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Pytorch Tutorial 5 - MNIST classification - Jupyter and Markdown #91

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merged 8 commits into from
Oct 21, 2021

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@Adamage Adamage commented Oct 5, 2021

Summary

I split all the functions used in the __main__ because the main program and argument parsing have been removed.

Now the structure is linear and follows naturally from what has to be done - datasets loading, training, evaluating.

Added descriptions to steps and links to more documentation.

Changed a bit how TDQM is used.

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Adamage commented Oct 5, 2021

Closing #66

@Adamage Adamage self-assigned this Oct 5, 2021
@Adamage Adamage changed the title Pytorch Tutorial 5 - MNIST classification Pytorch Tutorial 5 - MNIST classification - Jupyter and Markdown Oct 5, 2021
@plutasnyy plutasnyy linked an issue Oct 6, 2021 that may be closed by this pull request
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I think you got the wrong folder, tutorial 5 is in tutorials/simple_applications/pytorch/mnist/ ;)

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Overall nice to read ;)

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Adamage commented Oct 14, 2021

@LRVerkin @arbfay I pushed the fixes please check the updated descriptions, new links, removed softmax layer.

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Adamage commented Oct 18, 2021

TODO to self:

  • use AnchorMode to calculate accuracy and loss better (or allow a switch to enable this or not - poptorch.AnchorMode.All or poptorch.AnchorMode.Sum

…e behavior of training statistics like previewing losses and accuracy
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Nice addition with the anchor stuff

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Adamage commented Oct 19, 2021

@dirkbrink @LRVerkin Thank you guys for the comments. I pushed changes addressing those requests, please check

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LGTM assuming Louise is also happy

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LGTM as well

@Adamage Adamage merged commit c7f7558 into main Oct 21, 2021
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Tutorial 5 - PyTorch Mnist
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