[Testing] Reduce error verbosity of cleanup

tests/e2e/vLLM/test_vllm.py

@@ -170,7 +170,7 @@ def test_vllm(self, test_data_file: str):
         self.tear_down()
 
     def tear_down(self):
-        if self.save_dir is not None:
+        if self.save_dir is not None and os.path.isdir(self.save_dir):
             shutil.rmtree(self.save_dir)
 
         timer = get_singleton_manager()

tests/llmcompressor/transformers/compression/test_decompress.py

@@ -1,4 +1,5 @@
 import copy
+import os
 import shutil
 import tempfile
 import unittest
@@ -128,7 +129,8 @@ def test_hf_quantizer_decompress_match_manual_decompress(self):
 
     @classmethod
     def tearDownClass(self):
-        shutil.rmtree(self.test_dir)
+        if os.path.isdir(self.test_dir):
+            shutil.rmtree(self.test_dir)
         del self.dense_model
         del self.decompressed_model_hf_quantizer
         del self.decompressed_model_manual

tests/llmcompressor/transformers/compression/test_quantization.py

@@ -49,7 +49,8 @@ def setUpClass(cls):
 
     @classmethod
     def tearDownClass(cls):
-        shutil.rmtree(cls.test_dir)
+        if os.path.isdir(cls.test_dir):
+            shutil.rmtree(cls.test_dir)
         del cls.model
         torch.cuda.empty_cache()
 

tests/llmcompressor/transformers/compression/test_run_compressed.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import tempfile
 import unittest
@@ -82,7 +83,8 @@ def test_compressed_matches_decompressed(self):
 
     @classmethod
     def tearDownClass(cls):
-        shutil.rmtree(cls.test_dir)
+        if os.path.isdir(cls.test_dir):
+            shutil.rmtree(cls.test_dir)
         del cls.decompressed_model
         del cls.uncompressed_model
         torch.cuda.empty_cache()
@@ -167,7 +169,8 @@ def test_compressed_matches_decompressed__hf_quantizer(self):
 
     @classmethod
     def tearDownClass(cls):
-        shutil.rmtree(cls.test_dir)
+        if os.path.isdir(cls.test_dir):
+            shutil.rmtree(cls.test_dir)
         del cls.decompressed_model
         del cls.compressed_model
         torch.cuda.empty_cache()

tests/llmcompressor/transformers/finetune/test_finetune_no_recipe_custom_dataset.py

@@ -107,7 +107,8 @@ def create_mock_file(self, extension, content, path, filename):
         return mock_filepath  # Return the file path
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)
 
 
 @pytest.mark.integration

tests/llmcompressor/transformers/finetune/test_finetune_oneshot_with_modifier.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 from pathlib import Path
@@ -46,4 +47,5 @@ def test_oneshot_with_modifier_object(self):
         )
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/finetune/test_finetune_without_recipe.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 
@@ -41,4 +42,5 @@ def test_finetune_without_recipe(self):
         )
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/finetune/test_oneshot_and_finetune.py

@@ -75,7 +75,8 @@ def _test_oneshot_and_finetune(self):
     def tearDown(self):
         # TODO: we get really nice stats from finetune that we should log
         # stored in results.json
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)
 
 
 @pytest.mark.integration

tests/llmcompressor/transformers/finetune/test_oneshot_and_finetune_with_tokenizer.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 
@@ -78,4 +79,5 @@ def test_oneshot_and_finetune_with_tokenizer(self):
         print(tokenizer.decode(output[0]))
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/finetune/test_oneshot_then_finetune.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 from pathlib import Path
@@ -175,4 +176,5 @@ def test_oneshot_quantization_then_finetune(self):
             )
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/finetune/test_safetensors.py

@@ -53,4 +53,5 @@ def test_safetensors(self):
         )
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/gptq/test_oneshot.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 
@@ -113,4 +114,5 @@ def test_oneshot_application(self):
         assert not hasattr(not_targetted, "quantization_scheme")
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/obcq/test_consecutive_runs.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 from pathlib import Path
@@ -109,7 +110,8 @@ def _test_consecutive_runs(
         self.assertEqual(stage1_modifier_names, exp_stage1_modifier_names)
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)
 
