Refactoring Tensor

Adding context to Tensor
Adding "active area" to Tensor
Forward declaring TensorImpl in Tensor instead of the another way around
CPU storage is unsigned char instead of void *
todo: memory location for device different than CPU
todo: a Tensor can share a TensorImpl with another Tensor
TensorImpl = storage
Tensor = view on storage

Notes:

• Tensor::getImpl() returns a reference not a pointer, thus client code must replace getImpl()-> by getImpl().
• Tensor.hpp does not includes backend\TensorImpl.hpp but backend\TensorImpl.hpp includes Tensor.hpp. Thus client code needs to include backend\TensorImpl.hpp (with or without Tensor.hpp)

aidge_core/unit_tests/test_tensor.py

-"""
-Copyright (c) 2023 CEA-List
-
-This program and the accompanying materials are made available under the
-terms of the Eclipse Public License 2.0 which is available at
-http://www.eclipse.org/legal/epl-2.0.
-
-SPDX-License-Identifier: EPL-2.0
-"""
-
-import unittest
-import aidge_core
-
-from functools import reduce
-import numpy as np
-
-class test_tensor(unittest.TestCase):
-    """
-    """
-    def setUp(self):
-        pass
-
-    def tearDown(self):
-        pass
-
-    def test_getcoord_getidx(self):
-        dims = [2,2,2]
-        size = reduce((lambda x, y: x*y), dims)
-
-        np_array = np.arange(size).reshape(dims)
-
-        t = aidge_core.Tensor(np_array)
-        for i in range(size):
-            coord = t.get_coord(i)
-            idx = t.get_idx(coord)
-            self.assertEqual(idx, i)
-
-if __name__ == '__main__':
-    unittest.main()
-
-
-
-
-