tensorBoard logging for pytorch
1. 로거 패키지 로딩
import torch
import torch.nn as nn
import torchvision.datasets as dsets
import torchvision.transforms as transforms
from torch.autograd import Variable
# 로거 패키지 로딩 *********(1)
from logger import Logger
2. 로거 경로 설정
# 로거의 로그경로 설정
logger = Logger('./logs')
3. 텐서보드 로깅
# (1) Log the scalar values ************** (3)
info = {
'loss': loss.data[0],
'accuracy': accuracy.data[0]
}
for tag, value in info.items():
logger.scalar_summary(tag, value, step+1)
1. Install the dependencies
답글삭제$ pip install -r requirements.txt
2. Train the model
$ python main.py
3. Open the TensorBoard
To run the TensorBoard, open a new terminal and run the command below. Then, open http://localhost:6006/ in your web browser.
$ tensorboard --logdir='./logs' --port=6006
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/04-utils/tensorboard
답글삭제info = {
답글삭제'epoch': epoch,
'errD': errD.data[0],
'errG': errG.data[0]
}
for tag, value in info.items():
logger.scalar_summary(tag, value, epoch)
print('{} Loss: {:.4f} Acc: {:.4f}'.format(
답글삭제phase, epoch_loss, epoch_acc))
if phase == 'train':
info={
'trainLoss':epoch_loss, 'trainAccuracy':epoch_acc
}
for tag, value in info.items():
logger.scalar_summary(tag, value, epoch+1)
else:
info={
'valLoss':epoch_loss, 'valAccuracy':epoch_acc
}
for tag, value in info.items():
logger.scalar_summary(tag, value, epoch+1)