Hi, thanks for the repo!
I wants to train the network, so I just call run_me.sh without any change. (but with pytorch 0.4.1)
but the process is so slow (and the gpu load is very very low), and the loss seems not changing much...
the losses are not decreasing, and the test results are worse.
So I would like to ask if the training process looks ok ?
below are part of training and validation logs
for the epoch -1
train_AffNet_test_on_graffity.py:250: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad():
instead.
var_image = torch.autograd.Variable(torch.from_numpy(img.astype(np.float32)), volatile = True)
train_AffNet_test_on_graffity.py:250: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad():
instead.
var_image = torch.autograd.Variable(torch.from_numpy(img.astype(np.float32)), volatile = True)
0.641245126724 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.101545810699
pe_time 0.0597500801086
0.166574954987 affine shape iters
0.0878648757935 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0334780216217
pe_time 0.0607059001923
0.108034133911 affine shape iters
Test epoch -1
Test on graf1-6, 217 tentatives 11 true matches 0.050 inl.ratio
Now native ori
0.066300868988 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0342180728912
pe_time 0.0577509403229
0.11149096489 affine shape iters
0.101871013641 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0336909294128
pe_time 0.0553169250488
0.103847026825 affine shape iters
Test epoch -1
Test on ori graf1-6, 147 tentatives 10 true matches 0.068 inl.ratio
for the epoch 0
Train Epoch: 0 [9984000/10000000 (100%)] Loss: 0.9201, 1.5074,0.9073: : 9760it [32:02:26, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9760it [32:02:38, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9761it [32:02:38, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9762it [32:02:49, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9763it [32:03:01, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9764it [32:03:12, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9765it [32:03:24, 11.82s/it]
Train Epoch: 0 [9994240/10000000 (100%)] Loss: 0.9484, 1.5387,0.9369: : 9766it [32:03:32, 11.82s/it]
train_AffNet_test_on_graffity.py:250: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad():
instead.
var_image = torch.autograd.Variable(torch.from_numpy(img.astype(np.float32)), volatile = True)
train_AffNet_test_on_graffity.py:250: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad():
instead.
var_image = torch.autograd.Variable(torch.from_numpy(img.astype(np.float32)), volatile = True)
0.0655670166016 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0328919887543
pe_time 0.0553648471832
0.103418111801 affine shape iters
0.0645890235901 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0329079627991
pe_time 0.0524799823761
0.100947141647 affine shape iters
Test epoch 0
Test on graf1-6, 183 tentatives 13 true matches 0.071 inl.ratio
Now native ori
0.0709731578827 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.033175945282
pe_time 0.0535531044006
0.103495836258 affine shape iters
0.100589036942 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0331048965454
pe_time 0.0523760318756
0.100074052811 affine shape iters
Test epoch 0
Test on ori graf1-6, 155 tentatives 9 true matches 0.058 inl.ratio
for the epoch 1
Train Epoch: 1 [9984000/10000000 (100%)] Loss: 0.9505, 2.0144,0.9437: : 9759it [33:31:50, 12.37s/it]
Train Epoch: 1 [9984000/10000000 (100%)] Loss: 0.9505, 2.0144,0.9437: : 9760it [33:32:02, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9760it [33:32:14, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9761it [33:32:14, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9762it [33:32:26, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9763it [33:32:39, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9764it [33:32:51, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9765it [33:33:03, 12.37s/it]
Train Epoch: 1 [9994240/10000000 (100%)] Loss: 0.9703, 1.9384,0.9606: : 9766it [33:33:11, 12.37s/it]
train_AffNet_test_on_graffity.py:250: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad():
instead.
var_image = torch.autograd.Variable(torch.from_numpy(img.astype(np.float32)), volatile = True)
train_AffNet_test_on_graffity.py:250: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad():
instead.
var_image = torch.autograd.Variable(torch.from_numpy(img.astype(np.float32)), volatile = True)
0.0826170444489 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0436849594116
pe_time 0.0609710216522
0.110808134079 affine shape iters
0.0830068588257 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0333650112152
pe_time 0.054986000061
0.103302001953 affine shape iters
Test epoch 1
Test on graf1-6, 165 tentatives 6 true matches 0.036 inl.ratio
Now native ori
0.066458940506 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0339682102203
pe_time 0.0546021461487
0.103893041611 affine shape iters
0.104158878326 detection multiscale
/media/iouiwc/0596f94c-b314-4162-80b4-79b3a602c9a2/iouiwc/github/affnet/SparseImgRepresenter.py:151: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number
if (num_features > 0) and (num_survived.data[0] > num_features):
affnet_time 0.0339379310608
pe_time 0.0541059970856
0.104035139084 affine shape iters
/home/iouiwc/anaconda2/envs/pytorch/lib/python2.7/site-packages/matplotlib/pyplot.py:537: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure
) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam figure.max_open_warning
).
max_open_warning, RuntimeWarning)
Test epoch 1
Test on ori graf1-6, 148 tentatives 9 true matches 0.060 inl.ratio