dinglinhe
4 years ago
1 changed files with 4 additions and 3 deletions
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+ 4
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mindspore/ops/operations/math_ops.py
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| @@ -2237,7 +2237,7 @@ class MulNoNan(_MathBinaryOp): | |||||
| When the inputs are one tensor and one scalar, the scalar could only be a constant. | When the inputs are one tensor and one scalar, the scalar could only be a constant. | ||||
| Note: | Note: | ||||
| The shapes of `input_x` and `input_y` should be same or can be broadcasted. | |||||
| The shapes of `input_x` and `input_y` should be the same or can be broadcasted. | |||||
| Inputs: | Inputs: | ||||
| - **input_x** (Union[Tensor]) - The first input is a tensor whose data type is one of | - **input_x** (Union[Tensor]) - The first input is a tensor whose data type is one of | ||||
| @@ -2246,8 +2246,9 @@ class MulNoNan(_MathBinaryOp): | |||||
| flota16, float32, int32, int64 currently or scalar. | flota16, float32, int32, int64 currently or scalar. | ||||
| Outputs: | Outputs: | ||||
| Tensor, the shape is same to the shape after broadcasting, | |||||
| the data type is the number with higher precision or higher digits in the two inputs. | |||||
| Tensor, the shape is the same as the shape after broadcasting, | |||||
| and the data type is the one with higher precision among the two inputs. | |||||
| Supported Platforms: | Supported Platforms: | ||||
| ``Ascend`` | ``Ascend`` | ||||