Closed anotinelg closed 3 years ago
Are there any news on this or possible solutions? I am having the same issue when trying to run sagemaker pytorch estimator with instance_type = 'local'.
Hi there, sorry for the late response. Can I ask where are you running the code from? The Python SDK code above calls CreateTrialComponent API which is restricted to SageMaker environments only: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrialComponent.html.
Hi there, sorry for the late response. Can I ask where are you running the code from? The Python SDK code above calls CreateTrialComponent API which is restricted to SageMaker environments only: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrialComponent.html.
In my case, i was trying to do that in a jupyter sagemaker notebook.
Hi Antoine, you should use Tracker.load
instead of Tracker.create
in this case. The load
method is the most common way to instantiate the tracker.
tf_estimator.fit(...job_name = job_name...)
tracker = Tracker.load(training_job_name=job_name, ...)
tracker.log_parameters(hyperparams)
@wangweixun Thank you for the resposne. So it is not possible to run those experiments locally and log the results to the AWS experiments? (even from the supported docker image?)
is not possible to run those experiments locally and log the results to the AWS experiments? (even from the supported docker image?)
It is not possible. In order for metrics to show up in Studio/Experiments log_metric
must be called from a training job instance.
Describe the bug In a jupyter notebook, i am not able to create a tracker ! I am not sure if it is really a bug, or a misconception from my part.
To Reproduce Steps to reproduce the behavior:
in a jupyter notebook:
this fails to:
Expected behavior If i understand the (examples)[https://github.com/shashankprasanna/sagemaker-experiments-examples/blob/master/sagemaker-experiment-examples.ipynb], this code should not give any problem:
Screenshots If applicable, add screenshots to help explain your problem.
Environment: jupyter notebook version of: sagemaker_experiments= '0.1.25' sagemaker =2.19.0
Additional context Add any other context about the problem here.