Question 102336 in Amazon Web Sevices Question posted in
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Amazon web services – How to reduce the verbosity of sagemaker training jobs?

I am training a model with tqdm in the dataloader, the log prints every update in a seperate line that fills up the entire notebook. Is there a way to reduce the verbosity or remove the logs entirely from the jupyter cell similar to from IPython.display import clear_output clear_output(wait=True)?

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2

Answers


  1. 0

    usually the logging can be controlled using the API parameters and SageMaker doesn’t usually add a lot of additional verbose. If you are using a sagemaker notebook instance to run your training you can very well use Ipython clear_output as the notebook is based on jupyter lab.

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  2. 0

    You can set log="None" inside the .fit() parameter.

    Here’s an example how I set it

    job_name = "something"

model = sagemaker.estimator.Estimator(image_uri=container_image_uri,
                                    ...)
model.fit(inputs=train_input,
       job_name=job_name,
       wait=True,
       logs="None")
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