libnpy | C++ library for reading and writing of numpy 's .npy files | File Utils library

by llohse C++ Version: v0.1.0 License: MIT

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kandi X-RAY | libnpy Summary

libnpy is a C++ library typically used in Utilities, File Utils, Numpy applications. libnpy has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

libnpy is a simple C++ library for reading and writing of numpy's .npy files. Refer to format.py for a detailed description of the .npy format. This libraries primary purpose is writing numerical data easily and efficiently into the .npy format. It also allows reading .npy files, although only a very limited subset of data types are supported.

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libnpy has a low active ecosystem.

It has 238 star(s) with 60 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 9 have been closed. On average issues are closed in 38 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of libnpy is v0.1.0

Quality

libnpy has 0 bugs and 0 code smells.

Security

libnpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

libnpy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

libnpy is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

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libnpy releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

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Community Discussions

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CSharp: Failed to read LARGE .npy file. Exception is "NumSharp.dll Arithmetic operation resulted in an overflow."

QUESTION

CSharp: Failed to read LARGE .npy file. Exception is "NumSharp.dll Arithmetic operation resulted in an overflow."

Asked 2021-Dec-07 at 20:50

I am trying to read a large .npy file in CSharp. In order to do that i am trying to use the NumSharp nuget.

The file is 7GB jagged float array (float[][]). It has ~1 million vectors, each vector is a 960 dimension.

Note: To be more specific the data I use is the GIST from the following link Approximate Nearest Neighbors Large datasets.

The following is the method I use to load the data but it failes with an exception:

...

ANSWER

Answered 2021-Dec-07 at 20:50

The issue is that the NumSharp data-structure is a heavy RAM consumer and it seems to be the CSharp GC is not aware of what NumSharp is allocating so it reaches the RAM limit very fast.

So, In order to overcome this, I split the input npy file so that every part should not consume more than max memory allocation allowed in C# (2147483591). In my case i split into 5 different files (200k vectors each).

python part to split the large .npy file:

Source https://stackoverflow.com/questions/69920737

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Only scalar numeric data types are supported. There is no natural way to represent more complex objects and parsing the header becomes tremendously more complex. Supported types:.

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