Mutually exclusive parameters for sweeps

Can I pass exclusive parameters for a sweep? E.g. for a particular pre-trained model, I want to try learning rate values of [0.1, 0.2]. For another model I want to use [0.3, 0.4]. if I use the sweep configuration below, then grid search will try all the four learning rate values for each model. However, for model 1 - I want to use a learning rate of 0.1, 0.2 whereas, for model2, I want to use 0.3, 0.4.

project: my_project
program: main.py
name: grid_search
method: grid
parameters:
learning_rate:
values: [0.1, 0.2, 0.3, 0.4]
arch:
values: [‘model1’, ‘model2’]

Hi @hsingh-utd,
Are you hoping for model1 to always receive [0.1, 0.2] or would you like the sweep to pair [0.3, 0.4] with model1 at some point during the sweep?

For instance, you could say values:{(0.1, 0.2), (0.3, 0.4)] to give model1 either one of the sets at any point.

Or if you would like try different combinations of the 2 different learning rates you could use

learning_rate_1:
values: [0.1, 0.2, 0.3, 0.4]
learning_rate_2:
values: [0.1, 0.2, 0.3, 0.4]

Feel free to clarify your goal if I’m not pointing you in the right direction.

Thank you,
Nate

Hi @hsingh-utd, I wanted to follow up and see if you were still looking for help with this?

Thank you,
Nate