随后,torch.cuda.empty_cache()被用来清理未使用的显存。在这之后,我们可以继续推理下一张图片,而不会因为显存不足而遭遇错误。 可视化推理过程 为了更好地理解上述过程,我们可以用序列图进行可视化: CUDAModelUserCUDAModelUserLoad Model to GPUModel LoadedPrepare Input ImagePerform InferenceOutput ResultClear Cache...
RuntimeError: cuda runtime error (2) : out of memory at /opt/conda/conda-bld/pytorch_1587428266983/work/aten/src/THC/THCCachingHostAllocator.cpp:278如上,我们在跑程序时经常会遇到这种情况,除了常规的因为模型参数量或计算量过大导致的问题,还有一种经常的情 ...
it is possible to temporarily disable (expandable_segments:False) the bevhavior for allocator tensors that need to be used cross-process. * CUDA runtime APIs related to sharing memory across process (cudaDeviceEnablePeerAccess) do not work for...
def _preproc_worker(dali_iterator, cuda_stream, fp16, mean, std, output_queue, proc_next_input, done_event, pin_memory):"""Worker function to parse DALI output & apply final preprocessing steps"""while not done_event.is_set():# Wait until main thread signals to proc_next_input -- ...
both in memoryencoder_rnn.cuda(0)decoder_rnn.cuda(1)# run input through encoder on GPU 0encoder_out = encoder_rnn(x.cuda(0))# run output through decoder on the next GPUout = decoder_rnn(encoder_out.cuda(1))# normally we want to bring all outputs back to GPU 0out = out.cuda(0...
# each model is sooo big we can't fit both in memoryencoder_rnn.cuda(0)decoder_rnn.cuda(1)# run input through encoder on GPU 0encoder_out=encoder_rnn(x.cuda(0))# run output through decoder on the next GPUout=decoder_rnn(encoder_out.cuda(1))# normally we want to bring all output...
模型状态内存(Model State Memory): 深度学习模型的状态可归为:优化器状态、梯度和参数这三个基本过程。 激活内存(Activation Memory):在优化了模型状态内存之后,人们发现激活函数也会导致瓶颈。激活函数计算位于前向传播之中,用于支持后向传播。 碎片内存(Fragmented Memory):深度学习模型的低效有时是由于内存碎片所导...
been retrieved over the wire on a separate stream and the// sendFunction itself runs on a different stream. As a result, we need to// manually synchronize those two streams here.constauto&send_backward_stream=sendFunction->stream(c10::DeviceType::CUDA);if(send_backward_stream){for(const...
Some users with 12.2 CUDA driver (535 version) report seeing "CUDA driver error: invalid argument" during NCCL or Symmetric Memory initialization. This issue is currently under investigation, see#150852. If you use PyTorch from source, a known workaround is to rebuild PyTorch with CUDA 12.2 to...
big we can't fit both in memoryencoder_rnn.cuda(0)decoder_rnn.cuda(1)# run input through encoder on GPU 0out = encoder_rnn(x.cuda(0))# run output through decoder on the next GPUout = decoder_rnn(x.cuda(1))# normally we want to bring all outputs back to GPU 0out = out.cuda...