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Merged
glenn-jocher merged 3 commits into from
Jul 31, 2022
Merged

Update ci-testing.yml streamlined tests #8809

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66e84db
Update ci-testing.yml streamlined tests
glenn-jocher Jul 31, 2022
80dcb4f
Update ci-testing.yml
glenn-jocher Jul 31, 2022
92404d9
Update ci-testing.yml
glenn-jocher Jul 31, 2022
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37 changes: 16 additions & 21 deletions .github/workflows/ci-testing.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -95,27 +95,22 @@ jobs:
shell: bash
run: |
# export PYTHONPATH="$PWD" # to run '$ python *.py' files in subdirectories
d=cpu # device
model=${{ matrix.model }}
best=runs/train/exp/weights/best.pt
# Train
python train.py --img 64 --batch 32 --weights $model.pt --cfg $model.yaml --epochs 1 --device $d
# Val
python val.py --img 64 --batch 32 --weights $model.pt --device $d
python val.py --img 64 --batch 32 --weights $best --device $d
# Detect
python detect.py --weights $model.pt --device $d
python detect.py --weights $best --device $d
python hubconf.py --model $model # hub
# Export
# python models/tf.py --weights $model.pt # build TF model
python models/yolo.py --cfg $model.yaml # build PyTorch model
python export.py --weights $model.pt --img 64 --include torchscript # export
# Python
m=${{ matrix.model }} # official weights
b=runs/train/exp/weights/best # best.pt checkpoint
python train.py --imgsz 64 --batch 32 --weights $m.pt --cfg $m.yaml --epochs 1 --device cpu # train
for d in cpu; do # devices
for w in $m $b; do # weights
python val.py --imgsz 64 --batch 32 --weights $w.pt --device $d # val
python detect.py --imgsz 64 --weights $w.pt --device $d # detect
done
done
python hubconf.py --model $m # hub
# python models/tf.py --weights $m.pt # build TF model
python models/yolo.py --cfg $m.yaml # build PyTorch model
python export.py --weights $m.pt --img 64 --include torchscript # export
python - <<EOF
import torch
model = torch.hub.load('.', 'custom', path='$model', source='local')
print(model('data/images/bus.jpg'))
model = torch.hub.load('.', 'custom', path='$best', source='local')
print(model('data/images/bus.jpg'))
for path in '$m', '$b':
model = torch.hub.load('.', 'custom', path=path, source='local')
print(model('data/images/bus.jpg'))
EOF