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License: Apache License 2.0
pytorch and cifar10
License: Apache License 2.0
In the resnet.py, the following codes should be revised.
if self.downsample is not None:
residual = self.downsample(x)
it should be
if self.downsample is not None:
residual = self.downsample(residual)
While I try to execute the code I get an error, googlenet has no attribute to.
When I only use 10,000 training data, the loss function of the test dataset of each network has been rising instead of falling, which will lead to very serious overfitting.Training accuracy rate is 100%, test accuracy rate is 10%. How can I solve this problem?
I just tried alexnet on cifar and got 69.09% on test set even with cv, although I trained for 100 epochs standard lr for adam (i.e. no mulstistep lr), batch size of 1024 for training and 64 for final test set evaluation.
OS: Ubuntu
pytorch: 1.1.0
cuda: 9.0
cudnn:7.6
GPU: RTX 2080
I got errors below:
runpy.run_path(target, run_name='__main__') File "/usr/lib/python3.6/runpy.py", line 263, in run_path pkg_name=pkg_name, script_name=fname) File "/usr/lib/python3.6/runpy.py", line 96, in _run_module_code mod_name, mod_spec, pkg_name, script_name) File "/usr/lib/python3.6/runpy.py", line 85, in _run_code exec(code, run_globals) File "/home/gaoya/Downloads/pytorch-cifar10-master/main.py", line 155, in <module> main() File "/home/gaoya/Downloads/pytorch-cifar10-master/main.py", line 27, in main solver.run() File "/home/gaoya/Downloads/pytorch-cifar10-master/main.py", line 145, in run train_result = self.train() File "/home/gaoya/Downloads/pytorch-cifar10-master/main.py", line 95, in train output = self.model(data) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 493, in __call__ result = self.forward(*input, **kwargs) File "/home/gaoya/Downloads/pytorch-cifar10-master/models/AlexNet.py", line 38, in forward x = self.features(x) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 493, in __call__ result = self.forward(*input, **kwargs) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/container.py", line 92, in forward input = module(input) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 493, in __call__ result = self.forward(*input, **kwargs) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/conv.py", line 338, in forward self.padding, self.dilation, self.groups) RuntimeError: cuda runtime error (11) : invalid argument at /pytorch/aten/src/THC/THCGeneral.cpp:383
I trained the "Alexnet" in another implementation and got very high accuracy, around 85%.
The main differences between the two implementations are,
Is this high accuracy possible?
hi!
I install pytorch 1.0 , when I run main.py
, it says:
No module named 'torchvision'
.
if I conda install torchvison
, it seems to install pytorch 0.4.0. Does pytorch1.0 not contain torchvison?
self.scheduler.step()
not self.scheduler.step(epoch)
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