load_state("my_checkpoint") # 只能与 Accelerator.save_state() 结合使用 2.5.2 自定义保存 save_state() 保存状态时的位置和方式可以被进一步的自定义,这可以通过 ProjectConfiguration类来实现。例如,如果启用了 automatic_checkpoint_naming,那么每个保存的检查点将被放置在 Accelerator.project_dir/checkpoints/...
只要对象具有state_dict和load_state_dict功能并且已注册检查点,HuggingFace Accelerate 就可以使用上述两种方法保存和加载任何对象。 这是一个在训练期间使用检查点保存和重新加载状态的示例(从 HuggingFace Accelerate 文档获取和修改) fromaccelerateimportAcceleratorimporttorchaccelerator=Accelerator()my_scheduler=torch.optim...
Accelerate提供的加载大模型的第二个工具是函数load_checkpoint_and_dispatch()，该函数可以完成向空模型加载参数的操作过程。该函数支持单个checkpoint加载（单个文件包含所有的state dict），也支持多个checkpoint分片的加载。它会自动完成权重向各个设备的分配（包括多个GPU、CPU或硬盘等），例如加载分片checkpoin...
accelerator.wait_for_everyone()unwrapped_model=accelerator.unwrap_model(model)unwrapped_model.save_pretrained(save_dir,save_function=accelerator.save,state_dict=accelerator.get_state_dict(model)) Note: DeepSpeed support is experimental for now. In case you get into some problem, please open an issue...
first_state_dict.bin包含 "linear1.weight "和 "linear1.bias "的权重。second_state_dict.bin是 "linear2.weight "和 "linear2.bias "的权重。 加载权重 第二个工具是引入了一个函数load_checkpoint_and_dispatch(),它将允许你在你的空模型中加载一个检查点。这支持完整的检查点(一个单个文件包含整个状态...
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support - accelerate/src/accelerate/hooks.py at main · hug
state = { 'epoch': epoch+1, 'state_dict': model.module.state_dict(), 'best_top5': best_top5, 'optimizer' : optimizer.state_dict(), } torch.save(state, filename) if args.local_rank == 0: if is_best: save_checkpoint(epoch, model, best_top5, optimizer, is_best=True, filenam...
Load the CIFAR10 dataset. Set the environment variableONEDNN_MAX_CPU_ISA: DEFAULTif running with Intel AMX AVX512_CORE_BF16if running with Intel AVX-512 Instantiate the ResNet50 model and use Intel Extension for PyTorch’soptimize()function on the model and training optimizer of ch...
The low-latency Intel Optane SSD P5800X series delivers near-nanosecond response times under any workload, maintaining consistent read response times, regardless of the write throughput. Near-nanosecond latency means improved application response times. With its bidirectional c...
If the status of the instance that is indicated by Status and the status of the container that is indicated by ContainerStatuses.State are Running, the instance is created and the container is running. Open Internet access to the application. If the VPC in which the elastic container ...