diff --git a/mindspore/nn/loss/loss.py b/mindspore/nn/loss/loss.py
index bbf0adfe61f..7bc395019e7 100644
--- a/mindspore/nn/loss/loss.py
+++ b/mindspore/nn/loss/loss.py
@@ -76,8 +76,8 @@ class LossBase(Cell):
 
         Args:
             weights (Union[float, Tensor]): Optional `Tensor` whose rank is either 0, or the same rank as inputs,
-            and must be broadcastable to inputs (i.e., all dimensions must be either `1`,
-            or the same as the corresponding inputs dimension).
+                and must be broadcastable to inputs (i.e., all dimensions must be either `1`,
+                or the same as the corresponding inputs dimension).
         """
         input_dtype = x.dtype
         x = self.cast(x, mstype.float32)
@@ -1282,10 +1282,10 @@ class FocalLoss(LossBase):
                 convert_weight = self.squeeze(convert_weight)
             log_probability = log_probability * convert_weight
 
-        weight = F.pows(-probability + 1.0, self.gamma)
+        weight = F.pows(-1 * probability + 1.0, self.gamma)
         if target.shape[1] == 1:
-            loss = (-weight * log_probability).mean(axis=1)
+            loss = (-1 * weight * log_probability).mean(axis=1)
         else:
-            loss = (-weight * targets * log_probability).mean(axis=-1)
+            loss = (-1 * weight * targets * log_probability).mean(axis=-1)
 
         return self.get_loss(loss)