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Global code reformat and optimize imports

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This commit is contained in:
Glenn Jocher 2020-08-22 17:49:27 -07:00
parent 64ff05c499
commit bf34ae007f
5 changed files with 24 additions and 26 deletions
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8
data/get_coco2014.sh
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@ -6,13 +6,13 @@
# Download labels from Google Drive, accepting presented query
filename="coco2014labels.zip"
fileid="1s6-CmF5_SElM28r52P1OUrCcuXZN-SFo"
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" > /dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=`awk '/download/ {print $NF}' ./cookie`&id=${fileid}" -o ${filename}
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" >/dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=$(awk '/download/ {print $NF}' ./cookie)&id=${fileid}" -o ${filename}
rm ./cookie
# Unzip labels
unzip -q ${filename} # for coco.zip
# tar -xzf ${filename} # for coco.tar.gz
unzip -q ${filename} # for coco.zip
# tar -xzf ${filename} # for coco.tar.gz
rm ${filename}
# Download and unzip images

8
data/get_coco2017.sh
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@ -6,13 +6,13 @@
# Download labels from Google Drive, accepting presented query
filename="coco2017labels.zip"
fileid="1cXZR_ckHki6nddOmcysCuuJFM--T-Q6L"
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" > /dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=`awk '/download/ {print $NF}' ./cookie`&id=${fileid}" -o ${filename}
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" >/dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=$(awk '/download/ {print $NF}' ./cookie)&id=${fileid}" -o ${filename}
rm ./cookie
# Unzip labels
unzip -q ${filename} # for coco.zip
# tar -xzf ${filename} # for coco.tar.gz
unzip -q ${filename} # for coco.zip
# tar -xzf ${filename} # for coco.tar.gz
rm ${filename}
# Download and unzip images

28
train.py
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@ -149,15 +149,15 @@ def train(hyp):
elif len(weights) > 0: # darknet format
# possible weights are '*.weights', 'yolov3-tiny.conv.15', 'darknet53.conv.74' etc.
load_darknet_weights(model, weights)
if opt.freeze_layers:
output_layer_indices = [idx - 1 for idx, module in enumerate(model.module_list) if isinstance(module, YOLOLayer)]
freeze_layer_indices = [x for x in range(len(model.module_list)) if
(x not in output_layer_indices) and
(x - 1 not in output_layer_indices)]
for idx in freeze_layer_indices:
for parameter in model.module_list[idx].parameters():
parameter.requires_grad_(False)
if opt.freeze_layers:
output_layer_indices = [idx - 1 for idx, module in enumerate(model.module_list) if isinstance(module, YOLOLayer)]
freeze_layer_indices = [x for x in range(len(model.module_list)) if
(x not in output_layer_indices) and
(x - 1 not in output_layer_indices)]
for idx in freeze_layer_indices:
for parameter in model.module_list[idx].parameters():
parameter.requires_grad_(False)
# Mixed precision training https://github.com/NVIDIA/apex
if mixed_precision:
@ -356,10 +356,10 @@ def train(hyp):
if save:
with open(results_file, 'r') as f: # create checkpoint
ckpt = {'epoch': epoch,
'best_fitness': best_fitness,
'training_results': f.read(),
'model': ema.ema.module.state_dict() if hasattr(model, 'module') else ema.ema.state_dict(),
'optimizer': None if final_epoch else optimizer.state_dict()}
'best_fitness': best_fitness,
'training_results': f.read(),
'model': ema.ema.module.state_dict() if hasattr(model, 'module') else ema.ema.state_dict(),
'optimizer': None if final_epoch else optimizer.state_dict()}
# Save last, best and delete
torch.save(ckpt, last)
@ -409,7 +409,7 @@ if __name__ == '__main__':
parser.add_argument('--device', default='', help='device id (i.e. 0 or 0,1 or cpu)')
parser.add_argument('--adam', action='store_true', help='use adam optimizer')
parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
parser.add_argument('--freeze-layers', action='store_true', help='Freeze non-output layers')
parser.add_argument('--freeze-layers', action='store_true', help='Freeze non-output layers')
opt = parser.parse_args()
opt.weights = last if opt.resume and not opt.weights else opt.weights
check_git_status()

3
utils/evolve.sh
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@ -12,8 +12,7 @@ while true; do
python3 train.py --data coco2014.data --img-size 512 608 --epochs 27 --batch 8 --accum 8 --evolve --weights '' --bucket ult/coco/sppa_512 --device $1 --cfg yolov3-sppa.cfg --multi
done
# coco epoch times --img-size 416 608 --epochs 27 --batch 16 --accum 4
# 36:34 2080ti
# 21:58 V100
# 63:00 T4
# 63:00 T4

3
utils/gcp.sh
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@ -29,8 +29,7 @@ docker kill $(docker ps -a -q --filter ancestor=$t)
sudo -s
t=ultralytics/yolov3:evolve
# docker kill $(docker ps -a -q --filter ancestor=$t)
for i in 0 1 6 7
do
for i in 0 1 6 7; do
docker pull $t && docker run --gpus all -d --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t bash utils/evolve.sh $i
sleep 30
done