Use tmp dir as work_dir of runner (#236)

* use tmp dir as work_dir of runner

* only run codecov for python 3.7

* remove useless comments

.travis.yml

@@ -34,7 +34,7 @@ script: coverage run --branch --source=mmcv -m pytest tests/
 
 after_success:
   - coverage report -m
-  - codecov
+  - if [[ $TRAVIS_PYTHON_VERSION == "3.7" ]]; then codecov; fi
 
 deploy:
   provider: pypi

tests/test_hooks.py

@@ -6,8 +6,11 @@ CommandLine:
     xdoctest tests/test_hooks.py zero
 
 """
+import logging
 import os.path as osp
+import shutil
 import sys
+import tempfile
 from unittest.mock import MagicMock, call
 
 import pytest
@@ -27,6 +30,7 @@ def test_pavi_hook():
         add_graph=False, add_last_ckpt=True)
     runner.register_hook(hook)
     runner.run([loader, loader], [('train', 1), ('val', 1)], 1)
+    shutil.rmtree(runner.work_dir)
 
     assert hasattr(hook, 'writer')
     hook.writer.add_scalars.assert_called_with('val', {
@@ -34,7 +38,7 @@ def test_pavi_hook():
         'momentum': 0.95
     }, 5)
     hook.writer.add_snapshot_file.assert_called_with(
-        tag='data',
+        tag=runner.work_dir.split('/')[-1],
         snapshot_file_path=osp.join(runner.work_dir, 'latest.pth'),
         iteration=5)
 
@@ -69,6 +73,7 @@ def test_momentum_runner_hook():
         interval=1, add_graph=False, add_last_ckpt=True)
     runner.register_hook(hook)
     runner.run([loader], [('train', 1)], 1)
+    shutil.rmtree(runner.work_dir)
 
     # TODO: use a more elegant way to check values
     assert hasattr(hook, 'writer')
@@ -117,6 +122,7 @@ def test_cosine_runner_hook():
         interval=1, add_graph=False, add_last_ckpt=True)
     runner.register_hook(hook)
     runner.run([loader], [('train', 1)], 1)
+    shutil.rmtree(runner.work_dir)
 
     # TODO: use a more elegant way to check values
     assert hasattr(hook, 'writer')
@@ -149,6 +155,7 @@ def test_mlflow_hook(log_model):
         exp_name='test', log_model=log_model)
     runner.register_hook(hook)
     runner.run([loader, loader], [('train', 1), ('val', 1)], 1)
+    shutil.rmtree(runner.work_dir)
 
     hook.mlflow.set_experiment.assert_called_with('test')
     hook.mlflow.log_metrics.assert_called_with(
@@ -171,6 +178,8 @@ def test_wandb_hook():
 
     runner.register_hook(hook)
     runner.run([loader, loader], [('train', 1), ('val', 1)], 1)
+    shutil.rmtree(runner.work_dir)
+
     hook.wandb.init.assert_called_with()
     hook.wandb.log.assert_called_with({
         'learning_rate': 0.02,
@@ -182,7 +191,6 @@ def test_wandb_hook():
 
 def _build_demo_runner():
     model = nn.Linear(2, 1)
-    work_dir = osp.join(osp.dirname(osp.abspath(__file__)), 'data')
     optimizer = torch.optim.SGD(model.parameters(), lr=0.02, momentum=0.95)
 
     log_config = dict(
@@ -190,11 +198,13 @@ def _build_demo_runner():
             dict(type='TextLoggerHook'),
         ])
 
+    tmp_dir = tempfile.mkdtemp()
     runner = mmcv.runner.Runner(
         model=model,
-        work_dir=work_dir,
+        work_dir=tmp_dir,
         batch_processor=lambda model, x, **kwargs: {'loss': model(x) - 0},
-        optimizer=optimizer)
+        optimizer=optimizer,
+        logger=logging.getLogger())
 
     runner.register_logger_hooks(log_config)
     return runner

tests/test_runner.py

 # Copyright (c) Open-MMLab. All rights reserved.
+import logging
 import os.path as osp
 import tempfile
 import warnings
@@ -15,7 +16,8 @@ def test_save_checkpoint():
     import mmcv.runner
 
     model = nn.Linear(1, 1)
-    runner = mmcv.runner.Runner(model=model, batch_processor=lambda x: x)
+    runner = mmcv.runner.Runner(
+        model=model, batch_processor=lambda x: x, logger=logging.getLogger())
 
     with tempfile.TemporaryDirectory() as root:
         runner.save_checkpoint(root)