(二)pytorch視覺化
阿新 • • 發佈:2018-12-09
import torch from tensorboardX import SummaryWriter #writer = SummaryWriter() # 宣告writer物件,儲存的資料夾,預設是runs資料夾(在當前目錄執行tensorboard --logdir runs) #在當前目錄執行tensorboard --logdir log writer = SummaryWriter(log_dir='./log', comment='test_net') x = torch.FloatTensor([100]) y = torch.FloatTensor([200]) for epoch in range(100): x /= 2.0 y /= 2.0 loss = y - x print(loss) #新增正常顯示 writer.add_histogram('zz/x', x, epoch) writer.add_histogram('zz/y', y, epoch) #新增標量化顯示 writer.add_scalar('data/x', x, epoch) writer.add_scalar('data/y', y, epoch) writer.add_scalar('data/loss', loss, epoch) #新增標量組,一起顯示 writer.add_scalars('data/scalar_group', {'x': x, 'y': y, 'loss': loss}, epoch) writer.add_text('zz/text', 'zz: this is epoch ' + str(epoch), epoch)