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This algo performs a fairly simple, probably slow, inplace convolution over n-dimensional input. While cleaning up the tests, I ran into issues where trait impls aren't implemented on generic types, which is desired to combat code duplication, so I've fixed that. While Cuda is limited to f32 && f64, this algo can run over any type that implements (mainly) Add and Mul.

Note that this PR depends on autumnai/rust-cudnn#23, so accept that one first.

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GitCop commented Apr 12, 2016

There were the following issues with your Pull Request

  • Commit: 19df0f2
    • Commits must be in the following format: %{type}/%{scope}: %{description}
  • Commit: 2d2d88f
    • Commits must be in the following format: %{type}/%{scope}: %{description}
  • Commit: e946083
    • Commits must be in the following format: %{type}/%{scope}: %{description}

Guidelines are available at https://github.com/autumnai/collenchyma-nn/blob/master/CONTRIBUTING.md#git-commit-guidelines


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@DiamondLovesYou
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It's late here, so I'll fix the gitcop issues tomorrow.

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GitCop commented Apr 14, 2016

There were the following issues with your Pull Request

  • Commit: fe0258b
    • Your commit message body contains a line that is longer than 100 characters

Guidelines are available at https://github.com/autumnai/collenchyma-nn/blob/master/CONTRIBUTING.md#git-commit-guidelines


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…da backend

This allows the tests/downstream crates to be generic. For Cuda, this doesn't
expand the types allowed, so only `f32` and `f64` are allowed (just as before).
…the native

backend

This algo needs to allocate a few index vectors, however it requires no additional space.
@DiamondLovesYou
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I've fixed the gitcop issues.

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3 participants