().set_output_tensor(aidge_core.Tensor(np_var))
+        conv.input(1)[0].get_operator().set_output(0, aidge_core.Tensor(np_weights))
+        conv.input(2)[0].get_operator().set_output(0, aidge_core.Tensor(np_bias))
+        bn.input(1)[0].get_operator().set_output(0, aidge_core.Tensor(np_scale))
+        bn.input(2)[0].get_operator().set_output(0, aidge_core.Tensor(np_shift))
+        bn.input(3)[0].get_operator().set_output(0, aidge_core.Tensor(np_mean))
+        bn.input(4)[0].get_operator().set_output(0, aidge_core.Tensor(np_var))
         scheduler0 = aidge_core.SequentialScheduler(graph_view)
         scheduler0.forward()
 
         for outNode in graph_view.get_output_nodes():
-            output_aidge0 = outNode.get_operator().output(0)
+            output_aidge0 = outNode.get_operator().get_output(0)
 
         aidge_core.fuse_batchnorm(graph_view)
         scheduler1 = aidge_core.SequentialScheduler(graph_view)
         scheduler1.forward()
 
         for outNode in graph_view.get_output_nodes():
-            output_aidge1 = outNode.get_operator().output(0)
+            output_aidge1 = outNode.get_operator().get_output(0)
 
         self.assertTrue(aidge_core.approx_eq(output_aidge0, output_aidge1, 0.000001, 0.0001))