[Feature] Support revise_keys in load_checkpoint(). (#829)

* Simplified the code.

* Improved chkpt compatibility.

* One may modify the checkpoint via adding keywords.

* Tiny.

* Following reviewer's suggestion.

* Added unit_test.

* Fixed.

* Modify the state_dict  with  construction.

* Added test.

* Modified。

* Mimimalised the modification.

* Added the docstring.

* Format.

* Improved.

* Tiny.

* Temp file.

* Added assertion.

* Doc string.

* Fixed.

mmcv/cnn/utils/weight_init.py

@@ -310,6 +310,7 @@ class PretrainedInit(object):
             initialize. For example, if we would like to only load the
             backbone of a detector model, we can set ``prefix='backbone.'``.
             Defaults to None.
+        map_location (str): map tensors into proper locations.
     """
 
     def __init__(self, checkpoint, prefix=None, map_location=None):

mmcv/runner/base_runner.py

@@ -103,7 +103,6 @@ class BaseRunner(metaclass=ABCMeta):
         self.optimizer = optimizer
         self.logger = logger
         self.meta = meta
-
         # create work_dir
         if mmcv.is_str(work_dir):
             self.work_dir = osp.abspath(work_dir)
@@ -307,10 +306,20 @@ class BaseRunner(metaclass=ABCMeta):
         for hook in self._hooks:
             getattr(hook, fn_name)(self)
 
-    def load_checkpoint(self, filename, map_location='cpu', strict=False):
+    def load_checkpoint(self,
+                        filename,
+                        map_location='cpu',
+                        strict=False,
+                        revise_keys=[(r'^module.', '')]):
+
         self.logger.info('load checkpoint from %s', filename)
-        return load_checkpoint(self.model, filename, map_location, strict,
-                               self.logger)
+        return load_checkpoint(
+            self.model,
+            filename,
+            map_location,
+            strict,
+            self.logger,
+            revise_keys=revise_keys)
 
     def resume(self,
                checkpoint,

mmcv/runner/checkpoint.py

@@ -3,6 +3,7 @@ import io
 import os
 import os.path as osp
 import pkgutil
+import re
 import time
 import warnings
 from collections import OrderedDict
@@ -503,7 +504,8 @@ def load_checkpoint(model,
                     filename,
                     map_location=None,
                     strict=False,
-                    logger=None):
+                    logger=None,
+                    revise_keys=[(r'^module\.', '')]):
     """Load checkpoint from a file or URI.
 
     Args:
@@ -515,6 +517,11 @@ def load_checkpoint(model,
         strict (bool): Whether to allow different params for the model and
             checkpoint.
         logger (:mod:`logging.Logger` or None): The logger for error message.
+        revise_keys (list): A list of customized keywords to modify the
+            state_dict in checkpoint. Each item is a (pattern, replacement)
+            pair of the regular expression operations. Default: strip
+            the prefix 'module.' by [(r'^module\\.', '')].
+
 
     Returns:
         dict or OrderedDict: The loaded checkpoint.
@@ -530,8 +537,8 @@ def load_checkpoint(model,
     else:
         state_dict = checkpoint
     # strip prefix of state_dict
-    if list(state_dict.keys())[0].startswith('module.'):
-        state_dict = {k[7:]: v for k, v in state_dict.items()}
+    for p, r in revise_keys:
+        state_dict = {re.sub(p, r, k): v for k, v in state_dict.items()}
     # load state_dict
     load_state_dict(model, state_dict, strict, logger)
     return checkpoint

tests/test_runner/test_checkpoint.py

@@ -10,7 +10,8 @@ from torch.nn.parallel import DataParallel
 
 from mmcv.parallel.registry import MODULE_WRAPPERS
 from mmcv.runner.checkpoint import (_load_checkpoint_with_prefix,
-                                    get_state_dict, load_from_pavi)
+                                    get_state_dict, load_checkpoint,
+                                    load_from_pavi)
 
 
 @MODULE_WRAPPERS.register_module()
@@ -188,6 +189,38 @@ def test_load_checkpoint_with_prefix():
             _load_checkpoint_with_prefix(prefix, 'model.pth')
 
 
+def test_load_checkpoint():
+    import os
+    import tempfile
+    import re
+
+    class PrefixModel(nn.Module):
+
+        def __init__(self):
+            super().__init__()
+            self.backbone = Model()
+
+    pmodel = PrefixModel()
+    model = Model()
+    checkpoint_path = os.path.join(tempfile.gettempdir(), 'checkpoint.pth')
+
+    # add prefix
+    torch.save(model.state_dict(), checkpoint_path)
+    state_dict = load_checkpoint(
+        pmodel, checkpoint_path, revise_keys=[(r'^', 'backbone.')])
+    for key in pmodel.backbone.state_dict().keys():
+        assert torch.equal(pmodel.backbone.state_dict()[key], state_dict[key])
+    # strip prefix
+    torch.save(pmodel.state_dict(), checkpoint_path)
+    state_dict = load_checkpoint(
+        model, checkpoint_path, revise_keys=[(r'^backbone\.', '')])
+
+    for key in state_dict.keys():
+        key_stripped = re.sub(r'^backbone\.', '', key)
+        assert torch.equal(model.state_dict()[key_stripped], state_dict[key])
+    os.remove(checkpoint_path)
+
+
 def test_load_classes_name():
     import os
 

tests/test_runner/test_hooks.py

@@ -6,6 +6,7 @@ CommandLine:
 """
 import logging
 import os.path as osp
+import re
 import shutil
 import sys
 import tempfile
@@ -415,3 +416,42 @@ def _build_demo_runner(runner_type='EpochBasedRunner',
     runner.register_checkpoint_hook(dict(interval=1))
     runner.register_logger_hooks(log_config)
     return runner
+
+
+def test_runner_with_revise_keys():
+
+    import os
+
+    class Model(nn.Module):
+
+        def __init__(self):
+            super().__init__()
+            self.conv = nn.Conv2d(3, 3, 1)
+
+    class PrefixModel(nn.Module):
+
+        def __init__(self):
+            super().__init__()
+            self.backbone = Model()
+
+    pmodel = PrefixModel()
+    model = Model()
+    checkpoint_path = os.path.join(tempfile.gettempdir(), 'checkpoint.pth')
+
+    # add prefix
+    torch.save(model.state_dict(), checkpoint_path)
+    runner = _build_demo_runner(runner_type='EpochBasedRunner')
+    runner.model = pmodel
+    state_dict = runner.load_checkpoint(
+        checkpoint_path, revise_keys=[(r'^', 'backbone.')])
+    for key in pmodel.backbone.state_dict().keys():
+        assert torch.equal(pmodel.backbone.state_dict()[key], state_dict[key])
+    # strip prefix
+    torch.save(pmodel.state_dict(), checkpoint_path)
+    runner.model = model
+    state_dict = runner.load_checkpoint(
+        checkpoint_path, revise_keys=[(r'^backbone\.', '')])
+    for key in state_dict.keys():
+        key_stripped = re.sub(r'^backbone\.', '', key)
+        assert torch.equal(model.state_dict()[key_stripped], state_dict[key])
+    os.remove(checkpoint_path)