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Cache angle onnx #1108

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Cache angle onnx #1108

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44d3f7d
feat: add caching for Hugging Face hub in test workflow
cpaniaguam Jul 27, 2026
5a4044f
fix: update ONNX model path to use a local fixture for CI consistency
cpaniaguam Jul 27, 2026
af938b7
fix: correct cache path for Hugging Face hub in test workflow
cpaniaguam Jul 27, 2026
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8 changes: 8 additions & 0 deletions .github/workflows/run_tests.yml
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Expand Up @@ -36,6 +36,14 @@ jobs:
with:
python-version: ${{ matrix.python-version }}

- name: Cache Hugging Face hub

@digicosmos86 digicosmos86 Aug 4, 2026

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I think this is a different caching mechanism here than what we want to achieve. This gets us caching across different runs, so that we don't have to download the onnx files again. However, since the onnx models are so small, I am not sure this is necessary. Can we spend some time looking into why the hf_download call is not cached during testing?

@cpaniaguam cpaniaguam Aug 4, 2026

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Sure, we can address this later.

uses: actions/cache@v4
with:
path: ~/.cache/huggingface/hub
key: ${{ runner.os }}-huggingface-hub-v1
restore-keys: |
${{ runner.os }}-huggingface-hub-

- name: Run fast tests
if: ${{ !inputs.run_slow_tests }}
run: uv run pytest -m "not slow" $HSSM_TEST_ARGS
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5 changes: 4 additions & 1 deletion tests/rl/test_rl_likelihood_builder.py
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Expand Up @@ -29,9 +29,12 @@
from hssm.rl.likelihoods.two_armed_bandit import compute_v_subject_wise
from hssm.utils import annotate_function

# Use a local fixture to keep CI deterministic and avoid Hugging Face rate limits.
ANGLE_ONNX = Path(__file__).parent.parent / "fixtures" / "angle.onnx"

# Obtain the angle log-likelihood function from an ONNX model.
angle_logp_jax_func = make_jax_matrix_logp_funcs_from_onnx(
model="angle.onnx",
model=ANGLE_ONNX,
)

hssm.set_floatX("float32")
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