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@fmassa fmassa commented Mar 27, 2019

This PR introduces the foundations for reference training/evaluation scripts for torchvision.

The idea is that all pre-trained models will have corresponding training scripts / command-line arguments, so that reproducing a trained model should be straightforward.

This is not at its final version. I'll be merging this soon, and after adding segmentation and detection training/evaluation scripts, a lot of it will be refactored and included inside torchvision.

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reviewed the train script. didn't review classification/utills.py



def setup_for_distributed(is_master):
"""
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printing override seems fine, but torch.save override seems pretty sketchy. Maybe consider having a utils.save_on_master that you use, rather than monkey-patching torch.save

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sounds good.

This is a fundamental feature for distributed training, so it's better to have it right.

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codecov-io commented Mar 27, 2019

Codecov Report

Merging #819 into master will not change coverage.
The diff coverage is n/a.

Impacted file tree graph

@@           Coverage Diff           @@
##           master     #819   +/-   ##
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  Coverage   51.58%   51.58%           
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  Files          34       34           
  Lines        3342     3342           
  Branches      536      536           
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  Hits         1724     1724           
  Misses       1486     1486           
  Partials      132      132

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@fmassa fmassa merged commit 27ff89f into pytorch:master Mar 28, 2019
@fmassa fmassa deleted the classification-v0 branch March 28, 2019 13:37
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3 participants