modify test units for the influence of __del__ of runner 2

tests/test_hooks/test_ema_hook.py

@@ -1,6 +1,8 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
 import os.path as osp
+import shutil
+import tempfile
 
 import torch
 import torch.nn as nn
@@ -219,57 +221,66 @@ def test_after_load_checkpoint(self):
     def test_with_runner(self):
         cfg = copy.deepcopy(self.epoch_based_cfg)
         cfg.custom_hooks = [ConfigDict(type='EMAHook')]
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         ema_hook = self._get_ema_hook(runner)
         runner.train()
+        epoch_pre_work_dir = cfg.work_dir + 'tmp'
+        shutil.copytree(cfg.work_dir, epoch_pre_work_dir)
         self.assertTrue(
             isinstance(ema_hook.ema_model, ExponentialMovingAverage))
 
-        checkpoint = torch.load(osp.join(self.temp_dir.name, 'epoch_2.pth'))
+        checkpoint = torch.load(osp.join(epoch_pre_work_dir, 'epoch_2.pth'))
         self.assertTrue('ema_state_dict' in checkpoint)
         self.assertTrue(checkpoint['ema_state_dict']['steps'] == 8)
 
         # load and testing
-        cfg.load_from = osp.join(self.temp_dir.name, 'epoch_2.pth')
+        cfg.load_from = osp.join(epoch_pre_work_dir, 'epoch_2.pth')
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.test()
 
         # with model wrapper
         cfg.model = ConfigDict(type='DummyWrapper', model=cfg.model)
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.test()
 
         # Test load checkpoint without ema_state_dict
-        checkpoint = torch.load(osp.join(self.temp_dir.name, 'epoch_2.pth'))
+        checkpoint = torch.load(osp.join(epoch_pre_work_dir, 'epoch_2.pth'))
         checkpoint.pop('ema_state_dict')
         torch.save(checkpoint,
-                   osp.join(self.temp_dir.name, 'without_ema_state_dict.pth'))
+                   osp.join(epoch_pre_work_dir, 'without_ema_state_dict.pth'))
 
-        cfg.load_from = osp.join(self.temp_dir.name,
+        cfg.load_from = osp.join(epoch_pre_work_dir,
                                  'without_ema_state_dict.pth')
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.test()
 
         # Test does not load checkpoint strictly (different name).
         # Test load checkpoint without ema_state_dict
         cfg.model = ConfigDict(type='ToyModel2')
         cfg.custom_hooks = [ConfigDict(type='EMAHook', strict_load=False)]
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.test()
 
         # Test does not load ckpt strictly (different weight size).
         # Test load checkpoint without ema_state_dict
         cfg.model = ConfigDict(type='ToyModel3')
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.test()
 
         # Test enable ema at 5 epochs.
         cfg.train_cfg.max_epochs = 10
         cfg.custom_hooks = [ConfigDict(type='EMAHook', begin_epoch=5)]
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.train()
         state_dict = torch.load(
-            osp.join(self.temp_dir.name, 'epoch_4.pth'), map_location='cpu')
+            osp.join(cfg.work_dir, 'epoch_4.pth'), map_location='cpu')
         self.assertIn('ema_state_dict', state_dict)
         for k, v in state_dict['state_dict'].items():
             assert_allclose(v, state_dict['ema_state_dict']['module.' + k])
@@ -279,15 +290,16 @@ def test_with_runner(self):
         cfg.train_cfg.val_interval = 1
         cfg.custom_hooks = [ConfigDict(type='EMAHook', begin_iter=5)]
         cfg.default_hooks.checkpoint.interval = 1
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.train()
         state_dict = torch.load(
-            osp.join(self.temp_dir.name, 'iter_4.pth'), map_location='cpu')
+            osp.join(cfg.work_dir, 'iter_4.pth'), map_location='cpu')
         self.assertIn('ema_state_dict', state_dict)
         for k, v in state_dict['state_dict'].items():
             assert_allclose(v, state_dict['ema_state_dict']['module.' + k])
         state_dict = torch.load(
-            osp.join(self.temp_dir.name, 'iter_5.pth'), map_location='cpu')
+            osp.join(cfg.work_dir, 'iter_5.pth'), map_location='cpu')
         self.assertIn('ema_state_dict', state_dict)
 
     def _test_swap_parameters(self, func_name, *args, **kwargs):

tests/test_hooks/test_empty_cache_hook.py

@@ -1,4 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
+import tempfile
 from unittest.mock import patch
 
 from mmengine.testing import RunnerTestCase
@@ -11,6 +12,7 @@ def test_with_runner(self):
             cfg = self.epoch_based_cfg
             cfg.custom_hooks = [dict(type='EmptyCacheHook')]
             cfg.train_cfg.val_interval = 1e6  # disable validation during training  # noqa: E501
+            cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
             runner = self.build_runner(cfg)
 
             runner.train()
@@ -26,6 +28,7 @@ def test_with_runner(self):
 
