Hi,
am facing following errors while training.
Any help appreciated.
1. For batch size 1 and 2 with cuDNN is installed
F0612 08:31:44.348748 13429 syncedmem.cpp:51] Check failed: error == cudaSuccess (2 vs. 0) out of memory
Check failure stack trace:
Aborted (core dumped)
2. For batch size 4
File "main.py", line 37, in
model.train()
File "/home/user/3dprostrate/VNet/VNet.py", line 163, in train
self.trainThread(dataQueue, solver)
File "/home/user/3dprostrate/VNet/VNet.py", line 80, in trainThread
solver.net.blobs['data'].data[...] = batchData.astype(dtype=np.float32)
ValueError: could not broadcast input array from shape (4,1,128,128,64) into shape (2,1,128,128,64)
Seems like you dont have enough GPU Memory (e.g. type nvidia-smi in your comand line and have a look, for a batch size of 2 you need ~8Gb)
You have to adapt the input data blob in caffe as well to run the Network with a batch size of 4. In your train_noPooling_ResNet_cinque.prototxt line 2 and 5 change the input dim to fit 4 Volumes. However, if you dont have enought memory to run the net with a batchsize of 2 you wont be able to run it with 4.
Hi, am facing following errors while training. Any help appreciated.
1. For batch size 1 and 2 with cuDNN is installed F0612 08:31:44.348748 13429 syncedmem.cpp:51] Check failed: error == cudaSuccess (2 vs. 0) out of memory Check failure stack trace: Aborted (core dumped)
2. For batch size 4 File "main.py", line 37, in
model.train()
File "/home/user/3dprostrate/VNet/VNet.py", line 163, in train
self.trainThread(dataQueue, solver)
File "/home/user/3dprostrate/VNet/VNet.py", line 80, in trainThread
solver.net.blobs['data'].data[...] = batchData.astype(dtype=np.float32)
ValueError: could not broadcast input array from shape (4,1,128,128,64) into shape (2,1,128,128,64)
Thanks in advance -D