Make latest checkpoint symlink relative (#75)

* Make latest symlink relative. Add tests

* Skip test_save_checkpoint in the absense of torch

* Fix pep8 in test_runner

* Import runner only if torch import has succeeded

mmcv/runner/runner.py

@@ -243,11 +243,13 @@ class Runner(object):
         else:
             meta.update(epoch=self.epoch + 1, iter=self.iter)
 
-        filename = osp.join(out_dir, filename_tmpl.format(self.epoch + 1))
-        linkname = osp.join(out_dir, 'latest.pth')
+        filename = filename_tmpl.format(self.epoch + 1)
+        filepath = osp.join(out_dir, filename)
+        linkpath = osp.join(out_dir, 'latest.pth')
         optimizer = self.optimizer if save_optimizer else None
-        save_checkpoint(self.model, filename, optimizer=optimizer, meta=meta)
-        mmcv.symlink(filename, linkname)
+        save_checkpoint(self.model, filepath, optimizer=optimizer, meta=meta)
+        # use relative symlink
+        mmcv.symlink(filename, linkpath)
 
     def train(self, data_loader, **kwargs):
         self.model.train()

tests/test_runner.py

+import os.path as osp
+import tempfile
+import warnings
+
+
+def test_save_checkpoint():
+    try:
+        import torch
+        import torch.nn as nn
+    except ImportError:
+        warnings.warn('Skipping test_save_checkpoint in the absense of torch')
+        return
+
+    import mmcv.runner
+
+    model = nn.Linear(1, 1)
+    runner = mmcv.runner.Runner(
+        model=model,
+        batch_processor=lambda x: x
+    )
+
+    with tempfile.TemporaryDirectory() as root:
+        runner.save_checkpoint(root)
+
+        latest_path = osp.join(root, 'latest.pth')
+        epoch1_path = osp.join(root, 'epoch_1.pth')
+
+        assert osp.exists(latest_path)
+        assert osp.exists(epoch1_path)
+        assert osp.realpath(latest_path) == epoch1_path
+
+        torch.load(latest_path)