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69 × Eureka!CostlyOstrich36 Not sure I understood, the current iterations come from the function
task.get_last_iteration() ...
logger = task.get_logger()
train(model_dir=trained_model_dst, pipeline_config_path=pipeline_config_path, save_checkpoints_steps=args.checkpoints)
logger.report_scalar(title='evaluate', series='score', value=5, iteration=task.get_last_iteration())
CostlyOstrich36 having the reported tensorflow scalars show up on ClearML
SuccessfulKoala55
Hi,
Using task.upload_artifact
CostlyOstrich36 I get the last iteration by task.get_last_iteration()
I want to report each iteration..
Yes that's exactly what i do, But I'm trying to figure out if I can write down the line of code
logger.report_scalar(title='evaluate', series='score', value=5, iteration=task.get_last_iteration())
anywhere in the code?
Does the line of code open up another process parallel to training?
CostlyOstrich36 More precisely, My function only calculates the accuracy as I defined it.
I passing the accuracy to logger.report_scalar by
logger.report_scalar(title='evaluate', series='score', value=my_acc, iteration=task.get_last_iteration())
I have nowhere else to bring iteration number ..
CostlyOstrich36 I have my own function that gives an estimate of performance, and I want to display it in the graph of each iteration.
And I am using tensorflow
CostlyOstrich36 tensorflow reporting it, ClearML capture it, and I get it with that function.
In the init I passed output_uri=Folder
But now I have diffrent problem, in the dataset.get_mutable_local_copy
I get:
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/clearml/datasets/dataset.py", line 1276, in _download_part
raise ValueError("Could not download dataset id={} entry={}".format(self._id, data_artifact_name))
ValueError: Could not download dataset
CostlyOstrich36 thanks.
Maybe I should pass something in extra_docker_arguments in the config file?
And again only in docker mode CostlyOstrich36
I found the problem I think, thanks!
The sdk.aws.s3.credentials.0.host and sdk.aws.s3.credentials.0.key, yes
Hi CostlyOstrich36 CrookedWalrus33 AgitatedDove14
When I init an agent and run a task it works, but when I run the same task again it does not map the keys..
I need to change to pipe.set_default_execution_queue('services')?
or leave it defult?