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Thanks for your interest in the project and GSoC application we submit !
I think string encoding into numbers is a good approach. Currently, in ignite we provide a helper broadcast and all_gather methods to work on strings: |
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Hello there, |
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Hello there,
I am highly interested in working on the metrics module of this project and have started reading through the code base. I am a final year student in computer science.
I have been doing research work in Image classification and data noise reduction for over a year. Currently, I am doing a thesis on Text Summarization and NLP. So I am fairly familiar with ROUGE, BLEU, METEOR and others.
I am also reading up on distributed implementation for the same. Any good resource other than the pytorch documentation that might help?
I am facing issue with string operations. Since pytorch does not have a tensor representation for list of strings or similar, the step of counting common strings(n-grams) does not seem to have a parallel alternative, unless each character is encoded using corresponding ASCII value as mentioned here.
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