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Fix SDK submodule update to handle commit SHAs #311

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Fix SDK submodule update to handle commit SHAs #311

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da5d75b
Fix SDK submodule update to handle commit SHAs
juanmichelini Jan 14, 2026
08ee261
fix(swebenchmultimodal): pass selected_instances_file to collect_uniq…
juanmichelini Jan 14, 2026
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8 changes: 6 additions & 2 deletions .github/workflows/build-swebenchmultimodal-images.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -161,8 +161,12 @@ jobs:
if: ${{ github.event_name == 'workflow_dispatch' && inputs.sdk-commit != '' }}
run: |
cd vendor/software-agent-sdk
git fetch origin ${{ inputs.sdk-commit }}
git checkout FETCH_HEAD
# Fetch from origin (handles both branch names and commit SHAs)
git fetch origin
# Try to fetch the specific ref (works for branches/tags)
git fetch origin ${{ inputs.sdk-commit }} 2>/dev/null || true
# Checkout the commit/ref (works for both branches and commit SHAs)
git checkout ${{ inputs.sdk-commit }}
SDK_SHA=$(git rev-parse HEAD)
cd ../..
# Stage the submodule reference update so make build uses it
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17 changes: 14 additions & 3 deletions benchmarks/swebenchmultimodal/build_images.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,9 +57,17 @@ def extract_custom_tag(base_image: str) -> str:
return name


def collect_unique_base_images(dataset, split, n_limit):
def collect_unique_base_images(
dataset,
split,
n_limit,
selected_instances_file: str | None = None,
):
df = get_dataset(
dataset_name=dataset, split=split, eval_limit=n_limit if n_limit else None
dataset_name=dataset,
split=split,
eval_limit=n_limit if n_limit else None,
selected_instances_file=selected_instances_file,
)
return sorted(
{get_official_docker_image(str(row["instance_id"])) for _, row in df.iterrows()}
Expand All @@ -71,7 +79,10 @@ def main(argv: list[str]) -> int:
args = parser.parse_args(argv)

base_images: list[str] = collect_unique_base_images(
args.dataset, args.split, args.n_limit
args.dataset,
args.split,
args.n_limit,
args.select,
)
build_dir = default_build_output_dir(args.dataset, args.split)
return build_all_images(
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