Features/54 distributed random numbers

heat/core/manipulations.py

@@ -569,8 +569,6 @@ def sort(a, axis=None, descending=False, out=None):
             second_result[idx_slice] = r_val
             second_indices[idx_slice] = r_ind
 
-        # print('second_result', second_result, 'tmp_indices', second_indices)
-
         second_result, tmp_indices = second_result.sort(dim=0, descending=descending)
         final_result = second_result.transpose(0, axis)
         final_indices = torch.empty_like(second_indices)

heat/core/operations.py

@@ -223,9 +223,9 @@ def __reduce_op(x, partial_op, reduction_op, **kwargs):
             lshape_losedim = tuple(x.lshape[dim] for dim in range(len(x.lshape)) if dim not in axis)
             output_shape = gshape_losedim
             # Take care of special cases argmin and argmax: keep partial.shape[0]
-            if (0 in axis and partial.shape[0] != 1):
+            if 0 in axis and partial.shape[0] != 1:
                 lshape_losedim = (partial.shape[0],) + lshape_losedim
-            if (not 0 in axis and partial.shape[0] != x.lshape[0]):
+            if 0 not in axis and partial.shape[0] != x.lshape[0]:
                 lshape_losedim = (partial.shape[0],) + lshape_losedim[1:]
             partial = partial.reshape(lshape_losedim)
 
@@ -241,7 +241,7 @@ def __reduce_op(x, partial_op, reduction_op, **kwargs):
 
     # if reduction_op is a Boolean operation, then resulting tensor is bool
     boolean_ops = [MPI.LAND, MPI.LOR, MPI.BAND, MPI.BOR]
-    tensor_type = bool if reduction_op in boolean_ops else partial[0].dtype
+    tensor_type = bool if reduction_op in boolean_ops else partial.dtype
 
     if out is not None:
         out._DNDarray__array = partial