//目录

nd.array.where

http://mxnet.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.where

Return the elements, either from x or y, depending on the condition.

Given three ndarrays, condition, x, and y, return an ndarray with the elements from x or y, depending on the elements from condition are true or false. x and y must have the same shape. If condition has the same shape as x, each element in the output array is from x if the corresponding element in the condition is true, and from y if false.

If condition does not have the same shape as x, it must be a 1D array whose size is the same as x’s first dimension size. Each row of the output array is from x’s row if the corresponding element from condition is true, and from y’s row if false.

Note that all non-zero values are interpreted as True in condition.

复制代码
x = [[1, 2], [3, 4]]
y = [[5, 6], [7, 8]]
cond = [[0, 1], [-1, 0]]

where(cond, x, y) = [[5, 2], [3, 8]]

csr_cond = cast_storage(cond, 'csr')

where(csr_cond, x, y) = [[5, 2], [3, 8]]
复制代码

X,Y必须同样形状,然后条件可以为同样形状,也可以是一维的;条件为0,才为Y,否则正数,负数都为X

复制代码
from mxnet import nd

ious = nd.array([[0.1,0.3,0.3],[0.9,0.4,0.01],[0,0.55,2],[0.56,0.77,3],[0.9,0.73,4]])
print(ious)

label = [0. ,1., 1.]
print(label)

flag = nd.ones_like(ious)

y = nd.full(ious.shape,0.5)

for i, hard in enumerate(label):
    if hard == 1.0:
        flag[:,i] = ious[:,i] < 0.7
print(flag)

ious = nd.where(flag,ious,y)
print(ious)
复制代码

 

 

 

 

 

posted @   小草的大树梦  阅读(757)  评论(0编辑  收藏  举报
编辑推荐:
· 10年+ .NET Coder 心语,封装的思维:从隐藏、稳定开始理解其本质意义
· .NET Core 中如何实现缓存的预热?
· 从 HTTP 原因短语缺失研究 HTTP/2 和 HTTP/3 的设计差异
· AI与.NET技术实操系列:向量存储与相似性搜索在 .NET 中的实现
· 基于Microsoft.Extensions.AI核心库实现RAG应用
阅读排行:
· 10年+ .NET Coder 心语 ── 封装的思维:从隐藏、稳定开始理解其本质意义
· 地球OL攻略 —— 某应届生求职总结
· 提示词工程——AI应用必不可少的技术
· Open-Sora 2.0 重磅开源!
· 周边上新:园子的第一款马克杯温暖上架
点击右上角即可分享
微信分享提示