updates
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b52a49cf12
commit
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13
train.py
13
train.py
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@ -22,6 +22,7 @@ def train(
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resume=False,
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resume=False,
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epochs=100,
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epochs=100,
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batch_size=16,
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batch_size=16,
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accumulated_batches=1,
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weights_path='weights',
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weights_path='weights',
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report=False,
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report=False,
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multi_scale=False,
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multi_scale=False,
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@ -153,10 +154,10 @@ def train(
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loss = model(imgs.to(device), targets, batch_report=report, var=var)
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loss = model(imgs.to(device), targets, batch_report=report, var=var)
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loss.backward()
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loss.backward()
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# accumulated_batches = 1 # accumulate gradient for 4 batches before optimizing
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# accumulate gradient for x batches before optimizing
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# if ((i + 1) % accumulated_batches == 0) or (i == len(dataloader) - 1):
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if ((i + 1) % accumulated_batches == 0) or (i == len(dataloader) - 1):
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optimizer.step()
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optimizer.step()
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optimizer.zero_grad()
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optimizer.zero_grad()
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# Running epoch-means of tracked metrics
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# Running epoch-means of tracked metrics
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ui += 1
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ui += 1
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@ -237,6 +238,7 @@ if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument('--epochs', type=int, default=100, help='number of epochs')
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parser.add_argument('--epochs', type=int, default=100, help='number of epochs')
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parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch')
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parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch')
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parser.add_argument('--accumulated-batches', type=int, default=1, help='number of batches before optimizer step')
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parser.add_argument('--data-config', type=str, default='cfg/coco.data', help='path to data config file')
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parser.add_argument('--data-config', type=str, default='cfg/coco.data', help='path to data config file')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path')
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parser.add_argument('--multi-scale', action='store_true', help='random image sizes per batch 320 - 608')
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parser.add_argument('--multi-scale', action='store_true', help='random image sizes per batch 320 - 608')
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@ -244,7 +246,7 @@ if __name__ == '__main__':
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parser.add_argument('--weights-path', type=str, default='weights', help='path to store weights')
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parser.add_argument('--weights-path', type=str, default='weights', help='path to store weights')
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parser.add_argument('--resume', action='store_true', help='resume training flag')
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parser.add_argument('--resume', action='store_true', help='resume training flag')
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parser.add_argument('--report', action='store_true', help='report TP, FP, FN, P and R per batch (slower)')
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parser.add_argument('--report', action='store_true', help='report TP, FP, FN, P and R per batch (slower)')
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parser.add_argument('--freeze', action='store_true', help='freeze darknet53.conv.74 layers for first epoche')
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parser.add_argument('--freeze', action='store_true', help='freeze darknet53.conv.74 layers for first epoch')
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parser.add_argument('--var', type=float, default=0, help='optional test variable')
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parser.add_argument('--var', type=float, default=0, help='optional test variable')
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opt = parser.parse_args()
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opt = parser.parse_args()
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print(opt, end='\n\n')
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print(opt, end='\n\n')
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@ -259,6 +261,7 @@ if __name__ == '__main__':
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resume=opt.resume,
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resume=opt.resume,
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epochs=opt.epochs,
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epochs=opt.epochs,
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batch_size=opt.batch_size,
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batch_size=opt.batch_size,
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accumulated_batches=opt.accumulated_batches,
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weights_path=opt.weights_path,
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weights_path=opt.weights_path,
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report=opt.report,
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report=opt.report,
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multi_scale=opt.multi_scale,
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multi_scale=opt.multi_scale,
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