For those who run their own AI box, or want to

[slowtalk]

@balnazzar

A full-fledged linux box. You can run fastai/pytorch in a docker NGC container or in a conda environment. In both cases you don’t need to worry about CUDA and cuDNN, for the standard fastai/fastbook installations will take automatically care of them. On one hand, docker would be a bit more preferable for a beginner, since it provides an additional layer of insulation against mistakes. On the other hand, a conda env on the bare metal is more straightforward (and in line with the official installation instructions).

For those that setup on their own Linux box I recently upgraded mine to Ubuntu 22.04.1 and ran into an issue using FileUpload where the error message was FileUpload(): object has no attribute 'data'. I believe this might be due to an updated version of ipywidgets, but am/was unsure.

A workaround I used, tested with lessons 01_intro.ipynb and 02_production.ipynb, replaces any line similar to the following:

img = PILImage.create(uploader.data[0])

with:

img = PILImage.create(uploader.value[0].content.tobytes())

It seems that FileUpload switched from returning data type to a new type called value, which is also reflected in the ipywidgets FileUpload documentation.

I searched the forums and it didn’t seem that anybody else has run into this problem (yet), which may mean it’s a specific problem with my own environment or setup. I used the vanilla pip install fastai command listed on the welcome page of the fast.ai docs page as my setup.