aws / aws/amazon-sagemaker-examples
mxnet_mnist_with_gluon_local_mode.ipynb failed CI
- Dominant language
- Jupyter Notebook
- Stars
- 11k
- Forks
- 7k
- Avg merge
- 8h 29m
- Merged PRs (30d)
- 8
Description
Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/sagemaker-python-sdk/mxnet_gluon_mnist/mxnet_mnist_with_gluon_local_mode.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [2]":
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
in
11 instance_type = 'local'
12
---> 13 if subprocess.call('nvidia-smi') == 0:
14 ## Set type to GPU if one is present
15 instance_type = 'local_gpu'
/usr/local/lib/python3.7/subprocess.py in call(timeout, *popenargs, **kwargs)
337 retcode = call(["ls", "-l"])
338 """
--> 339 with Popen(*popenargs, **kwargs) as p:
340 try:
341 return p.wait(timeout=timeout)
/usr/local/lib/python3.7/subprocess.py in __init__(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creation
[...]
FileNotFoundError: [Errno 2] No such file or directory: 'nvidia-smi': 'nvidia-smi'
Contributor guide
Research direction
Start with sagemaker-python-sdk/mxnet_gluon_mnist/mxnet_mnist_with_gluon_local_mode.ipynb, especially cell In [2] and its subprocess.call('nvidia-smi') check. Run the notebook in the CI environment and verify that it completes when nvidia-smi is unavailable while still detecting the local GPU case when applicable.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 35/100