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update the description of input data type of mulnonan.

This commit is contained in:
wangshuide2020 2021-04-09 19:45:07 +08:00
parent 5b5891bb14
commit c7148c3ab4
2 changed files with 7 additions and 7 deletions
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8
mindspore/ops/operations/array_ops.py
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@ -2754,14 +2754,12 @@ class Select(PrimitiveWithInfer):
Returns the selected elements, either from input :math:`x` or input :math:`y`, depending on the `condition`.
Given a tensor as input, this operation inserts a dimension of 1 at the dimension,
it was invalid when both math: 'x' and math: 'y' are none,
the coordinates are returned as a two-dimensional tensor, where the first dimension (row) represents
the number of true elements and the second dimension (columns) represents the coordinates of the true
elements. Keep in mind that the shape of the output tensor can vary depending
it was invalid when both math: 'x' and math: 'y' are none.
Keep in mind that the shape of the output tensor can vary depending
on how many true values are in the input. Indexes are output in row-first
order.
math:`x` and :math:`y` must have the same shape. If :math:`x` and :math:`y` are
If neither is None, math:`x` and :math:`y` must have the same shape. If :math:`x` and :math:`y` are
scalars, the conditional tensor must be a scalar. If :math:`x` and :math:`y` are
higher-dimensional vectors, the `condition` must be a vector whose size matches the
first dimension of :math:`x`, or must have the same shape as :math:`y`.

6
mindspore/ops/operations/math_ops.py
View File

@ -2249,8 +2249,10 @@ class MulNoNan(_MathBinaryOp):
The shapes of `input_x` and `input_y` should be same or can be broadcasted.
Inputs:
- **input_x** (Union[Tensor]) - The first input is a tensor whose data type is number or scalar.
- **input_y** (Union[Tensor]) - The second input is a tensor whose data type is number or scalar.
- **input_x** (Union[Tensor]) - The first input is a tensor whose data type is one of
flota16, float32, int32, int64 currently or scalar.
- **input_y** (Union[Tensor]) - The second input is a tensor whose data type is one of
flota16, float32, int32, int64 currently or scalar.
Outputs:
Tensor, the shape is same to the shape after broadcasting,