目录
step1：下载专业版本的pycharm
https://www.jetbrains.com/pycharm/download/other.html
首先，你需要有个专业版本的pycharm，并且要有激活码，有需要激活码的可以私信我，我这里的激活码全部最新的pycharm都可以激活，以下激活码只是样例，过期了。
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step2 配置自动同步文件夹，即远程的工程文件和本地同步
我现在代码在远程服务器上。所以需要把远程服务器代码和我本地一个新建文件夹同步。
新建文件夹remote_0724_new并用pycharm打开，最新版本的pycharm2023.1.4打开空文件夹会自动新建一个main.py文件了。
2.1 Tools -> Deployment -> configuration
点左上角“+”，选择SFTP，随便命名一个server，“port_30975”
输入远程服务器ip，用户名密码端口号，并测试是否链接成功
2.2 设置同步文件夹
最右边的Excluded Paths是不需要同步的文件夹，比如数据文件夹等不需要同步。
2.3 同步服务器上代码到本地
这里打开多级设置，还不好截图了，只能手机拍照了
最下面的File Transfer会显示传输日志信息
代码就同步过来了。
2.3 设置代码同步，Tools->Deploment->Automatic Upload Always
就是你pycharm本地修改的代码自动也在服务器上修改
这里图上下面Browse Remote Host点开，可以在侧边栏显示远程服务器的文件目录，也可以直接在侧边栏打开
代码同步功能需要自己测试一下，比如就在pycharm修改代码，看远程服务器上面代码有没有自己同步过来。
在最下面栏，Terminal然后^可以打开远程的终端，可以vim查看代码是否同步过来了。
step3 配置解释器
3.1 一般可以直接debug
File -> Settings->Project->Python interpreter->Add interpreter->On SSH
输入密码端口号用户等信息，然后next，然后第4步project director and python
这里我设置的是第二个system interpreter，我远程环境就是直接用的系统目录下的python的，没有用conda虚拟环境。
设置python的路径，可以在远程环境下which python看看用的哪里的python
sync folders还是设置的之前的本地和远程的同步文件夹
这里理论上可以运行debug远程服务器上代码了，但是我这个比较特殊，是运行的pyorch的分布式训练的代码。运行的指令是
python -m torch.distributed.launch --nproc_per_node=1 main.py
直接点运行会报错
/usr/bin/python /code_src_debug/main.py
./logs/test
File "/_src_debug/src/data.py", line 807, in compile_data
train_sampler = DistributedSampler(traindata)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/distributed.py", line 65, in __init__
num_replicas = dist.get_world_size()
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/distributed_c10d.py", line 625, in get_world_size
return _get_group_size(group)
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/distributed_c10d.py", line 220, in _get_group_size
_check_default_pg()
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/distributed_c10d.py", line 211, in _check_default_pg
"Default process group is not initialized"
AssertionError: Default process group is not initialized
Process finished with exit code 1
这里需要格外的关注pycharm第一行给我们实际运行的指令
/usr/bin/python /code_src_debug/main.py
3.2 pytorch的分布式训练， 直接跑不debug
Run ->Edit Configurations...，在Interpreter optiins:这栏填写-m torch.distributed.launch --nproc_per_node=1
点运行按钮，可以直接跑了，这回pycharm给出的运行指令是：
/usr/bin/python -m torch.distributed.launch --nproc_per_node=1 /code_src_debug/main.py
./logs/test
3.3 pytorch的分布式训练， debug
按照上面3.2，debug运行，报错
/usr/bin/python -m torch.distributed.launch --nproc_per_node=1 /root/.pycharm_helpers/pydev/pydevd.py --multiprocess --qt-support=auto --client localhost --port 60888 --file /code_src_debug/main.py
Traceback (most recent call last):
File "/root/.pycharm_helpers/pydev/pydevd.py", line 2016, in main
setup = process_command_line(sys.argv)
File "/root/.pycharm_helpers/pydev/_pydevd_bundle/pydevd_command_line_handling.py", line 146, in process_command_line
raise ValueError("Unexpected option: " + argv[i])
ValueError: Unexpected option: --local_rank=0
Usage:
pydevd.py --port N [(--client hostname) | --server] --file executable [file_options]
Traceback (most recent call last):
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 260, in <module>
main()
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 256, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/usr/bin/python', '-u', '/root/.pycharm_helpers/pydev/pydevd.py', '--local_rank=0', '--multiprocess', '--qt-support=auto', '--client', 'localhost', '--port', '60888', '--file', '/machengnan/bevobj_20230620_vircam_yhl/bevobj_20230620_vircam_src_debug/main.py']' returned non-zero exit status 1.
Process finished with exit code 1