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33 lines
1.6 KiB
YAML
33 lines
1.6 KiB
YAML
# Generalized normal sweep across mixings (main-text figure)
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# python run.py --config configs/gennorm.yaml --run spiral_lejepa --alpha 2.0 --seed 1337
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experiment: gennorm
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out: results/gennorm
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N: 2
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source_dist: gennorm # alpha provided per-run via CLI
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num_eval: 10000
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steps: 20000
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lr: 3.0e-3
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batch_size: 256
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rho: 0.95
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log_every: 500
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runs:
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spiral_lejepa: {mixing: spiral, encoder: mlp, hidden: 256, mode: lejepa, lamb: 1.0e-3}
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spiral_whiten: {mixing: spiral, encoder: mlp, hidden: 256, mode: whiten, lamb: 0.5}
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spiral_infonce: {mixing: spiral, encoder: mlp, hidden: 256, mode: infonce, sigma: 1.0}
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banana_lejepa: {mixing: banana, encoder: mlp, hidden: 256, mode: lejepa, lamb: 1.0e-3}
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banana_whiten: {mixing: banana, encoder: mlp, hidden: 256, mode: whiten, lamb: 0.5}
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banana_infonce: {mixing: banana, encoder: mlp, hidden: 256, mode: infonce, sigma: 1.0}
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sinusoid_lejepa: {mixing: sinusoid, encoder: mlp, hidden: 256, mode: lejepa, lamb: 1.0e-3}
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sinusoid_whiten: {mixing: sinusoid, encoder: mlp, hidden: 256, mode: whiten, lamb: 0.5}
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sinusoid_infonce: {mixing: sinusoid, encoder: mlp, hidden: 256, mode: infonce, sigma: 1.0}
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nvp_lejepa: {mixing: nvp, encoder: matched, n_layers: 8, mode: lejepa, lamb: 1.0e-3}
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nvp_whiten: {mixing: nvp, encoder: matched, n_layers: 8, mode: whiten, lamb: 0.5}
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nvp_infonce: {mixing: nvp, encoder: matched, n_layers: 8, mode: infonce, sigma: 1.0}
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alphas: [0.125, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0, 32.0]
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seeds: [1337, 1338, 1339]
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