 
 @pytest.mark.integration

tests/llmcompressor/transformers/obcq/test_obcq_completion.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 
@@ -90,7 +91,8 @@ def _test_oneshot_completion(self, model_name: str = None):
         self.assertLess(avg_new_ppl, self.perplexity)
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)
 
 
 @requires_gpu

tests/llmcompressor/transformers/obcq/test_obcq_sparsity.py

@@ -1,4 +1,5 @@
 import math
+import os
 import shutil
 import unittest
 
@@ -48,7 +49,8 @@ def test_sparsities(self):
     def tearDown(self):
         import torch
 
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)
         torch.cuda.empty_cache()
 
 
@@ -97,5 +99,6 @@ def test_sparsities_gpu(self):
     def tearDown(self):
         import torch
 
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)
         torch.cuda.empty_cache()

tests/llmcompressor/transformers/oneshot/test_api_inputs.py

@@ -1,3 +1,4 @@
+import os
 import shutil
 import unittest
 
@@ -62,4 +63,5 @@ def test_one_shot_inputs(self):
         )
 
     def tearDown(self):
-        shutil.rmtree(self.output)
+        if os.path.isdir(self.output):
+            shutil.rmtree(self.output)

tests/llmcompressor/transformers/sparsification/test_compress_tensor_utils.py

@@ -1,4 +1,5 @@
 import math
+import os
 import shutil
 
 import pytest
@@ -115,7 +116,8 @@ def test_sparse_model_reload(compressed, config, dtype, tmp_path):
         assert dense_tensor.dtype == reconstructed_tensor.dtype == dtype
         assert torch.equal(dense_tensor, reconstructed_tensor)
 
-    shutil.rmtree(tmp_path)
+    if os.path.isdir(tmp_path):
+        shutil.rmtree(tmp_path)
 
 
 @pytest.mark.parametrize(
@@ -145,7 +147,8 @@ def test_dense_model_save(tmp_path, skip_compression_stats, save_compressed):
     sparsity_config = ModelCompressor.parse_sparsity_config(compression_config)
     assert sparsity_config is None
 
-    shutil.rmtree(tmp_path)
+    if os.path.isdir(tmp_path):
+        shutil.rmtree(tmp_path)
 
 
 @pytest.mark.parametrize(
@@ -223,7 +226,8 @@ def test_quant_model_reload(format, dtype, tmp_path):
             assert not torch.any(diff > 0.01).item()
         else:
             assert torch.equal(dense_tensor, reconstructed_tensor)
-    shutil.rmtree(tmp_path)
+    if os.path.isdir(tmp_path):
+        shutil.rmtree(tmp_path)
 
 
 # technically only tie_word_embeddings=False is supported right now
@@ -435,7 +439,8 @@ def test_compressor_stacking(model_stub, recipe, sparse_format, quant_format, tm
             assert not torch.any(diff > 0.025), f"Max diff: {torch.max(diff)}"
         else:
             assert torch.equal(dense_tensor, reconstructed_tensor)
-    shutil.rmtree(tmp_path)
+    if os.path.isdir(tmp_path):
+        shutil.rmtree(tmp_path)
 
 
 @pytest.mark.parametrize(
@@ -503,7 +508,8 @@ def test_sparse_24_compressor_is_lossless(model_stub, recipe, sparse_format, tmp
         assert dense_tensor.dtype == reconstructed_tensor.dtype
         if key.endswith("weight"):
             assert torch.equal(dense_tensor, reconstructed_tensor)
-    shutil.rmtree(tmp_path)
+    if os.path.isdir(tmp_path):
+        shutil.rmtree(tmp_path)
 
 
 def test_disable_sparse_compression_flag(tmp_path):
@@ -530,7 +536,8 @@ def test_disable_sparse_compression_flag(tmp_path):
 
     assert sparsity_config
     assert sparsity_config["format"] == "dense"
-    shutil.rmtree(tmp_path)
+    if os.path.isdir(tmp_path):
+        shutil.rmtree(tmp_path)
 
 
 class DummyLinearModel(nn.Module):

tests/lmeval/test_lmeval.py

@@ -175,5 +175,5 @@ def tear_down(self):
             df = pd.DataFrame(measurements)
             df.to_csv(p / f"{self.save_dir}.csv", index=False)
 
-        if self.save_dir is not None:
+        if self.save_dir is not None and os.path.isdir(self.save_dir):
             shutil.rmtree(self.save_dir)