         with patch('torch.cuda.empty_cache') as mock_empty_cache:
             cfg.custom_hooks = [dict(type='EmptyCacheHook', before_epoch=True)]
+            cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
             runner = self.build_runner(cfg)
 
             runner.train()
@@ -45,6 +48,7 @@ def test_with_runner(self):
                 dict(
                     type='EmptyCacheHook', after_iter=True, before_epoch=True)
             ]
+            cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
             runner = self.build_runner(cfg)
 
             runner.train()

tests/test_hooks/test_param_scheduler_hook.py

@@ -1,5 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
+import tempfile
 from unittest.mock import Mock
 
 from mmengine.hooks import ParamSchedulerHook
@@ -144,6 +145,7 @@ def test_with_runner(self):
             )
         ]
         init_lr = cfg.optim_wrapper.optimizer.lr
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.train()
 
@@ -174,6 +176,7 @@ def test_with_runner(self):
         ]
 
         init_lr = cfg.optim_wrapper.optimizer.lr
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.train()
 

tests/test_hooks/test_profiler_hook.py

@@ -169,14 +169,18 @@ def test_with_runner(self):
                 activity_with_cpu=False,
                 activity_with_cuda=False)
         ]
-        runner = self.build_runner(self.epoch_based_cfg)
+        cfg = copy.deepcopy(self.epoch_based_cfg)
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
+        runner = self.build_runner(cfg)
         runner.train()
 
         json_path = ops.join(self.temp_dir.name, 'demo.json')
         self.epoch_based_cfg['custom_hooks'] = [
             dict(type='ProfilerHook', json_trace_path=json_path)
         ]
-        runner = self.build_runner(self.epoch_based_cfg)
+        cfg = copy.deepcopy(self.epoch_based_cfg)
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
+        runner = self.build_runner(cfg)
         runner.train()
         self.assertTrue(
             ops.exists(json_path), 'ERROR::json file is not generated!')
@@ -189,21 +193,27 @@ def test_with_runner(self):
                     sort_by='self_cpu_time_total',
                     row_limit=10))
         ]
-        runner = self.build_runner(self.epoch_based_cfg)
+        cfg = copy.deepcopy(self.epoch_based_cfg)
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
+        runner = self.build_runner(cfg)
         runner.train()
 
         with self.assertRaises(ValueError):
             self.epoch_based_cfg['custom_hooks'] = [
                 dict(type='ProfilerHook', on_trace_ready=0)
             ]
-            runner = self.build_runner(self.epoch_based_cfg)
+            cfg = copy.deepcopy(self.epoch_based_cfg)
+            cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
+            runner = self.build_runner(cfg)
             runner.train()
 
         if torch.cuda.is_available():
             self.epoch_based_cfg['custom_hooks'] = [
                 dict(type='ProfilerHook', activity_with_cuda=True)
             ]
-            runner = self.build_runner(self.epoch_based_cfg)
+            cfg = copy.deepcopy(self.epoch_based_cfg)
+            cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
+            runner = self.build_runner(cfg)
             runner.train()
 
 
@@ -271,7 +281,6 @@ def test_with_runner(self):
         cfg = copy.deepcopy(self.epoch_based_cfg)
         cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
-        runner = self.build_runner(self.epoch_based_cfg)
         runner.train()
 
         self.assertTrue(

tests/test_model/test_test_aug_time.py

@@ -1,5 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
+import tempfile
 
 import torch
 from torch.utils.data import DataLoader, Dataset
@@ -107,11 +108,13 @@ def test_with_runner(self):
             type='ToyTestTimeAugModel', module=dict(type='ToyModel'))
         cfg.test_dataloader.dataset = dict(type='ToyDatasetTTA')
         cfg.test_dataloader.dataset['pipeline'] = dict(type='ToyTTAPipeline')
+        cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
         runner = self.build_runner(cfg)
         runner.test()
 
         if torch.cuda.is_available() and torch.distributed.is_nccl_available():
             cfg.launcher = 'pytorch'
             self.setup_dist_env()
+            cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir.name)
             runner = self.build_runner(cfg)
             runner.test()

tests/test_runner/test_runner.py

@@ -2505,9 +2505,9 @@ def test_checkpoint(self):
 
         resumed_cfg.experiment_name = 'test_checkpoint17'
         resumed_cfg.work_dir = tempfile.mkdtemp(dir=self.temp_dir)
-        shutil.rmtree(cfg.work_dir)
-        shutil.copytree(gan_epoch_pre_work_dir, cfg.work_dir)
-        path = osp.join(cfg.work_dir, 'epoch_3.pth')
+        shutil.rmtree(resumed_cfg.work_dir)
+        shutil.copytree(gan_epoch_pre_work_dir, resumed_cfg.work_dir)
+        path = osp.join(resumed_cfg.work_dir, 'epoch_3.pth')
         runner = Runner.from_cfg(resumed_cfg)
         runner.resume(path)
         self.assertEqual(len(runner.param_schedulers['linear1']), 1)