create step lr schedule
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6528238953
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208fd77fe4
14
train.py
14
train.py
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@ -6,7 +6,7 @@ from utils.datasets import *
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from utils.utils import *
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parser = argparse.ArgumentParser()
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parser.add_argument('-epochs', type=int, default=160, help='number of epochs')
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parser.add_argument('-epochs', type=int, default=68, help='number of epochs')
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parser.add_argument('-batch_size', type=int, default=12, help='size of each image batch')
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parser.add_argument('-data_config_path', type=str, default='cfg/coco.data', help='data config file path')
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parser.add_argument('-cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path')
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@ -86,7 +86,7 @@ def main(opt):
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optimizer = torch.optim.SGD(model.parameters(), lr=1e-3, momentum=.9, weight_decay=5e-4, nesterov=True)
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# Set scheduler
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# scheduler = torch.optim.lr_scheduler.ExponentialLR(optimizer, gamma=0.99082, last_epoch=start_epoch - 1)
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# scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer, milestones=[54, 61], gamma=0.1)
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modelinfo(model)
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t0, t1 = time.time(), time.time()
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@ -104,8 +104,14 @@ def main(opt):
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# scheduler.step()
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# Update scheduler (manual)
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# for g in optimizer.param_groups:
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# g['lr'] = 1e-3 * (g ** epoch) # 1/10th every [30, 50, 100, 250] epochs using g = [.926, .955, .977, .992]
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if epoch < 54:
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lr = 1e-3
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elif epoch < 61:
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lr = 1e-4
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else:
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lr = 1e-5
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for g in optimizer.param_groups:
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g['lr'] = lr
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ui = -1
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rloss = defaultdict(float) # running loss
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