From ff51d0a8d0f12771d05ea521389f8645a76f7d94 Mon Sep 17 00:00:00 2001 From: wangshuide2020 Date: Fri, 9 Apr 2021 19:45:07 +0800 Subject: [PATCH] update the description of input data type of mulnonan. --- mindspore/ops/operations/array_ops.py | 8 +++----- mindspore/ops/operations/math_ops.py | 6 ++++-- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py index f379ac50ee..df783f810f 100644 --- a/mindspore/ops/operations/array_ops.py +++ b/mindspore/ops/operations/array_ops.py @@ -2731,14 +2731,12 @@ 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`. diff --git a/mindspore/ops/operations/math_ops.py b/mindspore/ops/operations/math_ops.py index d51d8d61cd..3ee6b970f2 100644 --- a/mindspore/ops/operations/math_ops.py +++ b/mindspore/ops/operations/math_ops.py @@ -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,