CostlyOstrich36

MelancholyElk85 So I need to change the paths each time?

Or do I have to dive into the code in train function and write the code there?

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 I get the last iteration by task.get_last_iteration()
I want to report each iteration..

CostlyOstrich36

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..

The second run:

The first run:

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 When I do

logger = task.get_logger()
logger.report_scalar(title='evaluate', series='score', value=5, iteration=task.get_last_iteration())
train(model_dir=trained_model_dst, pipeline_config_path=pipeline_config_path, save_checkpoints_steps=args.checkpoints)

It only captures the first iteration...

CostlyOstrich36 tensorflow reporting it, ClearML capture it, and I get it with that function.

SuccessfulKoala55
Hi,
Using task.upload_artifact

CostlyOstrich36 Not sure I understood, the current iterations come from the function
task.get_last_iteration() ...

I have nowhere else to bring iteration number ..

OK, thanks!!

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 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())

Hi CostlyOstrich36 ,

MelancholyElk85 How do I change the SCRIPT PATH/SCRIPT PATH

Yes

AgitatedDove14 Yes,
I use add step

In the init I passed output_uri=Folder

Hi SuccessfulKoala55 ,
First I create the task and change the output_uri to some folder I created
task = Task.init(project_name='main', task_name='task', output_uri=r'C:\Users\Chen\Desktop\folder)Than I used:
task.upload_artifact

CostlyOstrich36

MelancholyElk85 Thanks,
I will try!

Regular folder...

Now, in other task I want to upload the artifact by using get_local_copy()
dataset_upload_task = Task.get_task(task_id=args['dataset_task_id']) local_json = dataset_upload_task.artifacts['dataset'].get_local_copy()But the path that I got contain '' and '/' (i.e combination of unix and win foramt)

CostlyOstrich36 having the reported tensorflow scalars show up on ClearML

pipe = PipelineController( name='grab2train_tf', project='main pipeline', version='0.0.1', abort_on_failure=True, # any failed step will cause the pipeline to immediately abort, stop all running steps, and mark the pipeline as failed. )
I'm missing something? CostlyOstrich36