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![Pytorch quizz! You have a 1d long tensor containing contiguous increasing blocks of ids
E.g. [ 0, 0, 1, 1, 1, 2, 3, 3, 3, 3 ]
how would you create the tensor of per-block reversed indexes?
E.g. here [ 1, 0, 4, 3, 2, 5, 9, 8, 7, 6 ] ?
I have a solution in 228 chars.](/_next/image?url=https%3A%2F%2Fpbs.twimg.com%2Fprofile_images%2F1741919776773902336%2FpXUEFYUA_400x400.jpg&w=3840&q=75 "Pytorch quizz! You have a 1d long tensor containing contiguous increasing blocks of ids
E.g. [ 0, 0, 1, 1, 1, 2, 3, 3, 3, 3 ]
how would you create the tensor of per-block reversed indexes?
E.g. here [ 1, 0, 4, 3, 2, 5, 9, 8, 7, 6 ] ?
I have a solution in 228 chars.")
Pytorch quizz! You have a 1d long tensor containing contiguous increasing blocks of ids E.g. [ 0, 0, 1, 1, 1, 2, 3, 3, 3, 3 ] how would you create the tensor of per-block reversed indexes? E.g. here [ 1, 0, 4, 3, 2, 5, 9, 8, 7, 6 ] ? I have a solution in 228 chars.
Research Scientist @meta (FAIR), Prof. @Unige_en, co-founder @nc_shape. I like reality.
RT @elonmusk: Grok can search 𝕏 and analyze or summarize anything
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One of the best parts of building a startup is your job as a founder will change every week without notice.
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My @X followers + @grok are literally planning our trip now, very nice
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And then you wake up to 10000 "as unknown as any"
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