!7915 update the indexes process to support negtive int

Merge pull request !7915 from yepei6/master_augassign

mindspore/ops/composite/multitype_ops/_compile_utils.py

@@ -59,13 +59,15 @@ def _generate_indices_from_tuple_of_tensor(data, tuple_index, op_name):
 
 def _generate_indices_from_tuple_of_mixed_tensors(data, tuple_index, op_name):
     """Generate an indices tensor from a tuple that contains slice, int, ellipsis, tensor."""
+    data_shape = F.shape(data)
     indexes_types = hyper_map(F.typeof, tuple_index)
     int_positions = const_utils.get_pos_of_int_index(indexes_types)
     tuple_index_new = ()
     tuple_len = len(tuple_index)
     for i in range(tuple_len):
         if i in int_positions:
-            tuple_index_new += (F.scalar_to_tensor(tuple_index[i], mstype.int32),)
+            tuple_index_new += (F.scalar_to_tensor(tuple_index[i] if tuple_index[i] >= 0 else tuple_index[i] + \
+                data_shape[i], mstype.int32),)
         else:
             tuple_index_new += (tuple_index[i],)
     indexes_types = hyper_map(F.typeof, tuple_index_new)
@@ -77,7 +79,6 @@ def _generate_indices_from_tuple_of_mixed_tensors(data, tuple_index, op_name):
         tensor_indexes.append(tuple_index_new[i])
     for j in slice_positions:
         slice_indexes.append(tuple_index_new[j])
-    data_shape = F.shape(data)
     tensor_indexes_shapes = hyper_map(F.shape, tensor_indexes)
     tensor_indexes_dtypes = hyper_map(F.dtype, tensor_indexes)
     broadcast_shape, final_shape, indexes_shapes_info, ellipsis_occupied_dims = \