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38 lines
1.4 KiB
38 lines
1.4 KiB
from lightning_sdk import Studio, Machine
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from random import sample
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NUM_JOBS = 4
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# reference to the current studio
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# if you run outside of Lightning, you can pass the Studio name
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studio = Studio()
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# use the jobs plugin
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studio.install_plugin('jobs')
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job_plugin = studio.installed_plugins['jobs']
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# do a sweep over learning rates
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# Define the ranges or sets of values for each hyperparameter
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alpha_values = [0.1, 0.3, 0.5, 0.7, 0.9]
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distinct_threshold_values = [0.5, 0.6, 0.7, 0.8]
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learning_rate_values = [1e-6, 1-e5, 1e-4, 1e-3, 1e-2]
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batch_size_values = [32, 64, 128]
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max_epochs_values = [10000]
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# Generate all possible combinations of hyperparameters
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all_params = [(alpha, dt, lr, bs, me) for alpha in alpha_values
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for dt in distinct_threshold_values
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for lr in learning_rate_values
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for bs in batch_size_values
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for me in max_epochs_values]
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# perform random search with a limit
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random_search_params = sample(search_params, NUM_JOBS)
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# start all jobs on an A10G GPU with names containing an index
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for idx, (a, thresh, lr, bs, max_epochs) in enumerate(search_params):
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cmd = f'python main.py --alpha {a} -D {thresh} --lr {lr} --bs {bs} --max_epochs {max_epochs}'
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job_name = f'color-exp-{idx}'
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job_plugin.run(cmd, machine=Machine.T4, name=job_name)
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