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I'd like to know which common file format is more efficient in terms of simplicity and storage space for storing the state of artificial neural network.

I'm not talking about memory storage, but file storage, so the data can be loaded later on.

My first guess would be XML, but having millions of connections and weights would generate huge amount of data. Another thing would be to dump object instances into binary file using some export/serialize functions, but the disadvantage is that the file isn't common and it's language specific.

Are there any common file format standards which can be used for exporting huge artificial neural network into the file to be loaded by another program? If so, which one.

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closed as off-topic by wythagoras, Matthew Graves, baranskistad, Luis, Enamul Hassan Aug 13 '16 at 0:12

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "This question does not appear to be about artificial intelligence, within the scope defined in the help center." – wythagoras, Matthew Graves, baranskistad, Luis, Enamul Hassan
If this question can be reworded to fit the rules in the help center, please edit the question.

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One option is NeuroML, one of the goals of which is:

To facilitate the exchange of complex neuronal models between researchers, allowing for greater transparency and accessibility of models

In general, the matrices associated with large neural network models are likely to be sparse. Hence a 'homebrew' alternative to the above would be to use something like the Matrix Market format.

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In general purpose for this kind of applications, One can use databases such as sqlite, mysql, mssql etc. It simplifies read / write operations, allows for a common language to interact with different databases from different vendors and platforms.

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