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Update autotune_scvi.ipynb
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ori-kron-wis authored Oct 9, 2024
1 parent 8f7c7c7 commit 74bf9f6
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6 changes: 3 additions & 3 deletions tuning/autotune_scvi.ipynb
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"source": [
"search_space = {\n",
" \"model_params\": {\"n_hidden\": tune.choice([64, 128, 256]), \"n_layers\": tune.choice([1, 2, 3])},\n",
" \"train_params\": {\"max_epochs\": 100},\n",
" \"train_params\": {\"max_epochs\": 100, \"plan_kwargs\": {\"lr\": tune.loguniform(1e-4, 1e-2)}},\n",
"}"
]
},
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"source": [
"There are a couple more arguments we should be aware of before fitting the tuner:\n",
"\n",
"- `num_samples`: The total number of hyperparameter sets to sample from `search_space`. This is the total number of models that will be trained.\n",
"- `num_samples`: The total number of hyperparameter sets to sample from ``. This is the total number of models that will be trained.\n",
"\n",
" For example, if we set `num_samples=2`, we might sample two models with the following hyperparameter configurations:\n",
" For example, if we set `num_samples=2`, based on the above search space, we might sample two models with the following hyperparameter configurations:\n",
"\n",
" ```python\n",
" model1 = {\n",
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