I tried this, but didn’t help:
input_models = current_task.models["input"] if len(input_models) == 1: input_model_as_input = {"name": input_models[0].name, "type": ModelTypeEnum.input} response = current_task.send(DeleteModelsRequest( task=current_task.task_id, models=[input_model_as_input] ))

I am not registering a model explicitly in apply_model . I guess it is done automatically when I do this:
output_models = train_task_with_model.models["output"] model_descriptor = output_models[0] model_filename = model_descriptor.get_local_copy()

I guess you can easily reproduce it by cloning any task which has an input model - logs, hyperparams etc are being reset, but inputmodel stays.

hi FiercePenguin76
Can you also send your clearml packages versions ?
I would like to sum your issue up , so that you could check i got it right

you have a task that has a model, that you use to make some inference on a dataset you clone the task, and would like to make inferences on the dataset, but with another modelthe problem is that you have a cloned task with the first model....

How have you registered the second model ? Also can you share your logs ?

I had a bunch of training tasks each of which outputted a model. I want to apply each one of them to a specific dataset. I have a clearml task ( apply_model ) for that, which takes dataset_id and model-producing task_id as input. First time I initiate apply model by hardcoding ids and starting the run from my machine (it is then goes into cloud, when it reaches execute_remotely )

also, I don’t see an edit button near input models

SmugDolphin23 sorry I don’t get how this will help with my problem

FiercePenguin76 Looks like there is actually a bug when loading models remotely. We will try to fix this asap

no, I’m providing the id of task which generated the model as a “hyperparam”

MotionlessCoral18 If you provide the model as a hyperparam, then I believe you should query its value by calling https://clear.ml/docs/latest/docs/references/sdk/task/#get_parameters or https://clear.ml/docs/latest/docs/references/sdk/task/#get_parameter

all subsequent invocations are done by cloning this task in UI and changing the model task_id

in cloned tasks, the correct model is being applied, but the original one stays registered as input model

FiercePenguin76 Are you changing the model by pressing the circled button in the first photo? Are you promted with a menu like in the second photo?

clearml==1.5.0
WebApp: 1.5.0-192 Server: 1.5.0-192 API: 2.18

thanks for all those precisions. I will try to reproduce and keep you updated 🙂