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Answered
What Sort Of Integration Is Possible With Clearml And Sagemaker? On The Page

What sort of integration is possible with ClearML and SageMaker? On the page describing ClearML Remote it says:

Create a remote development environment (e.g. AWS SageMaker, GCP CoLab, etc.) on any on-prem machine or any cloud.

But the only mention of SageMaker I see in the docs is the release notes for 0.13 saying "Add support for SageMaker".

I have SageMaker Studio up and running with access to my ClearML server and it's successfully able to log plots and scalars from experiments, but in terms of code it just logs the code used to launch the kernel:

"""Entry point for launching an IPython kernel.
This is separate from the ipykernel package so we can avoid doing imports until
after removing the cwd from sys.path.
"""
import sys

if __name__ == '__main__':
    # Remove the CWD from sys.path while we load stuff.
    # This is added back by InteractiveShellApp.init_path()
    if sys.path[0] == '':
        del sys.path[0]
    from ipykernel import kernelapp as app
    app.launch_new_instance()

Is it possible to capture more than that while using SageMaker?

  
  
Posted 2 years ago
Votes Newest

Answers 77


@<1532532498972545024:profile|LittleReindeer37> nice!!! 😍
Do you want to PR? it will be relatively easy to merge and test, and I think that they might even push it to the next version (or worst case quick RC)

  
  
Posted 2 years ago

environ{'PYTHONNOUSERSITE': '0',
        'HOSTNAME': 'gfp-science-ml-t3-medium-d579233e8c4b53bc5ad626f2b385',
        'AWS_CONTAINER_CREDENTIALS_RELATIVE_URI': '/_sagemaker-instance-credentials/xxx',
        'JUPYTER_PATH': '/usr/share/jupyter/',
        'SAGEMAKER_LOG_FILE': '/var/log/studio/kernel_gateway.log',
        'PATH': '/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tmp/miniconda3/condabin:/tmp/anaconda3/condabin:/tmp/miniconda2/condabin:/tmp/anaconda2/condabin',
        'REGION_NAME': 'us-east-1',
        'AWS_INTERNAL_IMAGE_OWNER': 'Custom',
        'AWS_DEFAULT_REGION': 'us-east-1',
        'PWD': '/home/sagemaker-user',
        'AWS_REGION': 'us-east-1',
        'SHLVL': '1',
        'HOME': '/home/sagemaker-user',
        'AWS_SAGEMAKER_PYTHONNOUSERSITE': '0',
        'AWS_ACCOUNT_ID': 'xxx',
        '_': '/opt/.sagemakerinternal/conda/bin/jupyter-kernelgateway',
        'LC_CTYPE': 'C.UTF-8',
        'KERNEL_LAUNCH_TIMEOUT': '40',
        'KERNEL_WORKING_PATH': '',
        'KERNEL_GATEWAY': '1',
        'JPY_PARENT_PID': '9',
        'PYDEVD_USE_FRAME_EVAL': 'NO',
        'TERM': 'xterm-color',
        'CLICOLOR': '1',
        'FORCE_COLOR': '1',
        'CLICOLOR_FORCE': '1',
        'PAGER': 'cat',
        'GIT_PAGER': 'cat',
        'MPLBACKEND': '
_inline'}
  
  
Posted 2 years ago

At the top there should be the URL of the notebook (I think)

  
  
Posted 2 years ago

the problem is here: None

  
  
Posted 2 years ago

image

  
  
Posted 2 years ago

Try to add here:
None

server_info['url'] = f"http://{server_info['hostname']}:{server_info['port']}/"
  
  
Posted 2 years ago

I've poked around both the internal URL that Jupyter kernel is running on and some of the files in /sagemaker/.jupyter but no luck so far - I can find plenty of kernel info, but not session

  
  
Posted 2 years ago

yeah, even then it'll run but return 0 notebooks

  
  
Posted 2 years ago

sh-4.2$ cat /var/log/studio/kernel_gateway.log | head -n10
{"__timestamp__": "2023-02-23T21:48:28.036559Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0012829303741455078, "method": "GET", "uri": "/api", "status": 200}
{"__timestamp__": "2023-02-23T21:48:39.111068Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0012879371643066406, "method": "GET", "uri": "/api/kernels", "status": 200}
{"__timestamp__": "2023-02-23T21:48:39.116324Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007715225219726562, "method": "GET", "uri": "/api/terminals", "status": 200}
{"__timestamp__": "2023-02-23T21:48:39.272822Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007491111755371094, "method": "GET", "uri": "/api/terminals", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.000795Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 2.539133071899414, "method": "POST", "uri": "/api/kernels", "status": 201}
{"__timestamp__": "2023-02-23T21:48:43.073568Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0013430118560791016, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.469751Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0013761520385742188, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.702549Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0013780593872070312, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.986808Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007445812225341797, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.992860Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.001028299331665039, "method": "GET", "uri": "/api/kernels", "status": 200}
  
  
Posted 2 years ago

and cat /var/log/studio/kernel_gateway.log | grep ipynb comes up empty

  
  
Posted 2 years ago

but the only exception handler is for requests.exceptions.SSLError

  
  
Posted 2 years ago

nope, that's wrong

  
  
Posted 2 years ago

at least in 2018 it returned sessions! None

  
  
Posted 2 years ago

Hmm what do you have here?

os.system("cat /var/log/studio/kernel_gateway.log")
  
  
Posted 2 years ago

but even then the sessions endpoint is still empty

  
  
Posted 2 years ago

it does return kernels, just not sessions

  
  
Posted 2 years ago

This is very odd ... let me check something

  
  
Posted 2 years ago

api/kernels does report back the active kernel, but doesn't give notebook paths or anything

  
  
Posted 2 years ago

Yep I think you are correct, you should have had the same output as a local jupyter notebook, and it seems that in sagemaker studio it is not working 😞
Let me check something

  
  
Posted 2 years ago

I can get it to run up to here: None

  
  
Posted 2 years ago

image

  
  
Posted 2 years ago

weird that it won't return that single session

  
  
Posted 2 years ago

I will once I figure out the fix!

  
  
Posted 2 years ago

that fails

  
  
Posted 2 years ago

As another test I ran Jupyter Lab locally using the same custom Docker container that we're using for Sagemaker Studio, and it works great there, just like the native local Jupyter Lab. So it's seemingly not the image, but maybe something to do with how Studio runs it as a kernel.

  
  
Posted 2 years ago

Just ran the same notebook in a local Jupyter Lab session and it worked as I expected it might, saving a copy to Artifacts

  
  
Posted 2 years ago

so notebooks ends up empty

  
  
Posted 2 years ago

the server_info is

[{'base_url': '/jupyter/default/',
  'hostname': '0.0.0.0',
  'password': False,
  'pid': 9,
  'port': 8888,
  'root_dir': '/home/sagemaker-user',
  'secure': False,
  'sock': '',
  'token': '',
  'url': '
',
  'version': '1.23.2'}]
  
  
Posted 2 years ago

What happens when you call:

from clearml.backend_interface.task.repo import ScriptInfo

print(ScriptInfo._ScriptInfo__legacy_jupyter_notebook_server_json_parsing(None))
  
  
Posted 2 years ago

if I instead change the request url to f"http://{server_info['hostname']}:{server_info['port']}/api/sessions" then it gets a 200 response... however , the response is an empty list

  
  
Posted 2 years ago
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