通过local_rank来确定该进程的设备:torch.cuda.set_device(opt.local_rank) 数据加载部分我们在该教程的第一篇里介绍过,主要时通过torch.utils.data.distributed.DistributedSampler来获取每个gpu上的数据索引,每个gpu根据索引加载对应的数据,组合成一个batch,与此同时Dataloader里的shuffle必须设置为None。 多机多卡训练 ...
Torch is easy to use and efficient, thanks to an easy and fast scripting language, Lua, and an underlying C/CUDA implementation. Torch offers popular neural network and optimization libraries that are easy to use yet provide maximum flexibility to build complex neural network topologies. Running ...
that is, I change the codetorch.cuda.set_device(self.opt.gpu_ids[0])totorch.cuda.set_device(self.opt.gpu_ids[-1])andtorch._C._cuda_setDevice(device)totorch._C._cuda_setDevice(-1),but it still not works. I tried to reinstall the pytorch and update to the newest version (1.4.0...
device = torch_device_from_trt(self.engine.get_location(idx)) output = torch.empty(size=shape, dtype=dtype, device=device) outputs[i] = output bindings[idx] = output.data_ptr() self.context.execute_async_v2(bindings, torch.cuda.current_stream().cuda_stream) outputs = tuple(outputs) if ...
将torch.cuda.amp.GradScaler替换为torchacc.torch_xla.amp.GradScaler: fromtorchacc.torch_xla.ampimportGradScaler 替换optimizer。 使用原生PyTorch optimizer性能会稍差,可将torch.optim的optimizer替换为syncfree optimizer来进一步提升训练速度。 fromtorchacc.torch_xla.ampimportsyncfree ...
最近在弄NLP模型的部署,记录下过程及其中一些坑。以下是基于Linudx RHELt8的配置过程 1. CUDA\cuDNN\显卡驱动版本匹配(多版本切换) 2. 使用Torch-TensorRT将torch模型转TensorRT 3. tensorRT使用的cuda\cuDNN版…
data_loader_train = torch.utils.data.DataLoader(dataset=data_set, batch_size=batch_size, sampler=train_sampler) net = ConvNet() net = net.cuda() net = torch.nn.parallel.DistributedDataParallel(net, device_ids=[rank]) criterion = torch.nn.CrossEntropyLoss() opt = torch.optim.Adam(net.pa...
get_device_properties(torch.device(cuda)))" _CudaDeviceProperties(name='NVIDIA A100-SXM4-40GB', major=8, minor=0, total_memory=40536MB, multi_processor_count=108) git clone https://github.com/microsoft/DeepSpeed/ cd DeepSpeed rm -rf build TORCH_CUDA_ARCH_LIST=“8.0” DS_BUILD_CPU_ADAM...
+importtorchacc.torch_xla.core.xla_modelasxm +importtorchacc.torch_xla.distributed.parallel_loaderasploader + dist.get_rank = xm.get_ordinal + dist.get_world_size = xm.xrt_world_size + device = xm.xla_device() + xm.set_replication(device, [device]) +else:fromtorch.cuda.ampimport...
But for reinstall torch + cuda loads properly but cv2 does not.rakesh.thykkoottathil.jay 2023 年9 月 20 日 16:16 14 Below is my docker file: # Use an official Python runtime as a parent image FROM dustynv/l4t-ml:r35.2.1 # Set the working directory inside...