# Upsampling in Flux.jl

**URL:** <https://discourse.julialang.org/t/upsampling-in-flux-jl/25919>\
**Category:** Machine Learning\
**Tags:** flux\
**Created:** [July 2, 2019, 10:40am UTC](https://discourse.julialang.org/t/upsampling-in-flux-jl/25919 "2019-07-02T10:40:42Z")\
**Posts on this page:** 1\
**Showing post:** 7

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**Author:** ![Alexander-Barth](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alexander-barth/32/3692_2.png) [@Alexander-Barth](https://discourse.julialang.org/u/Alexander-Barth)\
**Post date:** [October 15, 2019, 8:37am UTC](https://discourse.julialang.org/t/upsampling-in-flux-jl/25919/7 "2019-10-15T08:37:52Z")

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Here are the run times for 5 epochs on the same machine:

Flux.jl: 29.8 seconds (smallest run-time out of 3 tests)  
Tensorflow (python): 19.7 seconds

Unfortunately, the run time difference is too large for me, to migrate to Flux.jl. However, if I manage to optimize the Flux.jl model, I will post my updates here.

Flux: 0.9; julia 1.2.0; Tensorflow: 1.12; CuArrays 8e00af6

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