Merge pull request #851 from helmholtz-analytics/enhancement/798-logi…

…cal-dndarrray

Enhancement/798 logical dndarrray

heat/core/logical.py

@@ -237,13 +237,29 @@ def isclose(
         output_gshape = stride_tricks.broadcast_shape(t1.gshape, t2.gshape)
         res = torch.empty(output_gshape, device=t1.device.torch_device).bool()
         t1.comm.Allgather(_local_isclose, res)
-        result = factories.array(res, dtype=types.bool, device=t1.device, split=t1.split)
+        result = DNDarray(
+            res,
+            gshape=output_gshape,
+            dtype=types.bool,
+            split=t1.split,
+            device=t1.device,
+            comm=t1.comm,
+            balanced=t1.is_balanced,
+        )
     else:
         if _local_isclose.dim() == 0:
             # both x and y are scalars, return a single boolean value
-            result = bool(factories.array(_local_isclose).item())
+            result = bool(_local_isclose.item())
         else:
-            result = factories.array(_local_isclose, dtype=types.bool, device=t1.device)
+            result = DNDarray(
+                _local_isclose,
+                gshape=tuple(_local_isclose.shape),
+                dtype=types.bool,
+                split=None,
+                device=t1.device,
+                comm=t1.comm,
+                balanced=t1.is_balanced,
+            )
 
     return result