Merge branch 'ExportTensorRegistration' into 'dev'

[fix] Temporary fix for export backend that need to register fake tensor backends.

See merge request !259

aidge_core/aidge_export_aidge/registry.py

@@ -5,6 +5,3 @@ import aidge_core
 
 class ExportSerialize(ExportLib):
     _name="export_serialize"
-
-aidge_core.register_Tensor(["export_serialize", aidge_core.dtype.float32],
-                           aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.float32]))

aidge_core/export_utils/export_registry.py

@@ -2,6 +2,7 @@ from typing import Dict, List
 import aidge_core
 from aidge_core.export_utils import ExportNode
 
+
 class classproperty:
     """Helper class to define class-level properties.
 
@@ -50,6 +51,35 @@ class ExportLib(aidge_core.OperatorImpl):
 
     def __init__(self, operator):
         super(ExportLib, self).__init__(operator, self._name)
+        if self._name is None:
+            raise ValueError("ExportLib  {self.__class__.__name__} does not define the attribute ``_name``.")
+
+        # TODO: This is a patch, setBackend method is used to set an ExportLib as an Implementation.
+        # But it also set the backend of the Tensor and we don't define a backend for Tensor.
+        # The following code block associate to the export backend the "cpu" implementation.
+        # This is tracked by the issue :
+        #         https://gitlab.eclipse.org/eclipse/aidge/aidge_core/-/issues/178
+
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.float32],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.float32]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.float16],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.float16]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.int8],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.int8]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.int16],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.int16]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.int32],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.int32]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.int64],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.int64]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.uint8],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.uint8]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.uint16],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.uint16]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.uint32],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.uint32]))
+        aidge_core.register_Tensor([self._name, aidge_core.dtype.uint64],
+                                    aidge_core.get_key_value_Tensor(["cpu", aidge_core.dtype.uint64]))
 
     @classproperty
     def _export_node_registry(cls) -> Dict[str, List['ExportNode']]: