[Enhancement] Support registering function (#1858)

* [Enhance] Support register function.

* fix unittest error

* add docs and unittest of register function

* modify the docs

* fix version to 1.5.1

* Update docs/zh_cn/understand_mmcv/registry.md

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* Update docs/en/understand_mmcv/registry.md

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* refine the docs

* modify module_class to module

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

docs/en/understand_mmcv/registry.md

@@ -3,11 +3,15 @@
 MMCV implements [registry](https://github.com/open-mmlab/mmcv/blob/master/mmcv/utils/registry.py) to manage different modules that share similar functionalities, e.g., backbones, head, and necks, in detectors.
 Most projects in OpenMMLab use registry to manage modules of datasets and models, such as [MMDetection](https://github.com/open-mmlab/mmdetection), [MMDetection3D](https://github.com/open-mmlab/mmdetection3d), [MMClassification](https://github.com/open-mmlab/mmclassification), [MMEditing](https://github.com/open-mmlab/mmediting), etc.
 
+```{note}
+In v1.5.1 and later, the Registry supports registering functions and calling them.
+```
+
 ### What is registry
 
-In MMCV, registry can be regarded as a mapping that maps a class to a string.
+In MMCV, registry can be regarded as a mapping that maps a class or function to a string.
-These classes contained by a single registry usually have similar APIs but implement different algorithms or support different datasets.
+These classes or functions contained by a single registry usually have similar APIs but implement different algorithms or support different datasets.
-With the registry, users can find and instantiate the class through its corresponding string, and use the instantiated module as they want.
+With the registry, users can find the class or function through its corresponding string, and instantiate the corresponding module or call the function to obtain the result according to needs.
 One typical example is the config systems in most OpenMMLab projects, which use the registry to create hooks, runners, models, and datasets, through configs.
 The API reference could be found [here](https://mmcv.readthedocs.io/en/latest/api.html?highlight=registry#mmcv.utils.Registry).
 
@@ -17,7 +21,7 @@ To manage your modules in the codebase by `Registry`, there are three steps as b
 2. Create a registry.
 3. Use this registry to manage the modules.
 
-`build_func` argument of `Registry` is to customize how to instantiate the class instance, the default one is `build_from_cfg` implemented [here](https://mmcv.readthedocs.io/en/latest/api.html?highlight=registry#mmcv.utils.build_from_cfg).
+`build_func` argument of `Registry` is to customize how to instantiate the class instance or how to call the function to obtain the result, the default one is `build_from_cfg` implemented [here](https://mmcv.readthedocs.io/en/latest/api.html?highlight=registry#mmcv.utils.build_from_cfg).
 
 ### A Simple Example
 
@@ -34,7 +38,7 @@ from mmcv.utils import Registry
 CONVERTERS = Registry('converters')
 ```
 
-Then we can implement different converters in the package. For example, implement `Converter1` in `converters/converter1.py`
+Then we can implement different converters that is class or function in the package. For example, implement `Converter1` in `converters/converter1.py`, and `converter2` in `converters/converter2.py`.
 
 ```python
 
@@ -47,11 +51,22 @@ class Converter1(object):
         self.a = a
         self.b = b
 ```
+```python
+# converter2.py
+from .builder import CONVERTERS
+from .converter1 import Converter1
+
+# 使用注册器管理模块
+@CONVERTERS.register_module()
+def converter2(a, b)
+    return Converter1(a, b)
+```
 The key step to use registry for managing the modules is to register the implemented module into the registry `CONVERTERS` through
-`@CONVERTERS.register_module()` when you are creating the module. By this way, a mapping between a string and the class is built and maintained by `CONVERTERS` as below
+`@CONVERTERS.register_module()` when you are creating the module. By this way, a mapping between a string and the class (function) is built and maintained by `CONVERTERS` as below
 
 ```python
 'Converter1' -> <class 'Converter1'>
+'converter2' -> <function 'converter2'>
 ```
 ```{note}
 The registry mechanism will be triggered only when the file where the module is located is imported.
@@ -61,8 +76,11 @@ So you need to import that file somewhere. More details can be found at https://
 If the module is successfully registered, you can use this converter through configs as
 
 ```python
-converter_cfg = dict(type='Converter1', a=a_value, b=b_value)
+converter1_cfg = dict(type='Converter1', a=a_value, b=b_value)
-converter = CONVERTERS.build(converter_cfg)
+converter2_cfg = dict(type='converter2', a=a_value, b=b_value)
+converter1 = CONVERTERS.build(converter1_cfg)
+# returns the calling result
+result = CONVERTERS.build(converter2_cfg)
 ```
 
 ### Customize Build Function

docs/zh_cn/understand_mmcv/registry.md

@@ -2,10 +2,14 @@
 MMCV 使用 [注册器](https://github.com/open-mmlab/mmcv/blob/master/mmcv/utils/registry.py) 来管理具有相似功能的不同模块, 例如, 检测器中的主干网络、头部、和模型颈部。
 在 OpenMMLab 家族中的绝大部分开源项目使用注册器去管理数据集和模型的模块，例如 [MMDetection](https://github.com/open-mmlab/mmdetection), [MMDetection3D](https://github.com/open-mmlab/mmdetection3d), [MMClassification](https://github.com/open-mmlab/mmclassification), [MMEditing](https://github.com/open-mmlab/mmediting) 等。
 
+```{note}
+在 v1.5.1 版本开始支持注册函数的功能。
+```
+
 ### 什么是注册器
-在MMCV中，注册器可以看作类到字符串的映射。
+在MMCV中，注册器可以看作类或函数到字符串的映射。
-一个注册器中的类通常有相似的接口，但是可以实现不同的算法或支持不同的数据集。
+一个注册器中的类或函数通常有相似的接口，但是可以实现不同的算法或支持不同的数据集。
-借助注册器，用户可以通过使用相应的字符串查找并实例化该类，并根据他们的需要实例化对应模块。
+借助注册器，用户可以通过使用相应的字符串查找类或函数，并根据他们的需要实例化对应模块或调用函数获取结果。
 一个典型的案例是，OpenMMLab　中的大部分开源项目的配置系统，这些系统通过配置文件来使用注册器创建钩子、执行器、模型和数据集。
 可以在[这里](https://mmcv.readthedocs.io/en/latest/api.html?highlight=registry#mmcv.utils.Registry)找到注册器接口使用文档。
 
@@ -15,7 +19,7 @@ MMCV 使用 [注册器](https://github.com/open-mmlab/mmcv/blob/master/mmcv/util
 2. 创建注册器
 3. 使用此注册器来管理模块
 
-`Registry`（注册器）的参数 `build_func`（构建函数） 用来自定以如何实例化类的实例，默认使用 [这里](https://mmcv.readthedocs.io/en/latest/api.html?highlight=registry#mmcv.utils.build_from_cfg)实现的`build_from_cfg`。
+`Registry`（注册器）的参数 `build_func`（构建函数） 用来自定义如何实例化类的实例或如何调用函数获取结果，默认使用 [这里](https://mmcv.readthedocs.io/en/latest/api.html?highlight=registry#mmcv.utils.build_from_cfg) 实现的`build_from_cfg`。
 
 ### 一个简单的例子
 
@@ -29,9 +33,10 @@ from mmcv.utils import Registry
 CONVERTERS = Registry('converter')
 ```
 
-然后我们在包中可以实现不同的转换器（converter）。例如，在 `converters/converter1.py` 中实现 `Converter1`。
+然后我们在包中可以实现不同的转换器（converter），其可以为类或函数。例如，在 `converters/converter1.py` 中实现 `Converter1`，在 `converters/converter2.py` 中实现 `converter2`。
 
 ```python
+# converter1.py
 from .builder import CONVERTERS
 
 # 使用注册器管理模块
@@ -41,12 +46,23 @@ class Converter1(object):
         self.a = a
         self.b = b
 ```
-使用注册器管理模块的关键步骤是，将实现的模块注册到注册表 `CONVERTERS` 中。通过 `@CONVERTERS.register_module()` 装饰所实现的模块，字符串和类之间的映射就可以由 `CONVERTERS` 构建和维护，如下所示：
+```python
+# converter2.py
+from .builder import CONVERTERS
+from .converter1 import Converter1
 
-通过这种方式，就可以通过 `CONVERTERS` 建立字符串与类之间的映射，如下所示：
+# 使用注册器管理模块
+@CONVERTERS.register_module()
+def converter2(a, b)
+    return Converter1(a, b)
+```
+使用注册器管理模块的关键步骤是，将实现的模块注册到注册表 `CONVERTERS` 中。通过 `@CONVERTERS.register_module()` 装饰所实现的模块，字符串到类或函数之间的映射就可以由 `CONVERTERS` 构建和维护，如下所示：
+
+通过这种方式，就可以通过 `CONVERTERS` 建立字符串与类或函数之间的映射，如下所示：
 
 ```python
 'Converter1' -> <class 'Converter1'>
+'converter2' -> <function 'converter2'>
 ```
 ```{note}
 只有模块所在的文件被导入时，注册机制才会被触发，所以您需要在某处导入该文件。更多详情请查看 https://github.com/open-mmlab/mmdetection/issues/5974。
@@ -54,8 +70,11 @@ class Converter1(object):
 如果模块被成功注册了，你可以通过配置文件使用这个转换器（converter），如下所示：
 
 ```python
-converter_cfg = dict(type='Converter1', a=a_value, b=b_value)
+converter1_cfg = dict(type='Converter1', a=a_value, b=b_value)
-converter = CONVERTERS.build(converter_cfg)
+converter2_cfg = dict(type='converter2', a=a_value, b=b_value)
+converter1 = CONVERTERS.build(converter1_cfg)
+# returns the calling result
+result = CONVERTERS.build(converter2_cfg)
 ```
 
 ### 自定义构建函数

mmcv/utils/registry.py

@@ -3,11 +3,25 @@ import inspect
 import warnings
 from functools import partial
 
-from .misc import is_seq_of
+from .misc import deprecated_api_warning, is_seq_of
 
 
 def build_from_cfg(cfg, registry, default_args=None):
-    """Build a module from config dict.
+    """Build a module from config dict when it is a class configuration, or
+    call a function from config dict when it is a function configuration.
+
+    Example:
+        >>> MODELS = Registry('models')
+        >>> @MODELS.register_module()
+        >>> class ResNet:
+        >>>     pass
+        >>> resnet = build_from_cfg(dict(type='Resnet'), MODELS)
+        >>> # Returns an instantiated object
+        >>> @MODELS.register_module()
+        >>> def resnet50():
+        >>>     pass
+        >>> resnet = build_from_cfg(dict(type='resnet50'), MODELS)
+        >>> # Return a result of the calling function
 
     Args:
         cfg (dict): Config dict. It should at least contain the key "type".
@@ -43,7 +57,7 @@ def build_from_cfg(cfg, registry, default_args=None):
         if obj_cls is None:
             raise KeyError(
                 f'{obj_type} is not in the {registry.name} registry')
-    elif inspect.isclass(obj_type):
+    elif inspect.isclass(obj_type) or inspect.isfunction(obj_type):
         obj_cls = obj_type
     else:
         raise TypeError(
@@ -56,9 +70,10 @@ def build_from_cfg(cfg, registry, default_args=None):
 
 
 class Registry:
-    """A registry to map strings to classes.
+    """A registry to map strings to classes or functions.
 
-    Registered object could be built from registry.
+    Registered object could be built from registry. Meanwhile, registered
+    functions could be called from registry.
 
     Example:
         >>> MODELS = Registry('models')
@@ -66,6 +81,10 @@ class Registry:
         >>> class ResNet:
         >>>     pass
         >>> resnet = MODELS.build(dict(type='ResNet'))
+        >>> @MODELS.register_module()
+        >>> def resnet50():
+        >>>     pass
+        >>> resnet = MODELS.build(dict(type='resnet50'))
 
     Please refer to
     https://mmcv.readthedocs.io/en/latest/understand_mmcv/registry.html for
@@ -235,20 +254,21 @@ class Registry:
             f'scope {registry.scope} exists in {self.name} registry'
         self.children[registry.scope] = registry
 
-    def _register_module(self, module_class, module_name=None, force=False):
+    @deprecated_api_warning(name_dict=dict(module_class='module'))
-        if not inspect.isclass(module_class):
+    def _register_module(self, module, module_name=None, force=False):
-            raise TypeError('module must be a class, '
+        if not inspect.isclass(module) and not inspect.isfunction(module):
-                            f'but got {type(module_class)}')
+            raise TypeError('module must be a class or a function, '
+                            f'but got {type(module)}')
 
         if module_name is None:
-            module_name = module_class.__name__
+            module_name = module.__name__
         if isinstance(module_name, str):
             module_name = [module_name]
         for name in module_name:
             if not force and name in self._module_dict:
                 raise KeyError(f'{name} is already registered '
                                f'in {self.name}')
-            self._module_dict[name] = module_class
+            self._module_dict[name] = module
 
     def deprecated_register_module(self, cls=None, force=False):
         warnings.warn(
@@ -289,7 +309,7 @@ class Registry:
                 specified, the class name will be used.
             force (bool, optional): Whether to override an existing class with
                 the same name. Default: False.
-            module (type): Module class to be registered.
+            module (type): Module class or function to be registered.
         """
         if not isinstance(force, bool):
             raise TypeError(f'force must be a boolean, but got {type(force)}')
@@ -306,14 +326,12 @@ class Registry:
 
         # use it as a normal method: x.register_module(module=SomeClass)
         if module is not None:
-            self._register_module(
+            self._register_module(module=module, module_name=name, force=force)
-                module_class=module, module_name=name, force=force)
             return module
 
         # use it as a decorator: @x.register_module()
-        def _register(cls):
+        def _register(module):
-            self._register_module(
+            self._register_module(module=module, module_name=name, force=force)
-                module_class=cls, module_name=name, force=force)
+            return module
-            return cls
 
         return _register

tests/test_utils/test_registry.py

@@ -89,12 +89,23 @@ def test_registry():
     with pytest.raises(TypeError):
         CATS.register_module(0)
 
-    # can only decorate a class
+    @CATS.register_module()
+    def muchkin():
+        pass
+
+    assert CATS.get('muchkin') is muchkin
+    assert 'muchkin' in CATS
+
+    # can only decorate a class or a function
     with pytest.raises(TypeError):
 
-        @CATS.register_module()
+        class Demo:
-        def some_method():
+
-            pass
+            def some_method(self):
+                pass
+
+        method = Demo().some_method
+        CATS.register_module(name='some_method', module=method)
 
     # begin: test old APIs
     with pytest.warns(DeprecationWarning):