libc10_cuda.so error for installing pyG
After installing PyG, here is the error:
libc10_cuda.so: cannot open shared object file: No such file or directory
Solution
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After installing PyG, here is the error:
libc10_cuda.so: cannot open shared object file: No such file or directory
Solution
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在运行任务时,往linux的同一个文件夹中写入超过500万个文件,导致在硬盘还有空间的情况下,在该文件夹下无法继续写入文件,也无法使用ls、rm等命令。记录处理过程。
Background: physical server, about two years old, 7200-RPM SATA drives connected to a 3Ware RAID card, ext3 FS mounted noatime and data=ordered, not under crazy load, kernel 2.6.18-92.1.22.el5, uptime 545 days. Directory doesn’t contain any subdirectories, just millions of small (~100 byte) files, with some larger (a few KB) ones.
We have a server that has gone a bit cuckoo over the course of the last few months, but we only noticed it the other day when it started being unable to write to a directory due to it containing too many files. Specifically, it started throwing this error in /var/log/messages:
Automatically Sort Data in Google Sheets
Extension -> Apps script
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显示“未能找到金属编译器安装的Xcode。请安装Xcode并运行Xcode.app来接受协议,或确保激活的开发者目录设为当前的Xcode安装(使用xcode-select)
解决方案:
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给定两个稀疏向量,计算它们的点积(数量积)。
实现类 SparseVector:
SparseVector(nums) 以向量 nums 初始化对象。 dotProduct(vec) 计算此向量与 vec 的点积。 稀疏向量 是指绝大多数分量为 0 的向量。你需要 高效 地存储这个向量,并计算两个稀疏向量的点积。
进阶:当其中只有一个向量是稀疏向量时,你该如何解决此问题?
示例 1:
输入:nums1 = [1,0,0,2,3], nums2 = [0,3,0,4,0]
输出:8
解释:v1 = SparseVector(nums1) , v2 = SparseVector(nums2)
v1.dotProduct(v2) = 10 + 03 + 00 + 24 + 3*0 = 8
示例 2:
输入:nums1 = [0,1,0,0,0], nums2 = [0,0,0,0,2]
输出:0
解释:v1 = SparseVector(nums1) , v2 = SparseVector(nums2)
v1.dotProduct(v2) = 00 + 10 + 00 + 00 + 0*2 = 0