《Python》np.fromfile内存限制

https://stackoverflow.com/questions/54545228/is-there-a-memory-limit-on-np-fromfile-method

由于安装32bit python导致的问题

解决方案:安装64bit python

Is there a memory limit on np.fromfile() method?

1

I am trying to read a big file into array with the help of np.fromfile(), however, after certain number of bytes it gives MemoryError.

with open(filename,'r') as file:
    data = np.fromfile(file, dtype=np.uint16, count=2048*2048*63)
    data = data.reshape(63, 2048, 2048)

It works fine with 2048*2048*63 however not working with 2048*2048*64. How to debug this? I am wondering what is the bottleneck here?

Edit: I am running on Windows 10, RAM 256GB, it is a standalone script, 64bit Python.

Edit2: I followed the advices on comments, now getting the error at 128*2048*2048, works fine with 127*2048*2048.

  •  
    How much RAM do you have and what is the bittage of your system? – Mad Physicist Feb 6 '19 at 0:52
  • 1
    How much RAM do you have? How large is your swap/pagefile? Is this standalone code, or part of a larger program with other large allocations? Are you running a 32 or 64 bit version of Python? We need a lot more details to provide useful answers. – ShadowRanger Feb 6 '19 at 0:54
  •  
    256GB RAM, but python cannot handle that? – CanCode Feb 6 '19 at 0:54
  • 2
    2048 * 2048 * 2 * 64 = 0.5 GiB. Shouldn't be an issue. Unless you do it a few thousand times – Mad Physicist Feb 6 '19 at 0:55 
  • 1
    For the record, on 64 bit CPython 3.7.1 running on Ubuntu bash on Windows, I can't reproduce (and I have far less RAM than you, only 12 GB). It loads and reshapes just fine (if I change it to data.reshape from np.reshape). While it's unlikely to matter, it would be useful to know what OS and specific Python version you're running. – ShadowRanger Feb 6 '19 at 0:59 
1
 

Despite what you believe, you've installed a 32 bit version of Python on your 64 bit operating system, which means virtual address space is limited to only have 2 GB in user mode, and attempts to allocate contiguous blocks of a GB or more can easily fail due to address space fragmentation.

The giveaway is your sys.maxsize, which is just the largest value representable by a C ssize_t in your build of Python. 2147483647 corresponds to 2**31 - 1, which is the expected value on 32 bit Python. A 64 bit build would report 9223372036854775807 (2**63 - 1).

Uninstall the 32 bit version of Python and download/install a 64 bit version (link is to 3.7.2 download page) (look for the installer to be labelled as x86-64, not x86; the file name would include amd64). Annoyingly, the main page for downloading Python defaults to offering the 32 bit version for Windows, so you have to scroll down to the links to specific version download pages, click on the latest, then scroll down to the complete list by OS and bittedness and choose appropriately.

posted @   清风oo  阅读(446)  评论(0编辑  收藏  举报
编辑推荐:
· 开发者必知的日志记录最佳实践
· SQL Server 2025 AI相关能力初探
· Linux系列:如何用 C#调用 C方法造成内存泄露
· AI与.NET技术实操系列(二):开始使用ML.NET
· 记一次.NET内存居高不下排查解决与启示
阅读排行:
· Manus重磅发布:全球首款通用AI代理技术深度解析与实战指南
· 被坑几百块钱后,我竟然真的恢复了删除的微信聊天记录!
· 没有Manus邀请码?试试免邀请码的MGX或者开源的OpenManus吧
· 园子的第一款AI主题卫衣上架——"HELLO! HOW CAN I ASSIST YOU TODAY
· 【自荐】一款简洁、开源的在线白板工具 Drawnix
历史上的今天:
2018-07-10 第7章 类
点击右上角即可分享
微信分享提示