world size: 1 data parallel size: 1 model parallel size: 1 batch size per GPU: 1024 params per gpu: 1.29 M params of model = params per GPU * mp_size: 1.29 M fwd MACs per GPU: 41271.95 G fwd flops per GP A modul
world size: 1 data parallel size: 1 model parallel size: 1 batch size per GPU: 80 params per gpu: 336.23 M params of model = params per GPU * mp_size: 336.23 M fwd MACs per GPU: 3139.93 G fwd flops per GPU: 6279.86 G fwd flops of model = fwd flops per GPU * mp_size: 6279....
utils.data.DataLoader(trainset, # 每个批次包含16张图像 batch_size=16, # 在每次迭代开始时随机打乱训练数据的顺序 # 有助于模型训练 shuffle=True, # 开启2个子进程来并行加载数据,提高效率 num_workers=2) # 创建测试数据集 testset = torchvision.datasets.CIFAR10(root='./data', train=False, download...
cmd_args= parser.parse_args()#deepspeed命令行参数dataset= torchvision.datasets.FashionMNIST(root='./dataset', download=True, transform=img_transform)#数据集dataloader = torch.utils.data.DataLoader(dataset, batch_size=32, num_workers=4, shuffle=True)#数据加载器,batch_size应该等于train_batch_size/...
import os import torch import torch.distributed as dist import torch.multiprocessing as mp import torch.nn as nn import torch.optim as optim from torch.nn.parallel import DistributedDataParallel as DDP def example(rank, world_size): # create default process group dist.init_process_group("gloo",...
batch_size=16, shuffle=True, num_workers=2) testset = torchvision.datasets.CIFAR10(root='./data', train=False, download=True, transform=transform) testloader = torch.utils.data.DataLoader(testset, batch_size=4, shuffle=False, num_workers=2) ...
Setting ds_accelerator tocuda(auto detect)using world size:1and model-parallel size:1>using dynamic loss scaling>initializing model parallelwithsize1PretrainGPT2modelarguments:pretrained_bert...False attention_dropout...0.1num_attention_heads...16hidden_size...1024intermediate_size...None num_layers...
mpu – 可选:一个实现以下方法的对象:get_model_parallel_rank/group/world_size 和 get_data_parallel_rank/group/world_size。 deepspeed_config – 可选:当提供DeepSpeed配置JSON文件时,将用于配置DeepSpeed激活检查点。 partition_activations – 可选:启用后在模型并行GPU之间Partitions activation checkpoint。默认...
transform=transform)testloader= torch.utils.data.DataLoader(testset,batch_size=4,shuffle=False,num_workers=2) 2.2 编写模型: importtorch.nn as nnimporttorch.nn.functional as FclassNet(nn.Module):def__init__(self):super(Net, self).__init__()self.conv1= nn.Conv2d(3,6,5)self.pool = ...
设置参数 # LoRA参数 LORA_R = 8 LORA_ALPHA = 32 LORA_DROPOUT = 0.1 # 训练参数 EPOCHS=3 LEARNING_RATE=5e-5 OUTPUT_DIR="./checkpoints" BATCH_SIZE=4 # 2 GRADIENT_ACCUMULATION_STEPS=3 # 其他参数 MODEL_PATH = "bigscience/bloomz-7b1-mt" DATA_PATH = "./data/belle_open_source_1M...