|
|
@ -15,10 +15,10 @@ job_plugin = studio.installed_plugins["jobs"] |
|
|
# do a sweep over learning rates |
|
|
# do a sweep over learning rates |
|
|
|
|
|
|
|
|
# Define the ranges or sets of values for each hyperparameter |
|
|
# Define the ranges or sets of values for each hyperparameter |
|
|
alpha_values = [0.1, 0.3, 0.5, 0.7, 0.9] |
|
|
alpha_values = [0.1, 0.25, 0.5, 0.7, 0.9] |
|
|
learning_rate_values = [1e-6, 1e-5, 1e-4, 1e-3, 1e-2] |
|
|
learning_rate_values = [1e-3, 1e-4, 1e-5] |
|
|
batch_size_values = [32, 64, 128] |
|
|
batch_size_values = [128] |
|
|
max_epochs_values = [1000] |
|
|
max_epochs_values = [5000] |
|
|
|
|
|
|
|
|
# Generate all possible combinations of hyperparameters |
|
|
# Generate all possible combinations of hyperparameters |
|
|
all_params = [ |
|
|
all_params = [ |
|
|
@ -36,5 +36,7 @@ search_params = sample(all_params, NUM_JOBS) |
|
|
for idx, params in enumerate(search_params): |
|
|
for idx, params in enumerate(search_params): |
|
|
a, lr, bs, me = params |
|
|
a, lr, bs, me = params |
|
|
cmd = f"cd ~/colors && python main.py --alpha {a} --lr {lr} --bs {bs} --max_epochs {me}" |
|
|
cmd = f"cd ~/colors && python main.py --alpha {a} --lr {lr} --bs {bs} --max_epochs {me}" |
|
|
job_name = f"color_{bs}_{a}_{lr:2.2e}" |
|
|
job_name = f"color2_{bs}_{a}_{lr:2.2e}" |
|
|
job_plugin.run(cmd, machine=Machine.T4, name=job_name) |
|
|
# job_plugin.run(cmd, machine=Machine.T4, name=job_name) |
|
|
|
|
|
print(f"Running {params}: {cmd}") |
|
|
|
|
|
os.system(cmd) |
|
|
|
