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amygdala: drop linear_aggregator, not in steering-vectors v0.12.2

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Only mean/pca/logistic are exposed in the installed version.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
This commit is contained in:
Kent Overstreet 2026-04-18 22:17:55 -04:00
parent 3377c65061
commit 2ea89b1cb0
1 changed files with 1 additions and 4 deletions
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5
training/amygdala_training/train_with_library.py
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@ -41,7 +41,6 @@ from steering_vectors.aggregators import (
mean_aggregator, mean_aggregator,
pca_aggregator, pca_aggregator,
logistic_aggregator, logistic_aggregator,
linear_aggregator,
) )
# Reuse corpus loader from the hand-rolled trainer. # Reuse corpus loader from the hand-rolled trainer.
@ -96,8 +95,6 @@ def _aggregator_from_name(name: str):
return logistic_aggregator( return logistic_aggregator(
sklearn_kwargs={"penalty": "l1", "solver": "liblinear", "C": 0.1} sklearn_kwargs={"penalty": "l1", "solver": "liblinear", "C": 0.1}
) )
if name == "linear":
return linear_aggregator()
raise ValueError(f"unknown aggregator: {name}") raise ValueError(f"unknown aggregator: {name}")
@ -116,7 +113,7 @@ def main() -> None:
ap.add_argument( ap.add_argument(
"--aggregator", "--aggregator",
default="mean", default="mean",
choices=["mean", "pca", "logistic", "logistic_l1", "linear"], choices=["mean", "pca", "logistic", "logistic_l1"],
) )
ap.add_argument("--max-negatives-per-positive", type=int, default=3) ap.add_argument("--max-negatives-per-positive", type=int, default=3)
args = ap.parse_args() args = ap.parse_args()