split llmcompressor from vllm checks

tests/e2e/integrations/test_llm_compressor.py

@@ -12,7 +12,11 @@ from axolotl.train import train
 from axolotl.utils.config import normalize_config, prepare_plugins, validate_config
 from axolotl.utils.dict import DictDefault
 
-from tests.e2e.utils import check_model_output_exists, require_torch_2_4_1
+from tests.e2e.utils import (
+    check_model_output_exists,
+    require_llmcompressor,
+    require_torch_2_4_1,
+)
 
 MODELS = [
     "nm-testing/llama2.c-stories42M-pruned2.4-compressed",
@@ -26,6 +30,7 @@ MODELS = [
 @pytest.mark.parametrize(
     "save_compressed", [True, False], ids=["save_compressed", "save_uncompressed"]
 )
+@require_llmcompressor
 class TestLLMCompressorIntegration:
     """
     e2e tests for axolotl.integrations.llm_compressor.LLMCompressorPlugin

tests/e2e/utils.py

@@ -109,6 +109,24 @@ def require_vllm(test_case):
     )(test_case)
 
 
+def require_llmcompressor(test_case):
+    """
+    Decorator marking a test that requires a llmcompressor to be installed
+    """
+
+    def is_llmcompressor_installed():
+        try:
+            import llmcompressor  # pylint: disable=unused-import  # noqa: F401
+
+            return True
+        except ImportError:
+            return False
+
+    return unittest.skipUnless(
+        is_llmcompressor_installed(), "test requires a llmcompressor to be installed"
+    )(test_case)
+
+
 def is_hopper():
     compute_capability = torch.cuda.get_device_capability()
     return compute_capability == (9, 0)