For help running opt-demo with alpa

Please describe the bug
Run opt-demo whth alpa,follow https://alpa-projects.github.io/tutorials/opt_serving.html.
The demo cannot finished even minutes，Manual termination alway see the same info：
File "demo.py", line 23, in
output = model.generate(input_ids=input_ids, max_length=256, do_sample=True)
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/transformers/generation_utils.py", line 1320, in generate
return self.sample(
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/transformers/generation_utils.py", line 1938, in sample
outputs = self(
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/examples/opt_serving/model/wrapper.py", line 96, in call
ret = self.inference_func(input_ids[:, i:i + 1],
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/examples/opt_serving/model/wrapper.py", line 278, in inference_func
output = executable(
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/alpa/pipeline_parallel/pipeshard_executable.py", line 221, in call
out = self.launch_on_driver(*args_flat)
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/alpa/pipeline_parallel/pipeshard_executable.py", line 202, in launch_on_driver
self._check_alive()
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/alpa/pipeline_parallel/pipeshard_executable.py", line 344, in _check_alive
ray.get(rets)
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/ray/worker.py", line 1825, in get
values, debugger_breakpoint = worker.get_objects(object_refs, timeout=timeout)
File "/opt/conda/envs/alpa/lib/python3.8/site-packages/ray/worker.py", line 364, in get_objects
data_metadata_pairs = self.core_worker.get_objects(
File "python/ray/_raylet.pyx", line 1200, in ray._raylet.CoreWorker.get_objects
File "python/ray/_raylet.pyx", line 169, in ray._raylet.check_status
while the nvidia-smi command show：
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.129.06   Driver Version: 470.129.06   CUDA Version: 11.4     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla T4            Off  | 00000000:88:00.0 Off |                    0 |
| N/A   39C    P0    27W /  70W |  13701MiB / 15109MiB |    100%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  Tesla T4            Off  | 00000000:8A:00.0 Off |                    0 |
| N/A   42C    P0    27W /  70W |  13699MiB / 15109MiB |    100%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  Tesla T4            Off  | 00000000:B3:00.0 Off |                    0 |
| N/A   41C    P0    28W /  70W |  13727MiB / 15109MiB |    100%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   3  Tesla T4            Off  | 00000000:B4:00.0 Off |                    0 |
| N/A   39C    P0    27W /  70W |  14233MiB / 15109MiB |    100%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1687      G   /usr/lib/xorg/Xorg                  4MiB |
|    0   N/A  N/A      7322      C   python                             99MiB |
|    0   N/A  N/A      8068      C   ...stWorker.run_executable()    13595MiB |
|    1   N/A  N/A      1687      G   /usr/lib/xorg/Xorg                  4MiB |
|    1   N/A  N/A      7322      C   python                             99MiB |
|    1   N/A  N/A      8068      C   ...stWorker.run_executable()    13593MiB |
|    2   N/A  N/A      1687      G   /usr/lib/xorg/Xorg                  4MiB |
|    2   N/A  N/A      7322      C   python                             99MiB |
|    2   N/A  N/A      8069      C   ...stWorker.run_executable()    13621MiB |
|    3   N/A  N/A      1687      G   /usr/lib/xorg/Xorg                  4MiB |
|    3   N/A  N/A      7322      C   python                            605MiB |
|    3   N/A  N/A      8069      C   ...stWorker.run_executable()    13621MiB |
+-----------------------------------------------------------------------------+
For help，any ideas for investigation?

If you installed the latest version v0.1.4 of alpa (https://pypi.org/project/alpa/), could you run
ray start --head
python3 -m alpa.test_install

If you installed the latest version v0.1.4 of alpa (https://pypi.org/project/alpa/), could you pass the following test?
ray start --head
python3 -m alpa.test_install

I saw you successfully ran the demo in this post (#579 (comment)). What is the difference between this failed run and your successful run?

Yes，I installed the latest version v0.1.4 of alpa.
”python3 -m alpa.test_install” also cannot finished .
I have success run on another server，This two servers has the same system（ubuntu20.04）、nvidia driver（470.129.06），and the same docker image（with the cuda&cudnn）。
The only difference is that one is online and the other is offline when the operating system is installed。Could this have an impact?

@wgimperial what's the solution you ended up with?

We tested and found that it may be a problem with the machine，so we will first check the impact of the machine。


Indice are not showing ?

#Issues
I used both Properties and inline fields #Tagsname .
It can support the inline fields like #projects/one , #projects/two (Inline fields) or it need to be in the Properties ?
I have no idea after follow the guide , create a new note with the tag path like #projects/idx
another new note with a tag path #meta_idx .
There is no block show the index note .
Even restart the Obsidian .
How to call up the view > Force Reload ?

Add this tag into another node of this folder!