EvalHook uses case-insensitive key indicator matching and configurabl… (#1076)

* EvalHook uses case-insensitive key indicator matching and configurable test functions

* * fix docstring

* * move test_fn import into __init__
* configurable greater/less keys

* * update unittest
* update DistEvalHook

* fix comments and remove debug code

* support single greater/less key

mmcv/runner/hooks/evaluation.py

@@ -7,6 +7,7 @@ import torch.distributed as dist
 from torch.nn.modules.batchnorm import _BatchNorm
 from torch.utils.data import DataLoader
 
+from mmcv.utils import is_seq_of
 from .hook import Hook
 
 
@@ -41,6 +42,16 @@ class EvalHook(Hook):
             .etc will be inferred by 'greater' rule. Keys contain 'loss' will
             be inferred by 'less' rule. Options are 'greater', 'less', None.
             Default: None.
+        test_fn (callable, optional): test a model with samples from a
+            dataloader, and return the test results. If ``None``, the default
+            test function ``mmcv.engine.single_gpu_test`` will be used.
+            (default: ``None``)
+        greater_keys (List[str] | None, optional): Metric keys that will be
+            inferred by 'greater' comparison rule rule. If ``None``,
+            _default_greater_keys will be used. (default: ``None``)
+        less_keys (List[str] | None, optional): Metric keys that will be
+            inferred by 'less' comparison rule. If ``None``, _default_less_keys
+            will be used. (default: ``None``)
         **eval_kwargs: Evaluation arguments fed into the evaluate function of
             the dataset.
 
@@ -55,11 +66,11 @@ class EvalHook(Hook):
 
     rule_map = {'greater': lambda x, y: x > y, 'less': lambda x, y: x < y}
     init_value_map = {'greater': -inf, 'less': inf}
-    greater_keys = [
+    _default_greater_keys = [
         'acc', 'top', 'AR@', 'auc', 'precision', 'mAP', 'mDice', 'mIoU',
         'mAcc', 'aAcc'
     ]
-    less_keys = ['loss']
+    _default_less_keys = ['loss']
 
     def __init__(self,
                  dataloader,
@@ -68,6 +79,9 @@ class EvalHook(Hook):
                  by_epoch=True,
                  save_best=None,
                  rule=None,
+                 test_fn=None,
+                 greater_keys=None,
+                 less_keys=None,
                  **eval_kwargs):
         if not isinstance(dataloader, DataLoader):
             raise TypeError(f'dataloader must be a pytorch DataLoader, '
@@ -95,6 +109,28 @@ class EvalHook(Hook):
         self.eval_kwargs = eval_kwargs
         self.initial_flag = True
 
+        if test_fn is None:
+            from mmcv.engine import single_gpu_test
+            self.test_fn = single_gpu_test
+        else:
+            self.test_fn = test_fn
+
+        if greater_keys is None:
+            self.greater_keys = self._default_greater_keys
+        else:
+            if not isinstance(greater_keys, (list, tuple)):
+                greater_keys = (greater_keys, )
+            assert is_seq_of(greater_keys, str)
+            self.greater_keys = greater_keys
+
+        if less_keys is None:
+            self.less_keys = self._default_less_keys
+        else:
+            if not isinstance(less_keys, (list, tuple)):
+                less_keys = (less_keys, )
+            assert is_seq_of(less_keys, str)
+            self.less_keys = less_keys
+
         if self.save_best is not None:
             self.best_ckpt_path = None
             self._init_rule(rule, self.save_best)
@@ -103,7 +139,8 @@ class EvalHook(Hook):
         """Initialize rule, key_indicator, comparison_func, and best score.
 
         Here is the rule to determine which rule is used for key indicator
-        when the rule is not specific:
+        when the rule is not specific (note that the key indicator matching
+        is case-insensitive):
         1. If the key indicator is in ``self.greater_keys``, the rule will be
            specified as 'greater'.
         2. Or if the key indicator is in ``self.less_keys``, the rule will be
@@ -124,13 +161,19 @@ class EvalHook(Hook):
 
         if rule is None:
             if key_indicator != 'auto':
-                if key_indicator in self.greater_keys:
+                # `_lc` here means we use the lower case of keys for
+                # case-insensitive matching
+                key_indicator_lc = key_indicator.lower()
+                greater_keys = [key.lower() for key in self.greater_keys]
+                less_keys = [key.lower() for key in self.less_keys]
+
+                if key_indicator_lc in greater_keys:
                     rule = 'greater'
-                elif key_indicator in self.less_keys:
+                elif key_indicator_lc in less_keys:
                     rule = 'less'
-                elif any(key in key_indicator for key in self.greater_keys):
+                elif any(key in key_indicator_lc for key in greater_keys):
                     rule = 'greater'
-                elif any(key in key_indicator for key in self.less_keys):
+                elif any(key in key_indicator_lc for key in less_keys):
                     rule = 'less'
                 else:
                     raise ValueError(f'Cannot infer the rule for key '
@@ -181,8 +224,7 @@ class EvalHook(Hook):
         if not self._should_evaluate(runner):
             return
 
