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Implement BatchNormalization2d Layer #145
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Hey @colepoirier, that's awesome! The process is a bit tedious, especially the First there is Next layer is then to make it safe, catch any invalid preconditions, in most cases this is just mapping the input arguments, but now the function call is safe. We can also add input checks based on the documentation of valid inputs and outputs, but usually the C function does this already so there is no need to. At this point there are safe rust This is now the API that i.e.
One is defining a abstract configuration that works across all backends, so it should not contain any backend specifics. The final step to enable a new layer type, is to add it to the Feel free to ping me on https://gitter.im/spearow/juice or here, looking forward to your first PR! |
Thank you so much for this through guide and explanation! I plan on starting my attempt today and will ping you on gitter if (when) I get stuck :) |
Hi @drahnr,
I'd like to take a crack at implementing the BatchNormalization2d layer in juice.
Referring back to #10 you outlined that adding new cuDNN layers to juice is a 4 step task:
This is a 4 step task:
I am unfortunately having trouble deciphering how you went about turning the
unsafe extern "C"
version of a function likesigmoid_forward
into the safe version that now exists in rcudnn. Which I see is the basis for adding it to coaster-nn, then juice.Can you help me by outlining exactly how you want contributions like this to be carried out in the codebase?
Thanks very much for your help!
Cole
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