在我的代码里根本就没有找到任何inplace操作,因此上面这种方法行不通。自己盯着代码,debug,啥也看不出来,好久... 忽然有了新idea。我的训练阶段的代码如下: forepochinrange(1, epochs +1):foridx, (lr, hr)inenumerate(traindata_loader): lrs = lr.to(device) hrs = hr.to(device)# update the disc...
The coefficientageThe coefficientsex_femaleThe coefficientforsex_maleis-8.762584065506853The coefficientforbmiis0.3807106266997645The coefficientforchildren_0is-0.06605803000190659The coefficientforchildren_1is-0.946643170369065The coefficientforchildren_2is0.2108032984623088The coefficientforchildren_3is0.8800441822437507The...
set_train(True)fori, (images, labels)inenumerate(data_loader): loss = train_step(images, ...
eval_losses.append(eval_loss/len(test_loader)) eval_acces.append(eval_acc/len(test_loader)) print('epoch:{},Train Loss:{:.4f},Train Acc:{:.4f},Test Loss:{:.4f},Test Acc:{:.4f}' .format(epoch,train_loss/len(train_loader),train_acc/len(train_loader), eval_loss/len(test_loader...
值得注意的是,模型和数据都需要先 load 进 GPU 中,DataParallel 的 module 才能对其进行处理,否则会报错: # 这里要 model.cuda() model = nn.DataParallel(model.cuda(), device_ids=gpus, output_device=gpus[0]) for epoch in range(100): for batch_idx, (data, target) in enumerate(train_loader):...
("Start Training ...")# 训练循环forepochinrange(num_epoch):step=1train_loss=train_acc=0fordataintqdm(train_loader):# Load all data into GPUdata=[i.to(device)foriindata]# 将批次中的所有数据加载到GPU上# data是列表,共5个元素,分别对于input_ids, token_type_ids, attention_mask, start_...
train_path,filename=config.train_file,is_training=True,config=config,cached_features_file=os.path.join(config.train_path,"cache_" + config.train_file.replace("json","data"))) train_features,train_dataset = train_Dataset.features,train_Dataset.dataset train_loader = torch.utils.data.DataLoader...
值得注意的是,模型和数据都需要先 load 进 GPU 中,DataParallel 的 module 才能对其进行处理,否则会报错: # 这里要 model.cuda() model = nn.DataParallel(model.cuda(), device_ids=gpus, output_device=gpus[0]) for epoch in range(100): for batch_idx, (data, target) in enumerate(train_loader):...
值得注意的是,模型和数据都需要先 load 进 GPU 中,DataParallel 的 module 才能对其进行处理,否则会报错: # 这里要 model.cuda() model = nn.DataParallel(model.cuda(), device_ids=gpus, output_device=gpus[0]) for epoch in range(100): for batch_idx, (data, target) in enumerate(train_loader):...