TastyPancakes/Flux.jl
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make tf model running easier

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This commit is contained in:
Mike J Innes 2017-01-25 18:10:56 +05:30
parent 770b74fe5f
commit 8db503eafa
4 changed files with 6 additions and 3 deletions
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2
src/backend/tensorflow/model.jl
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@ -53,7 +53,7 @@ function runmodel(m::Model, args...)
end end
function (m::Model)(args::Batch...) function (m::Model)(args::Batch...)
runmodel(m, args...) runmodel(m, map(x -> convertel(Float32, x), args)...)
end end
function (m::Model)(args...) function (m::Model)(args...)

2
src/backend/tensorflow/tensorflow.jl
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@ -1,7 +1,7 @@
module TF module TF
using ..Flux, DataFlow, TensorFlow, Juno using ..Flux, DataFlow, TensorFlow, Juno
import Flux: accuracy, rebatch import Flux: accuracy, rebatch, convertel
export tf export tf

3
src/data.jl
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@ -1,5 +1,8 @@
export onehot, onecold, chunk, partition, batches, sequences export onehot, onecold, chunk, partition, batches, sequences
convertel(T::Type, xs::AbstractArray) = map(x->convert(T, x), xs)
convertel{T}(::Type{T}, xs::AbstractArray{T}) = xs
""" """
onehot('b', ['a', 'b', 'c', 'd']) => [false, true, false, false] onehot('b', ['a', 'b', 'c', 'd']) => [false, true, false, false]

2
test/backend.jl
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@ -1,4 +1,4 @@
xs = rand(Float32, 20) xs = rand(20)
d = Affine(20, 10) d = Affine(20, 10)