Hi ShallowCormorant89 ,
When does 1. happen? Can you add the full log?
Regarding 2, can you please elaborate? What is your pipeline doing and what sort of configurations would you want to add? On the pipeline controller level or steps?
hello AgitatedDove14
thanks for your reply.
yes, the HTTP link is valid I was able to download it using wget I'm doubtful if it was an inconsistency
right now this seems to be solved for me.
previously I was using ${V3M_step.artifacts.Detections} - which will return a dictionary
on changing it to ${V3M_step.artifacts.Detections.url} (the url of the artifact) is returned and this seemed to have helped.
hello again,
It will be helpful to know why we experience this when running a pipeline2022-12-19 15:13:47,884 - clearml - WARNING - Could not retrieve remote configuration named 'RUN_CONFIG'
- how do I add a configuration object to a pipeline.
the dictionary is split into multiple values.. when using it as a param in the pipeline
Hey CostlyOstrich36
Happens when I try to execute a pipeline remotely.2022-12-19 15:13:47,884 - clearml - WARNING - Could not retrieve remote configuration named 'RUN_CONFIG' Using default configuration: {...}It happens in my pipeline and here is the code :
` pipe = PipelineController(
name="mypipe", project="myproject", version="0.0.1", add_pipeline_tags=False
)
pipe.set_default_execution_queue("default")
my_json = "jsons/my_json.json"
clearml_input_path = "jsons/clearml_input.json"
my_json = load_json_if_path(my_json)
clearml_input_path = load_json_if_path(clearml_input_path)
pipe.add_parameter(name="my_json", default=my_json, param_type='dictionary')
pipe.add_parameter(name="RUN_CONFIG", default=clearml_input_path, param_type='dictionary')
pipe.add_step(
name="my_Step_1",
base_task_project="my_1",
base_task_id="e82582054be642e38541ab06770",
execution_queue="my_queue",
configuration_overrides={"my_json": "${pipeline.my_json}",
'RUN_CONFIG': "${pipeline.RUN_CONFIG}"}
)
pipe.add_step(
name="my_Step_2",
parents=["my_Step_1"],
base_task_project="my_2",
base_task_id="703cdbd4f46f4386b4e338f56f34",
execution_queue="my_queue",
parameter_override={"INPUTS/detection_file_path" : "${my_Step_1.artifacts.Detections.url}"},
configuration_overrides={
"my_json": "${pipeline.my_json}",
'RUN_CONFIG': "${pipeline.RUN_CONFIG}"
}
)
pipe.start()
print("done") I want my_json and RUN_CONFIG ` to be configuration object in a pipeline. (so that we can paste our dictionarys)
thank you for your help!
Hi ShallowCormorant89
Can you verify the http link is valid? Can you download it from code on your machine (i.e. not via an agent), maybe 8081 port is blocked from the agent machine to the server?
