How can I stop clearml from uploading temporary models?
I am running cross_validation, training a bunch of models in a loop like this:
models = []
for X_train, Y_train, X_test, Y_test in cv:
model = TempModel()
model.fit(X_train, Y_train)
model.eval(X_test, Y_test)
models.append(model)
final_model = get_final_model(models)
joblib.dump(final_model, 'model.joblib')
What happens: ClearML uploads each model from inside the loop
What I want: only upload the model I explicitly dump, the final model
How can I control this behaviour?
I am running cross_validation, training a bunch of models in a loop like this:
Use the wildcard or disable all together:
task = Task.init(..., auto_connect_frameworks={"joblib": False})
You can also do
task = Task.init(..., auto_connect_frameworks={"joblib": ["realmodelonly.pkl", ]})
should be the full path, or just the file name?
just file name, this is basically fname matching
"realmodelonly.pkl"
should be the full path, or just the file name?