pytorch中tensorboard數據顯示

pytorch 利用tensorboard顯示loss，acc曲線等

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運行環境：

python3.6.9
pytorch1.13.1
cuda10.0
cudnn7.5.1

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tensorboard顯示

運行PointRCNN算法進行training，得出events.out.tfevents.1592297776.hkd-Precision-7920-Tower

打開終端輸入：tensorboard --logdir path/to/tensorboard_logs/
會有輸出：TensorBoard 1.6.0 at http://iccd:6006 (Press CTRL+C to quit)
將上述鏈接複製到瀏覽器中打開便可以顯示該訓練參數（tensorboard）

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tensorboard記錄

from tensorboard_logger import Logger

logger = Logger(logdir="./tensorboard_logs", flush_secs=10)
...
def train(net, optimizer):
    for epoch in range(epoch_nums):
        net.train()
        for batch_idx, (inputs, targets) in enumerate(trainloader):           
            inputs = Variable(inputs, requires_grad=True).cuda()
            targets = targets.cuda()
            optimizer.zero_grad()
            outputs = net(inputs)
            loss = criterion(outputs, targets)
            loss.backward()  
            optimizer.step()
            train_loss += loss.item()
            ...
            # 記錄所需的變量
            logger.log_value('avg_loss', train_loss/(batch_idx+1), epoch*len(trainloader) + batch_idx)
            logger.log_value('loss', loss.item(), epoch*len(trainloader) + batch_idx)
            logger.log_value('acc', 100. * correct / total, epoch*len(trainloader) + batch_idx)