Adding INT64 Tensor support

Adding INT64 Tensor support

aidge_backend_cpu/unit_tests/test_tensor.py

@@ -16,7 +16,7 @@ class test_tensor(unittest.TestCase):
         self.assertTrue("cpu" in aidge_core.Tensor.get_available_backends())
 
     def test_numpy_int_to_tensor(self):
-        np_array = np.arange(9).reshape(1,1,3,3)
+        np_array = np.arange(9).reshape(1,1,3,3).astype(np.int32)
         # Numpy -> Tensor
         t = aidge_core.Tensor(np_array)
         self.assertEqual(t.dtype(), aidge_core.DataType.Int32)
@@ -35,6 +35,16 @@ class test_tensor(unittest.TestCase):
         for i,j in zip(t.dims(), nnarray.shape):
             self.assertEqual(i,j)
 
+    def test_numpy_int64_to_tensor(self):
+        np_array = np.arange(9).reshape(1,1,3,3).astype(np.int64)
+        # Numpy -> Tensor
+        t = aidge_core.Tensor(np_array)
+        self.assertEqual(t.dtype(), aidge_core.DataType.Int64)
+        for i_t, i_n in zip(t, np_array.flatten()):
+            self.assertTrue(i_t == i_n)
+        for i,j in zip(t.dims(), np_array.shape):
+            self.assertEqual(i,j)
+
     def test_numpy_float_to_tensor(self):
         t = aidge_core.Tensor()
         np_array = np.random.rand(1, 1, 3, 3).astype(np.float32)
@@ -49,7 +59,7 @@ class test_tensor(unittest.TestCase):
     def test_get_set(self):
         dims = [2,2,2]
 
-        np_array = np.arange(8).reshape(dims)
+        np_array = np.arange(8).reshape(dims).astype(np.int32)
         # Numpy -> Tensor
         t = aidge_core.Tensor(np_array)
         for i in range(8):