ValueError: Layer #232 (named "fpn_cells/cell_0/fnode0/add") expects 0 weight(s) , but the saved weights have 1 element(s)
ValueError: Layer #232 (named "fpn_cells/cell_0/fnode0/add") expects 0 weight(s) , but the saved weights have 1 element(s)
我一直在尝试使用
训练数据集
python train.py --snapshot efficientdet-d0.h5 --phi 0 --gpu 0 --random-transform --compute-val-loss --freeze-backbone --batch-size 4 --steps 100 coco C:/Users/mustafa/Downloads/deneme.v1-1.coco/datasets/coco
而且我看到了这个错误。
Traceback (most recent call last):
File "train.py", line 381, in
main()
File "train.py", line 333, in main
model.load_weights(args.snapshot, by_name=True)
File "C:\Users\mustafa\anaconda3\lib\site-packages\tensorflow\python\keras\eng
ine\training.py", line 271, in load_weights
return super(Model, self).load_weights(filepath, by_name, skip_mismatch)
File "C:\Users\mustafa\anaconda3\lib\site-packages\tensorflow\python\keras\eng
ine\network.py", line 1276, in load_weights
f, self.layers, skip_mismatch=skip_mismatch)
File "C:\Users\mustafa\anaconda3\lib\site-packages\tensorflow\python\keras\sav
ing\hdf5_format.py", line 769, in load_weights_from_hdf5_group_by_name
str(len(weight_values)) + ' element(s).')
ValueError: Layer #232 (named "fpn_cells/cell_0/fnode0/add") expects 0 weight(s)
, but the saved weights have 1 element(s).
我试过设置
weighted_bifpn = False
和
os.environ['CUDA_VISIBLE_DEVICES'] = ''
但是他们没有用。
我的 GPU 不支持 CUDA。
您应该在命令中包含 --weighted-bifpn 选项,如下所示。
python train.py --snapshot efficientdet-d0.h5 --phi 0 --gpu 0 --weighted-bifpn --random-transform --compute-val-loss --freeze-backbone --batch-size 4 --steps 100 coco C:/Users/mustafa/Downloads/deneme.v1-1.coco/datasets/coco
您使用的快照可能已经用 weighted-bifpn 训练过。所以当你开始训练时,它需要这个选项。
我一直在尝试使用
训练数据集python train.py --snapshot efficientdet-d0.h5 --phi 0 --gpu 0 --random-transform --compute-val-loss --freeze-backbone --batch-size 4 --steps 100 coco C:/Users/mustafa/Downloads/deneme.v1-1.coco/datasets/coco
而且我看到了这个错误。
Traceback (most recent call last):
File "train.py", line 381, in
main()
File "train.py", line 333, in main
model.load_weights(args.snapshot, by_name=True)
File "C:\Users\mustafa\anaconda3\lib\site-packages\tensorflow\python\keras\eng
ine\training.py", line 271, in load_weights
return super(Model, self).load_weights(filepath, by_name, skip_mismatch)
File "C:\Users\mustafa\anaconda3\lib\site-packages\tensorflow\python\keras\eng
ine\network.py", line 1276, in load_weights
f, self.layers, skip_mismatch=skip_mismatch)
File "C:\Users\mustafa\anaconda3\lib\site-packages\tensorflow\python\keras\sav
ing\hdf5_format.py", line 769, in load_weights_from_hdf5_group_by_name
str(len(weight_values)) + ' element(s).')
ValueError: Layer #232 (named "fpn_cells/cell_0/fnode0/add") expects 0 weight(s)
, but the saved weights have 1 element(s).
我试过设置
weighted_bifpn = False
和
os.environ['CUDA_VISIBLE_DEVICES'] = ''
但是他们没有用。 我的 GPU 不支持 CUDA。
您应该在命令中包含 --weighted-bifpn 选项,如下所示。
python train.py --snapshot efficientdet-d0.h5 --phi 0 --gpu 0 --weighted-bifpn --random-transform --compute-val-loss --freeze-backbone --batch-size 4 --steps 100 coco C:/Users/mustafa/Downloads/deneme.v1-1.coco/datasets/coco
您使用的快照可能已经用 weighted-bifpn 训练过。所以当你开始训练时,它需要这个选项。