-        from mmcv.engine import single_gpu_test
-        results = single_gpu_test(runner.model, self.dataloader)
+        results = self.test_fn(runner.model, self.dataloader)
         runner.log_buffer.output['eval_iter_num'] = len(self.dataloader)
         key_score = self.evaluate(runner, results)
         if self.save_best:
@@ -311,6 +353,10 @@ class DistEvalHook(EvalHook):
             .etc will be inferred by 'greater' rule. Keys contain 'loss' will
             be inferred by 'less' rule. Options are 'greater', 'less', None.
             Default: None.
+        test_fn (callable, optional): test a model with samples from a
+            dataloader in a multi-gpu manner, and return the test results. If
+            ``None``, the default test function ``mmcv.engine.multi_gpu_test``
+            will be used. (default: ``None``)
         tmpdir (str | None): Temporary directory to save the results of all
             processes. Default: None.
         gpu_collect (bool): Whether to use gpu or cpu to collect results.
@@ -329,10 +375,18 @@ class DistEvalHook(EvalHook):
                  by_epoch=True,
                  save_best=None,
                  rule=None,
+                 test_fn=None,
+                 greater_keys=None,
+                 less_keys=None,
                  broadcast_bn_buffer=True,
                  tmpdir=None,
                  gpu_collect=False,
                  **eval_kwargs):
+
+        if test_fn is None:
+            from mmcv.engine import multi_gpu_test
+            test_fn = multi_gpu_test
+
         super().__init__(
             dataloader,
             start=start,
@@ -340,7 +394,11 @@ class DistEvalHook(EvalHook):
             by_epoch=by_epoch,
             save_best=save_best,
             rule=rule,
+            test_fn=test_fn,
+            greater_keys=greater_keys,
+            less_keys=less_keys,
             **eval_kwargs)
+
         self.broadcast_bn_buffer = broadcast_bn_buffer
         self.tmpdir = tmpdir
         self.gpu_collect = gpu_collect
@@ -367,8 +425,7 @@ class DistEvalHook(EvalHook):
         if tmpdir is None:
             tmpdir = osp.join(runner.work_dir, '.eval_hook')
 
-        from mmcv.engine import multi_gpu_test
-        results = multi_gpu_test(
+        results = self.test_fn(
             runner.model,
             self.dataloader,
             tmpdir=tmpdir,

tests/test_runner/test_eval_hook.py

@@ -84,8 +84,8 @@ def _build_iter_runner():
 
 class EvalHook(BaseEvalHook):
 
-    greater_keys = ['acc', 'top']
-    less_keys = ['loss', 'loss_top']
+    _default_greater_keys = ['acc', 'top']
+    _default_less_keys = ['loss', 'loss_top']
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
@@ -273,6 +273,31 @@ def test_eval_hook():
         assert runner.meta['hook_msgs']['best_score'] == 7
         assert not osp.exists(old_ckpt_path)
 
+    # test EvalHook with customer test_fn and greater/less keys
+    loader = DataLoader(EvalDataset())
+    model = Model()
+    data_loader = DataLoader(EvalDataset())
+
+    eval_hook = EvalHook(
+        data_loader,
+        save_best='acc',
+        test_fn=mock.MagicMock(return_value={}),
+        greater_keys=[],
+        less_keys=['acc'])
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        logger = get_logger('test_eval')
+        runner = EpochBasedRunner(model=model, work_dir=tmpdir, logger=logger)
+        runner.register_checkpoint_hook(dict(interval=1))
+        runner.register_hook(eval_hook)
+        runner.run([loader], [('train', 1)], 8)
+
+        ckpt_path = osp.join(tmpdir, 'best_acc_epoch_6.pth')
+
+        assert runner.meta['hook_msgs']['best_ckpt'] == ckpt_path
+        assert osp.exists(ckpt_path)
+        assert runner.meta['hook_msgs']['best_score'] == -3
+
 
 @patch('mmcv.engine.single_gpu_test', MagicMock)
 @patch('mmcv.engine.multi_gpu_test', MagicMock)