Linux后台命令的使用说明

1)ctrl+Z:停止当前进程

首先先将一个程序运行起来,这个时候如果你需要去干别的事情,需要暂停运行,可以使用ctrl+Z:

user@mine:/opt/user/pytorch-gender$ python train_debug.py --debugFile=./debug
{'debugFile': './debug'}
Epoch 0/199
----------
^Z
[1]+  Stopped                 python train_debug.py --debugFile=./debug 

从上面可以看见,这个程序已经已经停止了,状态为Stopped

2)jobs:用于查看正在运行的命令

user@mine:/opt/user/pytorch-gender$ jobs
[1]+  Stopped                 python train_debug.py --debugFile=./debug 

前面的编号[1]是命令编号

3)bg 命令编号:把程序调度到后台执行:

user@mine:/opt/user/pytorch-gender$ bg 1
[1]+ python train_debug.py --debugFile=./debug &
user@mine:/opt/user/pytorch-gender$ jobs
[1]+  Running                 python train_debug.py --debugFile=./debug & 

然后我们可以看见该命令在后台运行起来了,状态为Running,命令后的&标志就是把命令放在后台运行的意思

这个时候该命令生成的返回信息会自己打印出来:

user@mine:/opt/user/pytorch-gender$ train Loss: 0.4611 Acc: 0.7824
val Loss: 0.1882 Acc: 0.9340
Epoch 1/199
----------

user@mine:/opt/user/pytorch-gender$ train Loss: 0.3271 Acc: 0.8578
val Loss: 0.1845 Acc: 0.9260
Epoch 2/199
---------- 

不影响你运行其他的命令,你就输入你的命令回车即可

 当然,如果你不想让输出显示在控制台中,那就在运行时指明将输出信息写入日志文件:

user@mine:/opt/user/pytorch-gender$ python train_debug.py --debugFile=./debug >> gender_log_debug_1.out 

打开另一个窗口查看日志文件为:

user@mine:/opt/user/pytorch-gender$ cat gender_log_debug_1.out
{'debugFile': './debug'}
Epoch 0/199
---------- 

然后这个时候如果你想进行调试,即pytorch Debug —交互式调试工具Pdb (ipdb是增强版的pdb)-1-在pytorch中使用,那么你在本地生成文件夹debug后,再查看日志文件变为:

user@mine:/opt/user/pytorch-gender$ cat gender_log_debug_1.out
{'debugFile': './debug'}
Epoch 0/199
----------
train Loss: 0.4507 Acc: 0.7919
val Loss: 0.1578 Acc: 0.9420
Epoch 1/199
----------
train Loss: 0.3201 Acc: 0.8576
val Loss: 0.1069 Acc: 0.9540
Epoch 2/199
----------
--Call--
> /home/mine/anaconda3/lib/python3.6/site-packages/torch/autograd/grad_mode.py(129)__exit__()
    128
--> 129     def __exit__(self, *args):
    130         torch.set_grad_enabled(self.prev)

ipdb> user@mine:/opt/user/pytorch-gender$ 

这时候你在命令端输入调试命令u:

user@mine:/opt/user/pytorch-gender$ python train_debug.py --debugFile=./debug >> gender_log_debug_1.out
u

可见日志文件中变为:

user@mine:/opt/user/pytorch-gender$ cat gender_log_debug_1.out
{'debugFile': './debug'}
Epoch 0/199
----------
train Loss: 0.4507 Acc: 0.7919
val Loss: 0.1578 Acc: 0.9420
Epoch 1/199
----------
train Loss: 0.3201 Acc: 0.8576
val Loss: 0.1069 Acc: 0.9540
Epoch 2/199
----------
--Call--
> /home/mine/anaconda3/lib/python3.6/site-packages/torch/autograd/grad_mode.py(129)__exit__()
    128
--> 129     def __exit__(self, *args):
    130         torch.set_grad_enabled(self.prev)

ipdb> > /opt/user/pytorch-gender/train_debug.py(151)train_model()
    150                             import ipdb;
--> 151                             ipdb.set_trace()
    152

ipdb> 

如果调用l 123命令:

user@mine:/opt/user/pytorch-gender$ python train_debug.py --debugFile=./debug >> gender_log_debug_1.out
u
l 123

可见日志文件又变为:

user@mine:/opt/user/pytorch-gender$ cat gender_log_debug_1.out
{'debugFile': './debug'}
Epoch 0/199
----------
train Loss: 0.4507 Acc: 0.7919
val Loss: 0.1578 Acc: 0.9420
Epoch 1/199
----------
train Loss: 0.3201 Acc: 0.8576
val Loss: 0.1069 Acc: 0.9540
Epoch 2/199
----------
--Call--
> /home/mine/anaconda3/lib/python3.6/site-packages/torch/autograd/grad_mode.py(129)__exit__()
    128
--> 129     def __exit__(self, *args):
    130         torch.set_grad_enabled(self.prev)

ipdb> > /opt/user/pytorch-gender/train_debug.py(151)train_model()
    150                             import ipdb;
--> 151                             ipdb.set_trace()
    152

ipdb>     118                 labels = labels.to(device)  # 当前批次的标签输入
    119                 # print('input : ', inputs)
    120                 # print('labels : ', labels)
    121
    122                 # 将梯度参数归0
    123                 optimizer.zero_grad()
    124
    125                 # 前向计算
    126                 # track history if only in train
    127                 with torch.set_grad_enabled(phase == 'train'):
    128                     # 相应输入对应的输出

ipdb> 

所以输出和命令输入虽然不在一起,但是并不妨碍功能的实现

4)fg 命令编号:将后台命令调到前台运行

如果我想要对上面的命令进行调试,我就需要将其调到前台,然后再进行调试

user@mine:/opt/user/pytorch-gender$ fg 1
python train_debug.py --debugFile=./debug
train Loss: 0.2337 Acc: 0.9059
val Loss: 0.1347 Acc: 0.9400
Epoch 4/199
----------
train Loss: 0.2040 Acc: 0.9141
val Loss: 0.0962 Acc: 0.9640
Epoch 5/199
----------
train Loss: 0.1984 Acc: 0.9182
val Loss: 0.0825 Acc: 0.9720
Epoch 6/199
----------
train Loss: 0.1841 Acc: 0.9218
val Loss: 0.1059 Acc: 0.9640
Epoch 7/199
----------
train Loss: 0.1868 Acc: 0.9215
val Loss: 0.0668 Acc: 0.9740
Epoch 8/199
----------
train Loss: 0.1782 Acc: 0.9273
val Loss: 0.0735 Acc: 0.9740
Epoch 9/199
----------
train Loss: 0.1703 Acc: 0.9291
val Loss: 0.0850 Acc: 0.9680
Epoch 10/199
----------
train Loss: 0.1596 Acc: 0.9329
val Loss: 0.1114 Acc: 0.9560
Epoch 11/199
----------
--Call--
> /home/mine/anaconda3/lib/python3.6/site-packages/torch/autograd/grad_mode.py(129)__exit__()
    128
--> 129     def __exit__(self, *args):
    130         torch.set_grad_enabled(self.prev)

ipdb>                                  

5)nohup 命令 & :直接将命令放在后台运行

nohup python train_debug.py --debugFile=./debug &

如果要指定返回信息写入的日志文件log.out:

nohup python train_debug.py --debugFile=./debug >> log.out &

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转载自www.cnblogs.com/wanghui-garcia/p/10755205.html