Error when running watermarks_removal.py:
C:\.....\DoubleDIP\DoubleDIP-master>python watermarks_removal.py Traceback (most recent call last): File "watermarks_removal.py", line 567, in <module> remove_watermark_many_images(['f1'], [im1], "fotolia_many_images") File "watermarks_removal.py", line 544, in remove_watermark_many_images s.optimize() File "watermarks_removal.py", line 440, in optimize self._optimization_closure(j, step) File "watermarks_removal.py", line 502, in _optimization_closure self.watermark_net_output = self.watermark_net(watermark_net_input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\Documents\machine_learning\DoubleDIP\DoubleDIP-master\net\layers.py", line 54, in forward inputs.append(module_(input_)) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\conv.py", line 349, in forward return self._conv_forward(input, self.weight) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\conv.py", line 346, in _conv_forward self.padding, self.dilation, self.groups) RuntimeError: CUDA out of memory. Tried to allocate 2.00 MiB (GPU 0; 4.00 GiB total capacity; 815.82 MiB already allocated; 0 bytes free; 2.42 GiB reserved in total by PyTorch)
On the web I found solutions like reducing the batch size, but in this case I can not find anything I could change to a lower value that might not take that much memory.
Any suggestion I could do?
Error when running watermarks_removal.py:
C:\.....\DoubleDIP\DoubleDIP-master>python watermarks_removal.py Traceback (most recent call last): File "watermarks_removal.py", line 567, in <module> remove_watermark_many_images(['f1'], [im1], "fotolia_many_images") File "watermarks_removal.py", line 544, in remove_watermark_many_images s.optimize() File "watermarks_removal.py", line 440, in optimize self._optimization_closure(j, step) File "watermarks_removal.py", line 502, in _optimization_closure self.watermark_net_output = self.watermark_net(watermark_net_input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\Documents\machine_learning\DoubleDIP\DoubleDIP-master\net\layers.py", line 54, in forward inputs.append(module_(input_)) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\conv.py", line 349, in forward return self._conv_forward(input, self.weight) File "C:\Users\youre\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\nn\modules\conv.py", line 346, in _conv_forward self.padding, self.dilation, self.groups) RuntimeError: CUDA out of memory. Tried to allocate 2.00 MiB (GPU 0; 4.00 GiB total capacity; 815.82 MiB already allocated; 0 bytes free; 2.42 GiB reserved in total by PyTorch)On the web I found solutions like reducing the batch size, but in this case I can not find anything I could change to a lower value that might not take that much memory.
Any suggestion I could do?