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The proposed method in LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild
训练时使用了LRW-1000,数据、标签路径均无误。即使改小了batch_size=10也是无法解决
Traceback (most recent call last):
File "D:\Anaconda3\envs\py36\lib\multiprocessing\process.py", line 258, in _bootstrap
self.run()
File "D:\Anaconda3\envs\py36\lib\multiprocessing\process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "E:\Git_Lip\D3D\main.py", line 74, in run
trn_epoch(model=model, data_loader=trn_loader, optimizer=optimizer, epoch=epoch)
File "E:\Git_Lip\D3D\util.py", line 76, in trn_epoch
outputs = model(inputs)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch\nn\modules\module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "E:\Git_Lip\D3D\model\D3D.py", line 125, in forward
f2 = self.features(x)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch\nn\modules\module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch\nn\modules\container.py", line 92, in forward
input = module(input)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch\nn\modules\module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch\nn\modules\pooling.py", line 210, in forward
self.return_indices)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch_jit_internal.py", line 134, in fn
return if_false(*args, **kwargs)
File "D:\Anaconda3\envs\py36\lib\site-packages\torch\nn\functional.py", line 519, in _max_pool3d
input, kernel_size, stride, padding, dilation, ceil_mode)
RuntimeError: CUDA out of memory. Tried to allocate 1.44 GiB (GPU 0; 11.00 GiB total capacity; 7.05 GiB already allocated; 1.37 GiB free; 10.02 MiB cached)
Hi, how can I test it on a video. Thanks for the code.
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