Adapt ExportNode to is_input/is_output parameter.

aidge_export_cpp/operators.py

@@ -61,8 +61,8 @@ def export_params(name: str,
 @operator_register(ExportLibCpp, "Producer")
 class ProducerCPP(ExportNode):
 
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         self.values = np.array(self.operator.get_output(0))
 
         if len(self.values.shape) == 4:  # Note: export in HWC
@@ -70,11 +70,11 @@ class ProducerCPP(ExportNode):
 
     def export(self, export_folder: Path, list_configs: list):
 
-        list_configs.append(f"parameters/{self.attributes['name']}.h")
+        list_configs.append(f"include/parameters/{self.attributes['name']}.h")
         export_params(
             self.attributes['out_name'][0],
             self.values.reshape(-1),
-            str(export_folder / "parameters" / f"{self.attributes['name']}.h"))
+            str(export_folder / "include" / "parameters" / f"{self.attributes['name']}.h"))
 
         return list_configs
 
@@ -87,8 +87,8 @@ class ProducerCPP(ExportNode):
 
 @operator_register(ExportLibCpp, "ReLU")
 class ReLUCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         self.attributes["activation"] = "Rectifier"
         self.attributes["rescaling"] = "NoScaling"
         self.config_template = str(
@@ -106,8 +106,8 @@ class ReLUCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "Conv")
 class ConvCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         # No padding with Conv
         # Use PaddedConv to add padding attribute
         self.attributes["padding"] = [0, 0]
@@ -131,8 +131,8 @@ class ConvCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "PaddedConv")
 class PaddedConvCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         # TODO find a way to retrive attr for meta op
         for n in self.operator.get_micro_graph().get_nodes():
             if n.type() == "Pad":
@@ -163,8 +163,8 @@ class PaddedConvCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "Add")
 class AddCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         self.attributes["elemwise_op"] = "Add"
         self.attributes["activation"] = "Linear"
         self.attributes["rescaling"] = "NoScaling"
@@ -183,8 +183,8 @@ class AddCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "Sub")
 class SubCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         self.attributes["elemwise_op"] = "Sub"
         self.attributes["activation"] = "Linear"
         self.attributes["rescaling"] = "NoScaling"
@@ -204,8 +204,8 @@ class SubCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "Mul")
 class MulCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         self.attributes["elemwise_op"] = "Mul"
         self.attributes["activation"] = "Linear"
         self.attributes["rescaling"] = "NoScaling"
@@ -224,8 +224,8 @@ class MulCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "MaxPooling")
 class MaxPoolCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
 
         # No padding with MaxPooling
         # Use PaddedMaxPooling to add padding attribute
@@ -249,8 +249,8 @@ class MaxPoolCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "PaddedMaxPooling")
 class PaddedMaxPoolCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         for n in self.operator.get_micro_graph().get_nodes():
             if n.type() == "Pad":
                 self.attributes["padding"] = n.get_operator(
@@ -278,8 +278,8 @@ class PaddedMaxPoolCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "GlobalAveragePooling")
 class GlobalAveragePoolCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
 
         self.attributes["stride_dims"] = [1, 1]
         # No padding with MaxPooling
@@ -307,8 +307,8 @@ class GlobalAveragePoolCPP(ExportNodeCpp):
 
 @operator_register(ExportLibCpp, "FC")
 class FcCPP(ExportNodeCpp):
-    def __init__(self, node, mem_info):
-        super().__init__(node, mem_info)
+    def __init__(self, node, mem_info, is_input, is_output):
+        super().__init__(node, mem_info, is_input, is_output)
         self.attributes["activation"] = "Linear"
         self.attributes["rescaling"] = "NoScaling"
         self.config_template = str(