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50 lines
1.4 KiB
50 lines
1.4 KiB
import subprocess
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import sys
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from random import sample
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import numpy as np
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from lightning_sdk import Machine, Studio # noqa: F401
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NUM_JOBS = 64
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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 = list(np.round(np.linspace(0, 2, 21), 4))
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learning_rate_values = [1e-3, 1e-4, 1e-5]
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batch_size_values = [128]
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max_epochs_values = [5000]
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# Generate all possible combinations of hyperparameters
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all_params = [
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(alpha, lr, bs, me)
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for alpha in alpha_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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]
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# perform random search with a limit
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search_params = sample(all_params, min(NUM_JOBS, len(all_params)))
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for idx, params in enumerate(search_params):
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a, lr, bs, me = params
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cmd = f"cd ~/colors && python main.py --alpha {a} --lr {lr} --bs {bs} --max_epochs {me}"
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job_name = f"color2_{bs}_{a}_{lr:2.2e}"
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# job_plugin.run(cmd, machine=Machine.T4, name=job_name)
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print(f"Running {params}: {cmd}")
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try:
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# Run the command and wait for it to complete
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subprocess.run(cmd, shell=True, check=True)
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except KeyboardInterrupt:
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print("Interrupted by user")
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sys.exit(1)
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