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Update connections to work with new Transform API #142

merged 4 commits into from Feb 20, 2019


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@drasmuss drasmuss commented Nov 19, 2018

This gets all the tests passing with nengo master. Note that this does not support the new Convolution transforms, it just brings the existing nengo-loihi functionality up-to-date with nengo core. There are still several open PRs related to the nengo-loihi convolution implementation, so I figured I would wait for those to be resolved before trying to apply those changes.

Also note that right now I've done this in a non-backwards-compatible way (i.e. it does not work with nengo 2.8.0). Since nengo-loihi is pretty "in development", requiring the most up-to-date version of Nengo (assuming there is a new nengo release before the next nengo-loihi release) seems reasonable. But we could make it backwards compatible, it just adds a little extra complexity and maintenance burden.


  • improve test coverage
  • update conv example notebook

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drasmuss commented Dec 28, 2018

Rebased this to master, and added support for nengo.Convolution transforms. All the tests are passing, but I'm not confident that that means things are working, as the test coverage is a bit sparse. For example, it looks like a lot of the tests were set up as if they should test different conditions, but then those conditions aren't being tested (e.g. e39c54b#diff-2b5472730de7e72d3c4c167f986643d2R46, e39c54b#diff-2b5472730de7e72d3c4c167f986643d2R285, e39c54b#diff-2b5472730de7e72d3c4c167f986643d2R359, e39c54b#diff-2b5472730de7e72d3c4c167f986643d2R397). But I'm not sure if those un-tested conditions are expected to be working or not. So need @hunse to look it over, since he is most familiar with the convolution code (and might have other examples that could be made into tests).

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hunse commented Feb 1, 2019

  • The xfail tests in should all work on the emulator, and currently they're not. I think it's just syntax changes related to this PR that were never fixed. So a reminder to do that before we merge.

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" layer, conv = conv_layer(layer, 6, conv.output_shape, strides=2)\n",
" layer, conv = conv_layer(layer, 24, conv.output_shape, strides=2)\n",
" layer, conv = conv_layer(layer, 6, conv.output_shape, \n",
" strides=(2, 2))\n",
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It'd be nice to be able to pass an int and have it broadcast like before, since in my experience almost all the time you want the same strides in both directions. I realize that a) this would be a Nengo change and b) it would make it different than kernel_size which needs a tuple (since that specifies the number of dimensions for the convolution). I just wanted to raise the point here.

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Also fix the passthrough logic for non-array transforms.

This is backwards compatibile with Nengo 2.8 transforms,
where we did not have Transform types (all transforms were arrays).
@hunse hunse force-pushed the nengo-update branch 2 times, most recently from 0271a86 to 803dded Compare February 20, 2019 21:46
And update the MNIST example with new syntax and parameter files.

This is not backwards compatible: We do not support the new
convolution code with older Nengo, since much of the supporting code
is in new Nengo. However, this is not a significant regression,
since convolution only worked briefly with old Nengo.
Also separate builds into basic and advanced stages.

This also makes test_learning.test_multiple_pes more robust;
lenthening the runtime seems to make it fail much less often.
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