artifact loglikelihood results

.github/workflows/unit_tests.yml

@@ -70,3 +70,9 @@ jobs:
 #        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Test with pytest
       run: python -m pytest --showlocals -s -vv -n=auto --ignore=tests/tests_master --ignore=tests/extra
+    - name: Archive artifacts
+      uses: actions/upload-artifact@v3
+      with:
+        name: output_results
+        path: |
+          test_logs/*

tests/models/test_huggingface.py

 from __future__ import annotations
 import pytest
+from pathlib import Path
 import numpy as np
 from lm_eval.models.huggingface import HFLM
 from lm_eval.api.instance import Instance
 import lm_eval.tasks as tasks
+import sys
 import torch
 
 
 class Test_HFLM:
     torch.use_deterministic_algorithms(True)
+    version_minor = sys.version_info.minor
     multiple_choice_task = tasks.TASK_REGISTRY.get("arc_easy")()  # type: ignore
     multiple_choice_task.build_all_requests(limit=10, rank=0, world_size=1)
     MULTIPLE_CH: list[Instance] = multiple_choice_task.instances
@@ -91,7 +94,12 @@ class Test_HFLM:
     def test_logliklihood(self) -> None:
         res = self.LM.loglikelihood(self.MULTIPLE_CH)
         _RES, _res = self.MULTIPLE_CH_RES, [r[0] for r in res]
-        # change atol in case of consistent failure
+        # log samples to CI
+        file_path = Path(f"test_logs/outputs_log_{self.version_minor}.txt")
+        file_path.mkdir(parents=True, exist_ok=True)
+        file_path = file_path.resolve()
+        with open(file_path, "w") as f:
+            f.write("\n".join(str(x) for x in _res))
         assert np.allclose(_res, _RES, atol=1e-4)
         # check indices for Multiple Choice
         argmax_RES, argmax_res = np.argmax(