FluxML/Flux.jl

Does Flux support N-dimensional convolutions, where N>3?

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#451 opened on Oct 22, 2018

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 (20 comments) (0 reactions) (0 assignees)Julia (619 forks)batch import
enhancementhelp wanted

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Description

While this works:

Conv((1,1,1), 1=>1)(rand(1,1,1,1,1)) #3D convolution

This throws an error:

Conv((1,1,1,1), 1=>1)(rand(1,1,1,1,1,1)) #4D convolution
#ERROR: MethodError: no method matching conv!(::Array{Float64,6}, ::Array{Float64,6}, ::Array{Float64,6}; pad=(0, 0, 0, 0), stride=(1, 1, 1, 1), dilation=(1, 1, 1, 1))

I'm running Julia 0.7 and:

[587475ba] Flux v0.6.7+ #master (https://github.com/FluxML/Flux.jl.git)
[872c559c] NNlib v0.4.2+ #master (https://github.com/FluxML/NNlib.jl.git)

Contributor guide

Research direction
Investigate the NNlib convolution implementation and extend it to support arbitrary dimensions. Modify Flux's Conv layer to handle higher dimensional inputs.
Tech stack
None
Domain
machine learning
Issue type
Feature
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3
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Half day
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Clear
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30